JPWO2020241888A1 - Corrosion generation prediction model under heat insulating material and plant maintenance support device - Google Patents

Abstract

In the first aspect of the present invention, there is a method of forming at least a part of a plant, which is covered with a heat insulating material and is mounted on a computer for maintenance of equipment whose corrosion state cannot be confirmed from the appearance. The stage of acquiring the conditions including the operating temperature of the equipment and determining whether the target equipment is suitable for non-destructive inspection using a predetermined measuring device, and the heat insulating material of the target equipment based on the conditions. A first inspection to measure the surface temperature of the exterior material covering the surface of the target equipment and a second inspection to measure the amount of water contained in the heat insulating material of the target equipment, and a plurality of non-destructive without peeling of the heat insulating material including Provided is a method including a step of extracting a method suitable for measurement of a target facility from an inspection method and a step of outputting the type when one or more types of non-destructive inspection are extracted.

Description

The present invention relates to a model for predicting corrosion under a heat insulating material and a plant maintenance support device.

In heavy industry plants such as chemical plants, it is necessary to take measures against aging. Corrosion Under Insulation (CUI) of carbon steel and low alloy steel equipment is one of the damage phenomena that is common to all punto and poses a serious threat to safety.

CUI is corrosion that occurs from the outer surface of carbon steel equipment and piping that is covered by the heat insulating material that covers the equipment of the plant and the exterior material that covers the outside of the heat insulating material. Insulation and exterior materials deteriorate during plant use, and rainwater and dew water infiltrate or impregnate into the insulation and exterior materials, creating a moist atmosphere on the outer surfaces of carbon steel equipment and piping, resulting in CUI. do.

The location and degree of progress of CUI vary greatly depending on the type of plant equipment and the like. Further, since the CUI is usually hidden behind the heat insulating material and the exterior material and cannot be seen, its occurrence cannot be easily detected, which makes it difficult to maintain and manage the equipment of the plant. Currently, CUI inspection as part of the maintenance of plant equipment is carried out by installing scaffolding and peeling off the heat insulating material and exterior material. Therefore, the CUI inspection requires a large amount of cost including the installation of scaffolding, and has a problem that the CUI detection probability is low even if the heat insulating material and the exterior material are peeled off.

As mentioned in the methods described in Patent Documents 1 to 7, some methods and devices for maintaining and inspecting plant equipment in which CUI may occur are known to date.

Japanese Unexamined Patent Publication No. 2018-025497 Japanese Unexamined Patent Publication No. 2018-017704 Japanese Unexamined Patent Publication No. 2012-052933 Japanese Unexamined Patent Publication No. 2011-080937 Japanese Unexamined Patent Publication No. 2010-107362 Japanese Unexamined Patent Publication No. 2007-120126 Japanese Unexamined Patent Publication No. 2006-284416

The problem to be solved

However, at present, it is not clear how to appropriately estimate the part to be inspected for CUI, the number of equipment to be inspected for peeling is increased, and the maintenance cost of the equipment is increased. For this reason, there is a need for a maintenance support method that achieves both safety and economic efficiency for plant equipment in which CUI can occur. In order to realize maintenance support that achieves both safety and economy, the problem is that there is no highly accurate and economical non-destructive inspection method for CUI that can be applied without removing the heat insulating material. Therefore, there is a further demand for a method and a plant maintenance support device that are highly accurate and economical for the CUI and can be inspected non-destructively. In view of the above, it is an object of the present invention to provide a plant inspection support method capable of detecting CUI with high accuracy and non-destructively inspecting without removing the heat insulating material, and a plant maintenance support device for realizing the method.

In the first aspect of the present invention, there is a step of acquiring a condition including an operating temperature of the target equipment and a condition for determining whether the target equipment is suitable for non-destructive inspection using a predetermined measuring device. Includes a first inspection to measure the surface temperature of the exterior material covering the surface of the heat insulating material of the target equipment and a second inspection to measure the amount of water contained in the heat insulating material of the target equipment based on the conditions. Provides a method to extract at least one of multiple non-destructive inspection types without peeling of the thermal insulation, a method including, a device to perform the method, and a program to cause the computer to perform this method. do.

Further, in the second aspect of the present invention, there is a step of calculating the probability density f (x; μ) of the wall thinning depth x based on the parameter μ determined according to the installation condition of the equipment of the plant. Provided is a method comprising a step of evaluating the inspection necessity of the equipment of the plant based on the permissible wall thinning depth of the equipment of the plant and the probability density.

Further, in the third aspect of the present invention, there is a calculation unit that calculates the probability density f (x; μ) of the wall thinning depth x based on the parameter μ determined according to the installation status of the equipment of the plant. Provided is a plant maintenance support device including an evaluation unit for evaluating the inspection necessity of the equipment of the plant based on the allowable wall thickness reduction depth of the equipment of the plant and the probability density.

Further, in the fourth aspect of the present invention, it is a computer program including instructions, and when the instructions are executed by a processor or a programmable circuit, the plant equipment is installed in the processor or the programmable circuit. Based on the calculation unit that calculates the probability density f (x; μ) of the wall thinning depth x based on the population μ determined according to the situation, the allowable wall thinning depth of the equipment of the plant, and the probability density. Provided is a computer program that executes an operation including an evaluation unit that evaluates the inspection necessity of the equipment of the plant.

Further, in the fifth aspect of the present invention, the installation status and allowable wall thinning depth of one or more target equipment and whether the wall thinning depth of the target equipment is equal to or greater than or exceeds the allowable wall thinning depth are the target equipment. The result of the first evaluation stage to evaluate the inspection necessity of the target equipment and the evaluation result of the inspection necessity in the first evaluation stage based on the prediction model predicted based on the installation situation of For high target equipment, the evaluation of the inspection necessity in the stage of performing a peeling inspection or renewal of the target equipment with peeling of the heat insulating material and the first evaluation stage is less than the first degree and smaller than the first degree. Provided is a method including a step of performing a non-destructive inspection without peeling of a heat insulating material for a target facility having a predetermined range higher than the second degree.

Further, in the sixth aspect of the present invention, there are a plurality of prediction models that predict the wall thinning depth of the equipment based on the installation status of the equipment, and the installation status and the allowable wall thinning depth of the plurality of target equipment. The first evaluation stage to evaluate the inspection necessity of the target equipment, the stage to perform non-destructive inspection without peeling of the heat insulating material for at least one of the plurality of target equipment, and the inspection result of the non-destructive inspection. At least one of the second evaluation stage for evaluating the inspection necessity of the target equipment based on the above, the result of the evaluation of the inspection necessity in the first evaluation stage, and the result of the evaluation of the inspection necessity in the second evaluation stage. Provides a method for each of the plurality of target equipments, including the step of selectively performing at least one of target equipment renewal, peeling inspection, partial peeling inspection, condition monitoring, and post-maintenance. ..

Further, in the seventh aspect of the present invention, the stage of acquiring the installation status and the allowable wall thinning depth of the target equipment, the acquired installation status, the allowable wall thickness reduction depth, and the wall thickness reduction of the equipment based on the installation status. Based on the estimation model that estimates the depth, the stage of evaluating the inspection necessity of the target equipment, and the peeling inspection with the peeling of the heat insulating material and the peeling of the heat insulating material based on the evaluation result of the inspection necessity. Provided are methods, including non-destructive inspection without, and a step of setting at least one of the types of countermeasures, including.

Further, in the eighth aspect of the present invention, there is a temperature measurement step of measuring the surface temperature of the exterior material of the heat insulating material of the plant equipment, and the measured temperature unevenness and surface temperature of the surface temperature of the exterior material of the heat insulating material. Provided is a method comprising a determination step of determining the necessity of inspection of the equipment of the plant based on at least one of the difference between the temperature and the outside air temperature.

Further, in the ninth aspect of the present invention, there is a temperature measuring device for measuring the surface temperature of the exterior material of the heat insulating material of the plant equipment, and the measured temperature unevenness and surface temperature of the surface temperature of the exterior material of the heat insulating material. Provided is an apparatus including a determination unit for determining the necessity of inspection of equipment of the plant based on at least one of the difference between the temperature and the outside air temperature.

Further, in the tenth aspect of the present invention, it is a computer program including instructions, and when the instructions are executed by a processor or a programmable circuit, the processor or the programmable circuit keeps the plant equipment warm. Provided is a computer program that performs an operation including measuring the surface temperature of the exterior material of the material and determining the inspection necessity of the equipment of the plant based on the measured surface temperature.

Further, in the eleventh aspect of the present invention, the moisture measurement step of measuring the moisture content inside the exterior material of the heat insulating material covering the equipment of the plant by the moisture measuring device, and the measured moisture content are based on the measured moisture content. The present invention provides a method including a determination stage for determining the necessity of inspection of the equipment of the plant.

Further, in the twelfth aspect of the present invention, the equipment of the plant to be inspected is based on the prediction model generated based on the plurality of detected values of the wall thinning depth acquired in advance for the equipment of the plurality of plants. Based on the results of the preliminary judgment stage for preliminarily determining the inspection necessity and the measurement results performed on the equipment of the plant in which the inspection necessity is recognized to be more than a predetermined degree in the preliminary judgment stage. Provided is a method including a determination stage for determining the necessity of inspection of plant equipment.

Further, in the thirteenth aspect of the present invention, the water content measuring device for measuring the water content inside the exterior material of the heat insulating material covering the equipment of the plant, and the water content of the plant based on the measured water content. Provided is an apparatus including a determination unit for determining the necessity of inspection of equipment.

Further, in the fourteenth aspect of the present invention, it is a computer program including instructions, and when the instructions are executed by a processor or a programmable circuit, the processor or the programmable circuit is coated with the equipment of the plant. A computer that performs operations including measuring the amount of water inside the exterior material of the heat insulating material and determining the necessity of inspecting the equipment of the plant based on the measured amount of water. Provide a program.

Further, in the fifteenth aspect of the present invention, for each of the plurality of target equipments, the stage of acquiring the installation status and the allowable wall thinning depth, the acquired installation status and the allowable wall thickness reduction depth, and the installation status are set. Based on the prediction model that predicts the wall thinning depth of the equipment, the stage of evaluating the inspection necessity for each of the plurality of target equipment and the inspection necessity of the plurality of target equipment are relatively high. Provides a computer-implemented method, a device for performing this method, and a program for causing the computer to perform this method, including a step of outputting to emphasize the equipment.

Further, in the sixteenth aspect of the present invention, the stage of acquiring the installation status of the target equipment, determining the type of non-destructive inspection suitable for the target equipment based on the installation status, and based on the installation status. Evaluate the inspection necessity of the target equipment using a predictive model that predicts the wall thinning depth of the equipment, the stage of performing at least one of them, the type of non-destructive inspection suitable, and the inspection necessity. Provided are a computer-implemented method, a device for performing the method, and a program for causing the computer to execute the method, including a step of outputting at least one of the sex evaluation results.

In the 16th aspect, the necessity of equipment inspection is evaluated by determining the type of non-destructive inspection suitable for the equipment and using a prediction model that predicts the wall thinning depth of the equipment based on the installation situation. What to do is done in this order, and the assessment of the need for equipment inspection may be done for equipment without suitable non-destructive inspection.

The outline of the above invention does not list all the necessary features of the present invention. A subcombination of these feature groups can also be an invention.

It is a figure which shows the flow for performing maintenance of a plant in this embodiment. It is a figure which shows the structure of the plant maintenance support system 100 of this embodiment. It is a figure which shows the processing flow of the plant maintenance support apparatus 110 of this embodiment. It is a figure which shows S210 in the processing flow of the plant maintenance support apparatus 110 of this embodiment. It is a figure explaining the validity of the model which predicts the risk degree of the CUI generated in S212 in the processing flow of the plant maintenance support apparatus 110 of this embodiment. It is a figure which shows S230 in the processing flow of the plant maintenance support apparatus 110 of this embodiment. It is a figure explaining the mechanism which calculates the 1st evaluation result of inspection necessity in S230 in the processing flow of the plant maintenance support apparatus 110 of this embodiment. It is a figure which shows S230 in the processing flow of the plant maintenance support apparatus 110 of this embodiment. It is a figure which shows an example which displays the 1st evaluation result obtained in S232 in the processing flow of the plant maintenance support apparatus 110 of this embodiment. It is a figure which shows an example which displays the 1st evaluation result obtained in S232 in the processing flow of the plant maintenance support apparatus 110 of this embodiment. It is a figure which shows S250 in the processing flow of the plant maintenance support apparatus 110 of this embodiment. It is a figure which shows S260 in the processing flow of the plant maintenance support apparatus 110 of this embodiment. It is a figure which verified the prediction accuracy of the preliminary determination obtained in S232 in the processing flow of the plant maintenance support apparatus 110 of this embodiment. It is a figure which compared the prediction accuracy of the preliminary judgment obtained in S232 in the processing flow of the plant maintenance support apparatus 110 of this embodiment, and the prediction accuracy of the preliminary judgment obtained by using a conventional model. It is a figure which compared the prediction accuracy of the preliminary judgment obtained in S232 in the processing flow of the plant maintenance support apparatus 110 of this embodiment, and the prediction accuracy of the preliminary judgment obtained by using a conventional model. It is a figure which verified the result of the determination obtained in S264 in the processing flow of the plant maintenance support apparatus 110 of this embodiment. It is a figure which verified the result of the determination obtained in S265 in the processing flow of the plant maintenance support apparatus 110 of this embodiment. It is a figure which verified the result of the determination obtained in S265 in the processing flow of the plant maintenance support apparatus 110 of this embodiment. An example of the hardware configuration of the computer 1900 is shown.

Hereinafter, the present invention will be described through embodiments of the invention, but the following embodiments do not limit the invention according to the claims. Also, not all combinations of features described in the embodiments are essential to the means of solving the invention.

<Flow of plant maintenance and inspection> In this embodiment, maintenance that balances safety and economy for equipment that constitutes at least a part of the plant and is covered with a heat insulating material and whose corrosion state cannot be confirmed from the outside. And how to perform inspections as part of equipment maintenance, as well as equipment to support this method. In order to perform maintenance and inspection that achieves both safety and economy, by accurately identifying the location where corrosion under the heat insulating material is occurring, the target equipment that carries out costly peeling inspection with peeling of the heat insulating material. , And its location is important. The method for performing maintenance and inspection in the present embodiment is to use a prediction model generated based on a plurality of detection values of the wall thinning depth acquired in advance for a plurality of facilities in which corrosion under the heat insulating material occurs, and to perform the maintenance and inspection of the target equipment. One of the types of non-destructive inspection conducted using a predetermined measuring device without peeling of the heat insulating material, which is suitable for the target equipment, to evaluate the possibility of damage to the target equipment as a necessity of inspection. Or determine the type of multiple non-destructive inspections, perform non-destructive inspections suitable for the target equipment, evaluate the need for inspection of the target equipment using a predictive model and / or use a given measuring device. Includes at least one method of determining a maintenance method for the target equipment based on an assessment of the need for peeling inspection of the target equipment based on the measurement results of the non-destructive inspection. The method may be performed by one or more computers and predetermined software implemented in the one or more computers.

In the present disclosure, maintenance means an activity to take prescribed countermeasures (equipment renewal including inspection and repair, condition monitoring, etc.) for the target equipment in order to operate the target equipment economically and safely. Further, in the present disclosure, the inspection includes a destructive inspection and a non-destructive inspection. One of the destructive inspections for plant equipment where CUI can occur is a peeling inspection in which the heat insulating material is peeled off to check the state of corrosion of the equipment, and if necessary, the corrosion depth of the equipment is measured. In addition, non-destructive inspection of plant equipment where CUI may occur is performed by measuring the factors that cause corrosion of the equipment (for example, the amount of water contained in the heat insulating material) without peeling off the heat insulating material. Includes inspections to estimate corrosion conditions (eg, corrosion depth and corrosion distribution). Further, in the present disclosure, the evaluation of inspection necessity may be to evaluate the necessity of inspection for the target equipment including peeling inspection and non-destructive inspection, and the non-destructive inspection has already been carried out at the time of evaluation. If so, it may be possible to evaluate the necessity of the peeling inspection for the target equipment and the degree of the peeling inspection. The degree of the peeling inspection may be, for example, the area of the target equipment where the heat insulating material is peeled off. In addition, the evaluation of the necessity of inspection may include evaluating the possibility of damage to the target equipment due to corrosion under the heat insulating material. In addition, the assessment of inspection needs may include possible countermeasures for the target equipment. For example, if the degree of inspection necessity is greater than a predetermined degree, it may include recommending a peeling inspection or equipment renewal. Further, the peeling inspection includes a full peeling inspection in which the heat insulating material of the target equipment is peeled over the entire surface and a partial peeling inspection in which a part thereof is peeled off. Further, the peeling inspection may include a first peeling inspection for peeling the first ratio or more of the heat insulating material of the target equipment and a second peeling inspection for peeling less than the first ratio. When the full peeling inspection corresponds to the peeling inspection, the partial peeling inspection corresponds to the second peeling inspection.

FIG. 1 is a flow chart showing a flow of maintenance in the present embodiment. The maintenance flow shown in FIG. 1 can be carried out, for example, by a plant equipment maintenance manager or an inspector using a plant maintenance support system described later. As shown in FIG. 1, in S100, data on the installation status of equipment of one or more plants to be inspected for maintenance, which is covered with a heat insulating material and whose corrosion state cannot be confirmed from the appearance. (S100). The acquired data may include information on the type of equipment, the installation period of the equipment, and the operating temperature.

Subsequently, the necessity of inspection of the target equipment is evaluated using the data on the installation status of the target equipment and the prediction model that predicts the risk level of the CUI based on the installation status of the equipment (S101). In addition, you may proceed to the process of S103 which will be described later after S100 without performing S101. The evaluation of the inspection necessity of the target equipment may be executed by the plant maintenance support system described later performing arithmetic processing using the prediction model in the arithmetic unit. The prediction model may be a model generated by using a data group including pre-measured wall thinning depths for a plurality of facilities having different installation conditions, and predicts the wall thinning depths of the target facilities as a probability. It may be a model, that is, a model that predicts the possibility that the target equipment will be damaged by the CUI. The details of the prediction model will be described later. Further, it is preferable that the evaluation of the inspection necessity of the target equipment is performed based on the possibility of damage output by the prediction model and the degree of influence of the result when the target equipment is damaged. That is, it is preferable that the higher the possibility of damage to the target equipment and the greater the degree of influence of the result when the target equipment is damaged, the higher the evaluation of the necessity of inspection. The details of the prediction model and the evaluation of the inspection necessity of the target equipment using the prediction model will be described later.

In S102, at least one countermeasure to be taken for the target equipment is extracted from a plurality of types of countermeasures based on the evaluation result (degree of inspection necessity) of the target equipment using the prediction model. .. In this embodiment, the degree of evaluation of inspection necessity is classified into four types: small (A rank), medium (B rank), large (C rank), and extra large (D rank). In S102, for the target equipment in the predetermined range (first degree) where the degree of evaluation of inspection necessity is the highest, that is, the equipment with oversized inspection necessity, peeling inspection or equipment is provided as a countermeasure. We decided to update the equipment to be replaced and proceed to S110.

On the other hand, for equipment in a predetermined range (less than the first degree and above the second degree) in which the evaluation of inspection necessity is lower than the oversized, for example, equipment having a large to small degree of evaluation of inspection necessity. In order to examine in more detail whether or not to perform a peeling inspection, and to perform a nondestructive inspection to narrow down the target site when performing a peeling inspection, the subject is subject to the nondestructive inspection in advance. Proceed to S103 to determine whether the equipment is suitable for non-destructive inspection using a predetermined measuring device. The first degree and the second degree may be appropriately set, and for example, the case where the inspection necessity is 0 may be set as the second degree. Further, it may be determined whether or not the target equipment is suitable for non-destructive inspection using a predetermined measuring device for all of the target equipment. Further, the applicability of the non-destructive inspection in S103 is determined based on the conditions when the measurement is performed on the target equipment. This condition includes at least the operating temperature condition among the equipment installation conditions acquired in S100. Other conditions described later may be used as the conditions. The determination of the applicability of the non-destructive inspection may be executed by the plant maintenance support system described later performing arithmetic processing using a predetermined determination model in the arithmetic unit. A determination flow for determining the applicability of the nondestructive inspection may be executed by a predetermined determination model. For non-destructive inspection, the first inspection is to measure the surface temperature of the exterior material that covers the surface of the heat insulating material using a temperature measuring device, and the amount of water contained in the heat insulating material of the target equipment is measured using a moisture measuring device. It is preferable that a suitable non-destructive inspection method is extracted from a plurality of non-destructive inspection methods including the first inspection and the second inspection.

In S104, when there is no non-destructive inspection method suitable for the target equipment (NO in S104), for example, a visual inspection is performed on the target equipment as an inspection without using a predetermined measuring device. The part to be peeled off is narrowed down (S108), and the partial peeling inspection is carried out targeting a specific part of the target equipment (S112). For the target equipment for which there is no suitable non-destructive inspection method (NO in S104), the inspection site for peeling inspection is not narrowed down according to the evaluation result of inspection necessity by the prediction model. A peeling test may be performed.

On the other hand, in S104, when a non-destructive inspection method suitable for the target equipment exists (YES in S104), a non-destructive inspection is performed on the target equipment (S105), and based on the result of the non-destructive inspection. , The need for further inspection is evaluated (S106). The evaluation of the inspection necessity in S106 may be performed by correcting the evaluation of the inspection necessity using the prediction model performed in S101.

In S107, at least one response to the target equipment from a plurality of types of countermeasures based on the evaluation result (degree of inspection necessity) of the target equipment using the inspection result of the non-destructive inspection. Extract the plan. In the present embodiment, as described above, the degree of evaluation of the necessity of inspection is classified into four types: small (A), medium (B), large (C), and extra large (D). In S107, for the target equipment in the predetermined range (third degree) where the evaluation of inspection necessity is the highest, that is, the equipment with extra large inspection necessity, peel inspection or equipment renewal to replace the equipment is performed. It is decided to do it, and the process proceeds to S110. Further, in S107, equipment having an evaluation of inspection necessity in a predetermined range lower than the oversized size (less than a third degree and a fourth degree or more smaller than a third degree), for example, an evaluation of inspection necessity. For equipment with a large or medium degree of It is decided to carry out a peeling inspection, and the process proceeds to S112. Further, in S107, for equipment whose inspection necessity evaluation is lower than medium (less than the fourth degree), for example, equipment whose inspection necessity evaluation is small, condition monitoring and target At least one of the post-maintenance measures will be taken to deal with the case where an abnormality occurs due to corrosion under the heat insulating material in the equipment, and the process proceeds to S111.

The third degree and the fourth degree may be appropriately set. For example, the third degree may be the same as the first degree, and the fourth degree may be the same as the second degree. There may be. Further, as described above, the evaluation of the inspection necessity of the target equipment may include the evaluation of the possibility of damage to the target equipment based on the inspection result of the non-destructive inspection, and further, the possibility of damage to the target equipment may occur. And, it may be performed based on the evaluation of the degree of influence of the result when the target equipment is damaged. That is, it is preferable that the lower the possibility of damage to the target equipment and the smaller the degree of influence as a result when the target equipment is damaged, the lower the evaluation necessity of inspection.

In this way, for one or more target equipment, evaluation of inspection necessity based on the prediction model (first evaluation stage) and evaluation of inspection necessity based on the inspection result of non-destructive inspection (second evaluation). Perform at least one of the steps). Furthermore, based on the result of the evaluation by the first evaluation stage and the result of the evaluation by the second evaluation stage, the target equipment is renewed or peeled (total peeling inspection or peeling inspection) for each of one or more target equipments. Perform at least one of partial peeling inspection), condition monitoring, and post-maintenance. According to this, it is possible to narrow down the scope of the peeling inspection performed by peeling the heat insulating material for the coping equipment by the evaluation of the inspection necessity using the prediction model and the evaluation of the inspection necessity by the non-destructive inspection. As a result, this makes it possible to improve the prediction accuracy of the equipment of the plant where corrosion under the heat insulating material may occur, and to realize maintenance and inspection in which both safety and economy are compatible.

<Plant maintenance support system used to support plant maintenance and inspection>
Next, the plant maintenance support system used to support the maintenance and inspection of the above-mentioned plant equipment will be described.

FIG. 2 shows an example of the configuration of the plant maintenance support system 100 of the present embodiment. The plant maintenance support system 100 includes a plant maintenance support device 110, client terminals 151 to 153, a moisture measuring device 161 and a temperature measuring device 162.

The client terminals 151 to 153 may be installed in the facility of the plant for each plant. The client terminals 151 to 153 transmit data on the plant equipment to the plant maintenance support device 110 via a communication network such as the Internet 140, and data on the necessity of inspecting the plant equipment from the plant maintenance support device 110. Receive. The client terminals 151 to 153 may communicate with at least one of the moisture measuring device 161 and the temperature measuring device 162. The client terminals 151 to 153 may receive the measurement result of at least one of the measurements by the moisture measuring device 161 or the temperature measuring device 162.

The number of client terminals 151 to 153 may be one or two or more. At least one of the client terminals 151 to 153 may be at least one of the group consisting of a laptop terminal, a desktop terminal, a server, a client terminal, a smartphone, a tablet, and a wearable terminal.

In addition, any one of the plant maintenance support device 110 and the client terminals 151 to 153 may be integrally configured. That is, a series of processes from acquisition of data related to plant equipment, generation of data related to the necessity of inspection of plant equipment, and notification of the data may be performed by a single terminal. Further, the plant maintenance support device 110 may be composed of a plurality of terminals. That is, a plurality of terminals may cooperate with each other to perform a series of processes from acquisition of data related to plant equipment, generation of data related to inspection necessity of plant equipment, and output of the data.

The plant maintenance support device 110 includes a storage unit 120 and a calculation unit 130. The arithmetic unit 130 includes at least one hardware processor. The arithmetic unit 130 may be composed of, for example, a CPU, a ROM, and a RAM as hardware processors. The storage unit 120 may be, for example, an auxiliary storage device configured by a hard disk drive. The hardware configuration of the arithmetic unit 130 and the storage unit 120 in the present disclosure will be described later with reference to FIG.

The storage unit 120 includes a program storage unit 121, a measurement data storage unit 122, a probability information storage unit 123, and a determination information storage unit 124. The program storage unit 121 stores the program to be executed in the calculation unit 130. The measurement data storage unit 122 is among the data of the equipment of the plant which is the training data for generating the prediction model received from the client terminals 151 to 153 by the plant maintenance support device 110, or the data of the equipment of the plant to be inspected. Remember at least one. The probability information storage unit 123 stores a model generated by the model generation unit 132 that predicts the risk level of the CUI as a probability. Here, the risk level of CUI is an index for evaluating the necessity of inspection for whether or not CUI has occurred. The probability information storage unit 123 may store data regarding the inspection necessity of the equipment of the plant. The determination information storage unit 124 stores a determination model for extracting a non-destructive inspection method suitable for the target equipment based on predetermined conditions.

When the calculation unit 130 executes the program stored in the program storage unit 121 in the storage unit 120, the calculation unit 130 includes the acquisition unit 131, the model generation unit 132, the first evaluation unit 133, the determination unit 134, and the output unit. Functions as 135.

The acquisition unit 131 acquires the data of the equipment of the plant which is the learning data and the data of the equipment of the plant to be inspected. The equipment of the plant to be the training data or the equipment of the plant to be inspected may be covered with the heat insulating material and the exterior material covering the outside of the heat insulating material, and the corrosion state may not be confirmed from the appearance. The exterior material may be sheet metal or the like. The acquisition unit 131 sends the acquired learning data of the plant equipment data to the model generation unit 132 and the measurement data storage unit 122. Further, the acquisition unit 131 sends the data of the equipment of the plant to be inspected to the first evaluation unit 133.

The model generation unit 132 generates a model that predicts the risk level of the CUI as a probability from the data of the equipment of the plant, which is the data sent from the acquisition unit 131. The model generation unit 132 may generate a model by a machine learning method using the data of the plant equipment sent from the acquisition unit 131 as training data (training data). In the present disclosure, the model generation unit 132 may generate a model for predicting the CUI generation probability for each wall thinning depth, and calculate the probability density for each wall thinning depth based on the generated model. The model may be generated to output the probability density as a distribution based on the parameter μ. The model may also be generated to output the probability density as a probability density function based on the parameter μ. The model generation unit 132 sends the generated model to the first evaluation unit 133 via the probability information storage unit 123 or directly.

The first evaluation unit 133 evaluates the inspection necessity of the equipment of the plant to be inspected obtained by the acquisition unit 131 by using the model acquired from the probability information storage unit 123 or the model generation unit 132. Hereinafter, the evaluation by the first evaluation unit 133 may be expressed as a preliminary determination. The first evaluation unit 133 sends the first evaluation result (result of preliminary determination) to the determination unit 134. Here, as an example, the first evaluation result may be the rank of the degree of danger of the CUI represented by the rank A to the rank D. Here, the degree of danger of the CUI may be an index indicating the possibility that the equipment of the plant may be damaged by the CUI. The first evaluation unit 133 may transmit the first evaluation result to any of the client terminals 151 to 153. The client terminals 151 to 153 may notify the user by displaying the first evaluation result on the display unit or the like.

The determination unit 134 is suitable for the target equipment from among the non-destructive inspections performed by the equipment of the plant to be inspected using the predetermined measuring device without peeling of the heat insulating material based on the predetermined conditions. Extract the type of non-destructive inspection. Although some non-destructive inspection methods for inspecting the degree of corrosion under the heat insulating material are known, accurate inspection results cannot be obtained unless they are carried out under appropriate conditions. Therefore, it is important to select and implement a non-destructive inspection method suitable for the target equipment from a plurality of non-destructive inspection methods.

In the present disclosure, the determination unit 134 is qualifying whether the equipment of the plant to be inspected is suitable for measurement using at least one of the moisture measuring device 161 or the temperature measuring device 162. Make a judgment. As a result of the first evaluation result and the eligibility determination sent from the first evaluation unit 133, the determination unit 134 has a certain level of CUI risk in the equipment of the plant to be inspected, and the inspection target. If the equipment of the plant is suitable for measurement using a measuring device, the type of non-destructive inspection using a predetermined measuring device suitable for the target equipment is selected by the client via a communication network such as the Internet 140. Instruct at least one of terminals 151-153. In the present disclosure, the determination unit 134 communicates with the Internet 140 or the like so as to measure the equipment of the plant to be inspected by using at least one measuring device of the moisture measuring device 161 or the temperature measuring device 162. Instruct at least one of the client terminals 151 to 153 via the network. The determination unit 133 may transmit the eligibility determination result to the client terminal even when none of the measuring devices is suitable for measurement or when any of the measuring devices is suitable for measurement.

The determination unit 134 acquires the measurement result using at least one of the moisture measuring device 161 or the temperature measuring device 162 from the client terminals 151 to 153 via a communication network such as the Internet 140.

Further, as will be described later, the determination unit 134 is suitable for measuring the target equipment from the type of non-destructive inspection that does not involve peeling of the heat insulating material, based on the data of the equipment of the plant to be inspected acquired by the acquisition unit 131. The type may be extracted. Here, the types of non-destructive inspection include an inspection for measuring the surface temperature of the exterior material covering the surface of the heat insulating material of the target equipment (first inspection) and a measurement of the amount of water contained in the heat insulating material of the target equipment. An inspection (second inspection) may be included. It is preferable that the equipment data of the plant to be inspected includes the operating temperature condition as a condition for determining whether the target equipment is suitable for non-destructive inspection using a predetermined measuring device. Further, the conditions include the outside air temperature, the difference between the operating temperature and the outside air temperature, the type of the exterior material of the heat insulating material, the shape of the surface of the exterior material of the heat insulating material, and the object covered with the heat insulating material and the heat insulating material. It is more preferable that at least one of the conditions of the presence or absence of the heating equipment provided between the equipment and the equipment is included. The type of exterior material may include the type of surface processing of the exterior material.

The determination unit 134 sends the determination result to the output unit 135.

The output unit 135 may output the inspection necessity of the equipment of the plant to be inspected to at least one of the client terminals 151 to 153 via a communication network such as the Internet 140. The output unit 135 is qualified for non-destructive inspection by the determination unit 134, the data of the plant equipment acquired by the acquisition unit 131, the data of the equipment of the plant to be inspected, the evaluation result by the first evaluation unit 133, and the determination unit 134. The result of the sex determination, the result of the evaluation by the second evaluation unit 136, which will be described later, and the result of the evaluation by the third evaluation unit 137 may be output.

As described above, the plant maintenance support device 110 generates a model that predicts the risk level of CUI as a probability based on the acquired learning data of the plant equipment data, and uses the generated model to be inspected. Preliminarily determine the need for inspection of plant equipment. As a result of the first evaluation, the equipment of the plant to be inspected has a certain degree of risk of CUI, and the equipment of the plant to be inspected is a non-destructive inspection without peeling of the heat insulating material, and is a predetermined measuring device. When it is suitable for measurement using Instruct at least one of. The type of non-destructive inspection may include an inspection in which measurement is performed using at least one measuring device of the moisture measuring device 161 or the temperature measuring device 162. Therefore, when the plant maintenance support device 110 is suitable for inspection by at least one measuring device of the moisture measuring device 161 or the temperature measuring device 162 for the target equipment, the plant maintenance support device 110 may be a moisture measuring device 161 or a temperature measuring device 162. You may instruct at least one of the client terminals 151-153 to make measurements using at least one of these measuring devices. The determination unit 134 needs to inspect the equipment of the plant to be inspected based on the determination result of the eligibility of the non-destructive inspection of the moisture measuring device 161 and the like and the measurement result of the non-destructive inspection of the moisture measuring device 161 and the like. May be determined. Even if the determination unit 134 determines the necessity of inspecting the equipment of the plant to be inspected based only on the first evaluation result or only the measurement result by the measuring device without performing the preliminary determination. good.

The non-destructive inspection method may include a non-destructive inspection method in which the following measuring device is used. That is, as a measuring device, a thermo-hygrometer, an ACM sensor that detects a corrosion current flowing between two kinds of insulated metals (for example, iron and silver), and at least one of ultrasonic waves and magnetic flux leakage arranged in a pipe. An intelligent pig, which measures the wall thinning depth on the inner and outer surfaces of the pipe, can be used. Further, an acoustic emission measuring instrument that detects the degree of corrosion of a structure (for example, the progress state of corrosion) by detecting elastic waves emitted from the rust layer due to peeling or breaking of rust caused by corrosion can be used. .. The degree of corrosion of the structure (pipes, etc.) based on the radiographing results of the digital X-ray imaging device that X-rays the structure covered with the heat insulating material and the digital X-ray imaging device (for example, the maximum wall thinning depth within the imaging range). An image processing device that detects (s) can be used.

However, the thermo-hygrometer and ACM sensor require a partial peeling of the heat insulating material for their installation, which increases the installation cost, and also calculates calibration data for evaluating the degree of corrosion of the actual machine from the measurement results. , Acquisition of calibration data is complicated. In addition, the acoustic emission meter is complicated to calculate the obtained signal and the calibration data for evaluating the degree of corrosion, and to acquire the calibration data. Intelligent pigs are difficult to apply to in-plant piping with many curved pipes and branched parts, and applicable plant equipment is limited. In addition, the X-ray imaging device and the image processing device need to measure these devices in close proximity to the target pipe or the like. Further, the X-ray imaging apparatus and the image processing apparatus cannot be applied to a large-diameter pipe or equipment, and the application target thereof is limited. Therefore, as a non-destructive inspection method, it is preferable to use at least one of the moisture measuring device 161 and the temperature measuring device 162, which are methods in which the restriction of proximity measurement is relaxed to some extent. In addition, as will be described later, the inventors have realized the calculation of calibration data regarding the correlation between the accumulated measurement results and the degree of corrosion occurrence by performing non-destructive inspections using these measuring devices under predetermined conditions.

For the above reasons, the determination unit 134 extracts a plurality of non-destructive inspection types suitable for the target equipment, and at least one of the moisture measuring device 161 and the temperature measuring device 162 is included in the plurality of types. If it is included, it may be output together with the fact that at least one of the moisture measuring device 161 and the temperature measuring device 162 is recommended.

<Processing flow of plant maintenance support device 110>
FIG. 3 is an example of the processing flow of the plant maintenance support device 110. The plant maintenance support device 110 evaluates the inspection necessity of the equipment of the plant to be inspected by processing S210 to S290, and supports the determination of the countermeasure to be taken for the equipment of the plant to be inspected. By using the result of the arithmetic processing by the plant maintenance support device 110, it is possible to implement countermeasures such as inspection, equipment update, and condition monitoring suitable for the target equipment. For convenience of explanation, the processes of S210 to S290 will be described in order, but these processes may be executed in parallel like a pipeline.

Here, the plant means a factory facility including a reactor, a pipeline, a purification device, etc., in which raw materials are input and reacted, mixed, or separated to produce a target compound or composition. May be. Further, the equipment of the plant may include at least one of the metal pipes and the metal equipment used in the plant. At least one of the metal pipe and the metal equipment may be covered with a heat insulating material and an exterior material covering the outside of the heat insulating material. The equipment of the plant may be covered with a heat insulating material and an exterior material covering the outside of the heat insulating material, and the corrosion state may not be confirmed from the appearance.

First, in S210, the model generation unit 132 generates a prediction model that predicts the risk level of the CUI of the equipment based on the installation status of the equipment of the plant to be inspected. The prediction model may be a model that predicts the wall thinning depth of the target equipment as a probability. That is, the prediction model may be a model that predicts the possibility of damage caused by the CUI of the target equipment. In the present disclosure, the model generation unit 132 generates a model that predicts the risk level of the CUI as a probability based on the data of the equipment of the plant that is the learning data acquired from the acquisition unit 131. The model generation unit 132 sends the generated model to the first evaluation unit 133 via the probability information storage unit 123 or directly. Details of S210 will be described later. In the processing flow, S210, S220, S230 and S240 may be skipped and the process may proceed directly to S250 from the start.

Next, in S220, the acquisition unit 131 acquires the data of the equipment of the plant to be inspected and sends it to the first evaluation unit 133. The acquisition unit 131 may acquire data including the allowable wall thickness reduction depth, which is information on the wall thickness allowed for the equipment, as the data of the equipment of the plant to be inspected. The user of the plant maintenance support system 100 may input the allowable wall thinning depth into any of the terminals. According to this, since the threshold value for calculating the inspection necessity by the first evaluation unit 133 can be arbitrarily set according to, for example, the degree of influence of the result described later, it is possible to realize a highly accurate and economical inspection. can. It should be noted that a plurality of data on the equipment of the plant to be inspected may be acquired.

Next, in S230, the first evaluation unit 133 uses the acquired data of the equipment of the plant to be inspected as the probability of the CUI acquired from the probability information storage unit 123 or the model generation unit 132. Preliminarily determine the need for inspection of the equipment of the plant to be inspected using the predicted model. The first evaluation unit 133 may use the result of ranking the inspection necessity of the equipment of the plant as the first evaluation result. As an example, the first evaluation result may be classified into four ranks from A rank to D rank, in which A rank has the lowest possibility of CUI generation and D rank has the highest possibility of CUI generation. Details of S230 will be described later.

Next, in S240, when it is evaluated as a result of the first evaluation of S230 that the equipment of the plant to be inspected does not have a certain level of CUI risk (for example, A rank or B rank), plant maintenance is performed. The support device 110 advances the process to S290. As a result of the first evaluation of S230, when it is evaluated that the equipment of the plant to be inspected has a certain level of CUI risk (for example, C rank or D rank), the determination unit 134 processes S250. ..

Next, in S250, the determination unit 134 performs a non-destructive inspection using a predetermined measuring device for the equipment of the plant to be inspected, which is preliminarily determined to have a certain level of CUI risk in the equipment of the plant to be inspected. Judgment of eligibility as to whether or not it is suitable for. In the example of this processing flow, the determination unit 134 determines the eligibility for measurement using at least one of the moisture measuring device 161 and the temperature measuring device 162. The determination unit 134 may proceed to S260 if the result of the eligibility determination is suitable for the measurement using the equipment of the plant to be inspected. As a result of determining the eligibility, the determination unit 134 may proceed to S280 if the equipment of the plant to be inspected is not suitable for the measurement using the measuring device. The determination unit 134 may send the result of the eligibility determination to the probability information storage unit 123. Further, the determination unit 134 may send the result of the eligibility determination to the client terminals 151 to 153 via a communication network such as the output unit 135 and the Internet 140. Details of S250 will be described later. If it is determined in S240 that the equipment of the plant to be inspected has a certain degree of CUI risk in the processing flow, S250, S260 and S270 may be skipped and the process may proceed directly from S240 to S280.

Next, in S260, the determination unit 134 selects a measuring device suitable for measurement on the equipment of the plant to be inspected from the non-destructive inspection method using a predetermined measuring device based on the result of the eligibility determination. do. In the example of this processing flow, the determination unit 134 selects at least one of the moisture measuring device 161 and the temperature measuring device 162 as a measuring device suitable for measuring the equipment of the plant to be inspected. It should be noted that the options of the determination unit 134 (in the result of the rating determination, one of the measuring devices is suitable for measurement, none of the measuring devices is suitable for measurement, and / or any of the measuring devices is suitable for measurement. Appropriateness may be included. The determination unit 134 instructs the user of the client terminals 151 to 153 to perform the measurement by using the measuring device suitable for the measurement of the equipment of the plant to be inspected. In the example of the processing flow, the determination unit 134 uses the measuring device of the moisture measuring device 161 or the temperature measuring device 162, which is suitable for measuring the equipment of the plant to be inspected, to the user of the client terminals 151 to 153. Instructing the user to make a measurement. This instruction may recommend the user to make a measurement using any of the measuring devices. Hereinafter, the measurement of the plant equipment by the measuring device is referred to as the first inspection. I have something to express.

The measurement (first inspection) of the plant equipment by the measuring device is preferably a non-peeling inspection performed without peeling the exterior material or the heat insulating material. According to this, for example, the inspection can be performed without forming a scaffold for peeling off the exterior material or the heat insulating material. Further, the measurement (first inspection) of the plant equipment by the measuring device is preferably a non-contact inspection performed without contacting the exterior material or the heat insulating material. According to this, if it is within the measurement range of the measuring device, the measurement can be easily performed at a position away from the inspection object. As a result, highly accurate and economical inspection can be realized.

The determination unit 134 acquires a measurement result (first inspection result) from a predetermined measuring device. In an example of this processing flow, the determination unit 134 transfers the measurement result (first inspection result) from the moisture measuring device 161 and / or the temperature measuring device 162 via the communication network such as the client terminals 151 to 153 and the Internet 140. get. The determination unit 134 sends the measurement result to the second evaluation unit and / or the third evaluation unit. The second evaluation unit 136 and / or the third evaluation unit 137 evaluates the necessity of inspection of the equipment of the plant from the measurement results. Details of S260 will be described later. Hereinafter, the evaluation of the necessity of inspection of the equipment of the plant based on the measurement result may be simply expressed as an evaluation. Further, the evaluation result of the second evaluation unit 136 may be expressed as the second evaluation result, and the evaluation result by the third evaluation unit 137 may be expressed as the third evaluation result. Here, the evaluation of the necessity of inspection of the equipment of the plant based on the measurement result may be the evaluation of the necessity of the peeling inspection (second inspection) performed by peeling off the exterior material or the heat insulating material.

Next, in S270, when it is evaluated that peeling inspection of the equipment of the plant to be inspected is necessary as a result of the evaluation of S260, the plant maintenance support device 110 advances the processing to S280. If it is determined that the peeling inspection of the equipment of the plant to be inspected is unnecessary, the plant maintenance support device 110 advances the processing to S290.

Next, in S280, the output unit 135 outputs to instruct at least one of the client terminals 151 to 153 to perform a peeling inspection of the equipment of the plant to be inspected via a communication network such as the Internet 140. .. Here, the peeling inspection of the equipment of the plant to be inspected may be performed by peeling off the heat insulating material or the exterior material of the equipment of the plant. The output may be displayed on at least one display of the client terminals 151 to 153.

Next, in S290, the output unit 135 performs a peeling inspection on at least one of the client terminals 151 to 153 via a communication network such as the Internet 140 because the need for inspection of the equipment of the plant to be inspected is low. You may output that it is not necessary. The output may be displayed on at least one display of the client terminals 151 to 153.

In S250, if the equipment of the plant to be inspected is not suitable for the measurement using at least one of the moisture measuring device 161 or the temperature measuring device 162, the process proceeds to S280. If the equipment of the plant to be inspected is not suitable for measurement using at least one of the moisture measuring device 161 or the temperature measuring device 162, a non-destructive inspection using a measuring device different from these is performed. The recommendation may be output as a result of the eligibility determination. Non-destructive inspection methods that do not use the moisture measuring device 161 or the temperature measuring device 162 include, for example, an ACM sensor, an acoustic emission measuring device, an ultrasonic meter, and an X-ray measuring device. When any one of the non-destructive inspection methods using these measuring devices is carried out, the necessity of peeling inspection of the equipment of the plant is evaluated based on the inspection result of the non-destructive inspection (4th). (Evaluation), based on the evaluation result, a peeling inspection of the equipment of the plant may be carried out.

Further, in S250, if the equipment of the plant to be inspected is not suitable for the measurement using at least one of the moisture measuring device 161 or the temperature measuring device 162, the process proceeds to S280. If there is no non-destructive inspection method suitable for the equipment of the plant to be inspected, the site to be inspected for peeling should be narrowed down by, for example, visual inspection other than non-destructive inspection in advance of the peeling inspection of the plant. You may.

FIG. 4 is a diagram showing S210 in the processing flow of the plant maintenance support device 110 of the present embodiment. In S210, the plant maintenance support device 110 executes S211 and S212.

In S211 the acquisition unit 131 acquires the data of the plant equipment which is the data for generating the model from the client terminals 151 to 153 via the communication network such as the Internet 140. The plant equipment data, which is the data for generating the model, includes the installation status data. The installation status data may include at least one of the plant equipment type, installation location, installation period, operating temperature data, and wall thickness information. The installation status data preferably includes the type of equipment, the installation period, and the operating temperature. Further, it is preferable that the installation status data includes the parts of the equipment in which the types of equipment are subdivided. For example, when the type of equipment is "pipe", the equipment portion may include any one of "straight pipe portion", "curved pipe portion", and "near nozzle". Further, when the type of equipment is "tower", any one of "body", "strengthening wheel vicinity", and "nozzle vicinity" may be included. When the type of equipment is "tank", any one of "body", "near an accessory such as a ladder", and "near a nozzle" may be included. The type of equipment and the part of the equipment may include other than the above examples. In this way, the type of equipment and the part of the equipment are defined as a group defined by adding the part of the equipment to the type of equipment, which is a higher-level concept, and subdividing it into two stages (collectively referred to as "type of equipment". ). As a result, as will be described later, it is possible to provide a prediction model in which the influence on the prediction result is subdivided according to the type of the target equipment according to the type of the target equipment, and the prediction accuracy can be improved. Can be improved. The data of the equipment of the plant acquired by the acquired object 131 in S211 may include information on the attributes of the equipment of the plant and the wall thickness of the equipment of the plant. Here, the attribute of the equipment of the plant is some information indicating the characteristics of the equipment of the plant including the above-mentioned installation status, and is the degree of danger of CUI (for example, the probability of occurrence of CUI, the speed of progress, the depth of corrosion, etc.). ) Is preferably information that is a factor that fluctuates. The information on the wall thickness of the equipment of the plant preferably includes the initial wall thickness of the equipment of the plant, the measured value of the wall thinning depth and / or the numerical value correlating with the measured value of the wall thinning depth.

Information on the attributes of the equipment of the plant may include the type of equipment of the plant, the installation period of the equipment of the plant, the operating temperature of the equipment of the plant. Information on the type of equipment in the plant may include information specifying either piping, towers, tanks, nozzles, heat exchangers, or reactors. Information on the type of equipment in the plant may include information that specifies either piping with continuous operating temperatures or piping with discontinuous operating temperatures. The location of the plant equipment may include information specifying either the location of the straight pipe, the location of the curved pipe, the location of the nozzle, the perimeter of the support, the perimeter of the nozzle, or the perimeter of the flange. The installation period of the plant equipment may include information that specifies either the period after the installation of the plant equipment or the actual number of periods of use (years, months, days, etc.). The operating temperature of the equipment of the plant may include information specifying either the actual temperature of the material handled in the equipment or the set temperature set for the material handled in the equipment.

The wall thickness information may be information on the wall thickness reduction depth. The wall thickness information may be information on the initial wall thickness and the current wall thickness. The wall thickness information may include information on the thickness reduction rate, the required wall thickness, the controlled wall thickness, or the margin wall thickness, which is the ratio of the initial wall thickness to the current wall thickness. The required wall thickness is the wall thickness of the equipment required for safety and / or quality control, and is the wall thickness calculated by calculation and the wall thickness stipulated by law. In addition, the controlled wall thickness may be a wall thickness or the like specified in the in-house safety regulations. For example, the control wall thickness may be a wall thickness arbitrarily set by the maintenance entity that manages the structure of the plant. As the control wall thickness, the required wall thickness may be used, or a value larger than the required wall thickness may be set by adding a certain value to the required wall thickness, multiplying by a safety factor, or the like. The controlled wall thickness is, for example, the required wall thickness that causes ductile fracture, or the wall thickness specified by the plant manager on the safe side (thicker) than the required wall thickness in order to determine the propriety of repairing the structure. Thickness can be adopted.

In addition to the information listed above, plant equipment data includes annual average temperature, annual average precipitation, upper and lower temperature when there are fluctuations in operating temperature, distance from the coast, and from the cooling tower. It may include information such as distance, presence / absence of coating, material of heat insulating material, presence / absence of heat medium trace such as steam. The information listed above is an example, and the data of plant equipment is not limited to these.

As an example, the acquisition unit 131 may acquire a plurality of data sets as shown in [Piping, 100 months, 60 ° C., wall thinning depth 50 mm] as learning data for each facility of the plant.

The acquisition unit 131 sends the acquired learning data of the plant equipment data to the model generation unit 132 and the measurement data storage unit 122. As a result, a data group including the thickness reduction depth measured in advance is formed for a plurality of facilities having different installation conditions.

Next, in S212, the model generation unit 132 generates a model based on the data of the equipment of the plant which is the data for generating the model sent from the acquisition unit 131, and the risk level of the CUI is used as the probability. Generate a model to predict. The model can be generated by each method such as a statistical method, a machine learning method, or a combination of a plurality of methods selected from each of these methods. A model that predicts the risk of CUI as a probability may be generated by using the Gamlss package of the statistical processing language R. The model generation unit 132 may execute the step of generating a model by using a generalized additive model. The model generated by the model generation unit 132 may output the probability density with respect to the wall thinning depth. The model may output the probability density as a distribution based on the parameter μ, or may output the probability density as a probability density function based on the parameter μ. When the model is generated by the machine learning method, the model generation unit 132 may generate the model so as to minimize the error between the probability predicted by the model and the probability calculated from the training data, for example.

The model generated by the model generation unit 132 is represented by the following mathematical formula 1 as an example.
[Formula 1]
f (x; μ) = 1 / μ × exp (−x / μ)
Here, μ is a parameter of the distribution determined according to the installation status of the equipment of the plant, and x is the wall thinning depth. As shown in Equation 1, the model outputs the probability f (x; μ) corresponding to the parameter μ given the wall thinning depth x. By f (x; μ), it is possible to obtain the distribution of the probability density of the wall thinning depth of the plant equipment, which changes corresponding to the continuous wall thinning depth x.

Further, the parameter μ may be expressed by the following mathematical formula 2.
[Formula 2]
μ = exp (a0 + a1 x position + a2 x temperature + a3 x time + temperature (temperature))
Here, "position" is the part of the equipment in which the type of equipment is subdivided, "temperature" is the operating temperature of the equipment of the plant, and "time" is the installation period of the equipment of the plant. Further, "spline" is a predetermined cubic spline function. a0, a1, a2 and a3 may be coefficients optimized by learning. That is, a machine learning method may be used to optimize the coefficients.

a1 is a variable corresponding to each part of the equipment type in which the equipment type of the plant is subdivided.

Further, there may be a plurality of models at least depending on the type of equipment. For example, by providing a plurality of parameters μ according to the type of equipment, a plurality of models can exist. That is, by using a different model for each type of equipment as a factor that greatly changes the risk of CUI, highly accurate and economical inspection can be realized.

Further, the parameter μ may be determined based on at least one of the type of equipment of the plant, the site of the equipment subdivided thereof, the installation period, and the operating temperature. Further, the parameter μ may be determined by an exponential function including a coefficient calculated based on the type of equipment, the installation period, and the operating temperature.

In S212, the model generation unit 132 sends the generated model to the first evaluation unit 133 and the program storage unit 121.

FIG. 5 is a diagram illustrating the validity of the model that predicts the risk level of the learned CUI as a probability in S212. In a specific plant with a constant parameter μ, plotting the relationship between the detected value of the wall thinning depth of the plant equipment and the frequency of the plant equipment where the wall thinning depth actually occurred is plotted on a semi-logarithmic graph. , Was shown to be straight. Here, the straight line 400 in FIG. 5 is a regression line between the wall thinning depth and the frequency. That is, it is shown that the distribution of the wall thinning depth is an exponential distribution. Therefore, the exponential distribution showed the validity of modeling the distribution of wall thinning depth.

In the present disclosure, the model is constructed as a model that does not consider the degree of progress (time dependence) of the CUI. That is, the measurement data for generating the model does not include information on the time for which the wall thinning progresses, such as when the CUI occurred, in what period the wall thinning depth by the CUI progressed, and the like. To acquire measurement data including the progress of CUI, it is necessary to take measures such as performing a peeling inspection regularly and measuring a sensor to measure the wall thinning depth at the place where CUI is generated by the peeling inspection. Therefore, it becomes difficult to collect measurement data. On the other hand, according to the model of the present disclosure, the degree of danger of CUI is evaluated by a model that does not consider the degree of progress (time dependence) of CUI. Therefore, by collecting measurement data that can be collected relatively easily, the accuracy of the model can be continuously improved.

Further, in the present disclosure, the first evaluation using the model is performed without calculating the absolute value of the value corresponding to the wall thinning depth and / or the wall thinning depth. The location of CUI generation and the degree of progression vary greatly depending on the attributes of the plant equipment, such as the type of plant equipment. In the present disclosure, the model generation unit 132 is configured to generate a plurality of models according to the type of equipment of the plant. However, there are variations in the wall thinning depth depending on the attributes other than the type of plant equipment. Therefore, by calculating the risk of CUI, that is, the probability that the equipment can be damaged by CUI, instead of the absolute value of the wall thinning depth, appropriate maintenance support for the user is realized.

FIG. 6 is a diagram showing S230 in the processing flow of the plant maintenance support device 110 of the present embodiment. In S230, the plant maintenance support device 110 executes S231 to S233.

In S231, the first evaluation unit 133 uses the data of the equipment of the plant to be inspected acquired by the acquisition unit 131 in S220, and is the parameter of the model that predicts the risk level of the CUI generated by the model generation unit 132 as a probability. Calculate a few μ. The equipment data of the plant to be inspected may include the type of equipment, installation period, and operating temperature of the plant that need to be entered into the model. Next, the first evaluation unit 133 generates a probability density distribution f (x; μ) from the predicted model parameter μ.

Next, in S232, the first evaluation unit 133 uses the probability density distribution f (x; μ) and the wall thickness information of the equipment of the plant to be inspected to determine the thickness reduction depth of the equipment of the plant to be inspected. Calculate the probability of exceeding the permissible wall thinning depth. Here, the value of the allowable wall thickness reduction depth may be a value obtained by subtracting the required wall thickness from the initial wall thickness. As mentioned above, the required wall thickness is the wall thickness of the equipment required for safety and / or quality control, and is the wall thickness calculated by calculation, the wall thickness stipulated by law, or the internal safety regulations. It may be a predetermined wall thickness or the like, and one or a plurality of allowable wall reduction depth values may be set for the target equipment. Allowable reduction by setting multiple values of the allowable wall reduction depth for the target equipment in multiple stages, for example, and evaluating the possibility of damage caused by CUI for each allowable wall reduction depth. It is possible to grasp the degree of increase or decrease in the probability that damage may occur according to the set value of the wall depth, which contributes to the decision-making of countermeasures for equipment maintenance of the plant. Further, the possibility that the wall thinning depth exceeds the allowable wall thinning depth may be expressed by a probability. The wall thickness information of the equipment of the plant to be inspected may include information on the initial wall thickness and the required wall thickness.

Specifically, in the model generated in S231, the first evaluation unit 133 is based on the data of the equipment of the plant to be inspected, from "equipment type (No. 1)" to "equipment type (No. n)". , "Temperature", and "time" are substituted into equations 2 and 3 to calculate the parameter μ. The probability density distribution f (x; μ) is obtained from the calculated parameter μ. The probability that the wall thinning depth of the equipment of the plant to be inspected exceeds the permissible wall thinning depth is the interval in which the wall thinning depth x is xp <x <∞ when the permissible wall thinning depth is expressed by xp. It is expressed by integrating the probability density distribution f (x; μ) in.

Next, in S233, the first evaluation unit 133 outputs the evaluation result of the inspection necessity of the equipment of the plant to the determination unit 134. The first evaluation unit 133 may output the inspection necessity of the equipment of the plant to the determination unit 134 as a result of ranking. As an example, the first evaluation unit 133 may output the inspection necessity of the equipment of the plant to the determination unit 134 as a cumulative probability. The first evaluation unit 133 may provide the client terminals 151 to 153 with the necessity of inspecting the equipment of the plant as the first evaluation result, and may cause the client terminals 151 to 153 to display the first evaluation result.

As an example, the first evaluation unit 133 ranks A (low possibility of CUI) and 0.001 cumulative probability if the cumulative probability is less than 0.001 for the inspection necessity of the equipment of the plant to be inspected. If it is less than 0.01, it is ranked as B rank (in the possibility of CUI occurrence), and if the cumulative probability is 0.01 or more and less than 0.1, it is ranked as C rank (high possibility of CUI occurrence), and the cumulative probability is 0.1. If it is the above, it may be classified into D rank (maximum possibility of CUI occurrence), but it is not limited to this.

FIG. 7 is a diagram illustrating a mechanism for calculating the first evaluation result of the inspection necessity of the equipment of the plant to be inspected in S230. Here, the curve 600 represents the probability density distribution f (x; μ) generated based on the parameter μ of the model predicted by the first evaluation unit 133. Curve 600 may be a probability density function. In FIG. 7, the horizontal axis is the wall thinning depth, and the vertical axis is the probability density. The possibility that the wall thinning depth of the equipment of the plant to be inspected exceeds the allowable wall thinning depth is expressed by the area of the shaded area as a cumulative probability. The first evaluation unit 133 may calculate the cumulative probability 610 that the wall thinning depth of the equipment of the plant exceeds the allowable wall thinning depth. The first evaluation unit 133 classifies the cumulative probabilities into multiple categories according to a predetermined standard, and it is necessary to inspect the equipment of the plant for the possibility that the wall thinning depth of the plant equipment exceeds the allowable wall thinning depth. The sex may be expressed by the rank corresponding to each of the plurality of classifications, and this rank may be used as the first evaluation result.

Further, the first evaluation unit 133 evaluates the necessity of inspecting the equipment of the plant based on the degree of influence of the result when the equipment of the plant is damaged by the CUI in addition to the possibility of damage caused by the CUI. good.

FIG. 8 shows the plant equipment based on the possibility of damage caused by the CUI, the amount of damage that can occur if the plant equipment is damaged, the expected magnitude of human damage, and the degree of impact of the result. This is an example of the evaluation criteria when evaluating the necessity of inspection.

As shown in FIG. 8, the rank of the possibility of damage caused by CUI is divided into multiple stages, and the degree of impact of the result indicated by the amount of damage is divided into multiple stages. By the combination of, it is possible to evaluate the inspection necessity of the target equipment. At this time, the evaluation of the necessity of inspection may include the contents of possible countermeasures for the target equipment. As shown in FIG. 8, it is evaluated that the need for inspection is higher when the possibility of occurrence is higher than when the possibility of occurrence is low, and the necessity of inspection is evaluated when the degree of influence of the result is higher than when the degree of influence is low. .. Further, as a countermeasure according to the evaluation of the evaluation of the necessity of inspection, post-maintenance (no inspection) or condition monitoring, partial peeling inspection, and full peeling inspection may be set in ascending order of evaluation of inspection necessity.

FIG. 9 shows an example of a display mode of the first evaluation result obtained in S231 in the processing flow of the plant maintenance support device 110 of the present embodiment. As an example, the first evaluation unit 133 may display the results of classifying the calculated cumulative probabilities into four ranks from A rank to D rank according to a predetermined standard on the client terminals 151 to 153. The client terminals 151 to 153 may display the classification result in a table format as shown in FIG. Further, the classification result may include, but is not limited to, the address, the annual average temperature, the annual average precipitation, the factory name, the machine number, or the type of equipment, depending on the data used for the preliminary determination. In addition, as described above, when the inspection necessity is evaluated based on the possibility of damage and the degree of impact of the result, the possibility of damage is evaluated and the possibility of damage is evaluated. Instead of evaluation, an integrated index based on the likelihood of damage and the degree of impact of the result may be presented. The integrated indicator may be shown, for example, as the magnitude of risk as shown in FIG.

FIG. 10 shows an example of a display mode of the first evaluation result obtained in S231 in the processing flow of the plant maintenance support device 110 of the present embodiment. The display mode shown in FIG. 10 is an example of performing a peeling inspection of the equipment to be inspected based on the first evaluation result and displaying the result of measuring the wall thinning depth. As an example, the first evaluation unit 133 outputs the result of classifying the calculated cumulative probability into 4 ranks from A rank to D rank according to a predetermined standard in a graph format to the client terminals 151 to 153, and outputs this to the client terminals 151 to 153. It may be displayed on the client terminals 151 to 153. Further, in the classification result in the graph format, any one or two or more of the measured values of the wall thinning depth measured in the past and the measured values of the equipment of the plant to be inspected may be color-coded. ..

Here, as a result of ranking the client terminals 151 to 153, the first evaluation unit 133 has a list of plant equipment (for example, A rank and B rank) in which the possibility of occurrence of CUI is small and the possibility of occurrence of CUI. A list of large plant equipment (eg, rank C and rank D) may be provided for client terminals 151-153.

FIG. 11 is a diagram showing S250 in the processing flow of the plant maintenance support device 110 of the present embodiment. In S250, the plant maintenance support device 110 executes S2501 to S254. The determination unit 134 determines in S2501 to S254 whether the equipment of the plant to be inspected is suitable for measurement using a predetermined measuring device and evaluation of inspection necessity based on the measurement result. Judgment using a model. The determination model may determine eligibility based on the measurement conditions of the measuring device. Here, the measurement conditions of the measuring device are the operating temperature of the equipment of the plant to be inspected, the outside air temperature, the difference between the operating temperature and the outside air temperature, the type of surface processing of the exterior material of the heat insulating material, and the surface of the exterior material of the heat insulating material. And at least one of the conditions of the presence or absence of the heating equipment provided between the heat insulating material and the equipment of the plant covered with the heat insulating material may be further included. The determination model is a plurality of non-destructive inspections based on the threshold value set for the above conditions and the conditions when the target equipment is inspected, which is acquired by the acquisition unit 131 from the client terminal 151 via 153. It is configured to extract the non-destructive inspection method suitable for the target equipment from the method of. In an example of this processing flow, the determination unit 134 measures the water content inside the exterior material of the heat insulating material by the water content measuring device 161 according to the measurement conditions such as the operating temperature of the equipment of the plant to be inspected. And, it is configured to selectively recommend either measuring the surface temperature of the exterior material of the heat insulating material by the temperature measuring device 162.

The information on the measurement conditions may be acquired by the acquisition unit 131 when acquiring the data of the equipment of the plant to be inspected, or may be appropriately acquired by the determination unit 134 from the client terminals 151 to 153. For example, the determination unit 134 transmits a question regarding the operating temperature information to the client terminals 151 to 153 via a communication network such as the Internet 140, and the user of the client terminals 151 to 153 asks the client terminals 151 to 153 the question. An answer may be input and sent to the determination unit 134 via a communication network such as the Internet 140. The determination unit 134 may acquire information such as an operating temperature from a sensor and / or a camera or the like installed in the equipment of the plant to be inspected. Further, the determination unit 134 may acquire information on measurement conditions from a terminal constituting a management system that manages the operation of the plant.

First, in S2501, the determination unit 134 determines whether or not the operating temperature of the plant to be inspected is higher than the outside air temperature by a predetermined temperature (for example, 10 ° C.) or more. In the case of Yes, the determination unit 134 advances the process to S252, and in the case of No, the process proceeds to S251. It should be noted that it may be determined whether or not the temperature difference between the operating temperature of the plant and the outside air temperature is a predetermined temperature difference (for example, 10 ° C.) or more. If the heat insulating material that covers the equipment of the plant that is operating under the above conditions contains water, the water content causes the temperature of the plant equipment to be transmitted to the outer surface of the heat insulating material, and the heat insulating material and / or the exterior. It causes temperature unevenness on the outer surface of the material. When the heat insulating material contains a wide range of water, the water causes the temperature of the plant equipment to be transmitted to the outer surface of the heat insulating material, which is the surface temperature of the heat insulating material and / or the exterior material and the outside air. It can be observed as a difference from the temperature. As will be described later, the inclusion of water in the heat insulating material increases the risk of CUI. Therefore, the above condition is one of the conditions suitable for determining the suitability of the temperature measuring device.

In S251, the determination unit 134 determines whether the operating temperature of the plant to be inspected is within a predetermined temperature range (for example, higher than 15 ° C. and lower than 80 ° C.) or outside the range. When the operating temperature is out of the predetermined temperature range, the determination unit 134 may determine that the equipment of the plant to be inspected is not suitable for measurement using the measuring device, and may proceed to the process to S280. .. If the operating temperature of the plant to be inspected is within a predetermined temperature range, the determination unit 134 determines that the equipment of the plant to be inspected is suitable for measurement by the moisture measuring device 161 and proceeds to the process to S260. It's okay. Under the condition that the operating temperature is, for example, 15 ° C. or lower, dew condensation is likely to occur in the equipment of the plant, and the dew condensation may adversely affect the measurement result of the moisture measuring device 161. Further, under the condition that the operating temperature is, for example, 80 ° C. or higher, even if the heat insulating material contains water, the water often evaporates, and the presence of water may not be detected even by the water measuring device 161. Therefore, the above condition is one of the conditions suitable for determining the suitability of the moisture measuring device. Since both the generation of dew condensation and the evaporation of water affect the temperature measurement, the above condition may be used as one of the conditions for determining the suitability of the temperature measuring device.

As an example, in S252, the determination unit 134 determines whether the exterior material of the heat insulating material of the plant to be inspected is an infrared low-reflection material (for example, carbon steel or hot-dip galvanizing) or another material. do. If the exterior material is other than an infrared low-reflection material (for example, stainless steel or aluminum), the determination unit 134 determines that the equipment of the plant to be inspected is not suitable for measurement using a temperature measuring device, and performs processing. You may proceed to S251. If the exterior material of the heat insulating material of the plant to be inspected is an infrared low-reflection material, the determination unit 134 may proceed to the process to S253.

In S253, the determination unit 134 determines whether or not the exterior material of the heat insulating material of the plant to be inspected has a smooth surface. The judgment part has an abnormality on the surface of the exterior material, such as uneven coating of the exterior material (for example, a part of the coating is peeled off) or the surface of the exterior material is uneven. It is determined that the surface of the exterior material is not smooth, and if there is no such abnormality, it is determined that the surface of the exterior material is smooth. You can do it.

When the determination unit 134 determines that the exterior material of the heat insulating material of the plant to be inspected does not have a smooth surface, it determines that the equipment of the plant to be inspected is not suitable for measurement using the temperature measuring device, and processes it. May proceed to S251. When the surface condition of the exterior material of the heat insulating material of the plant to be inspected has a smooth surface, the determination unit 134 may proceed to the process to S254.

In S254, the determination unit 134 has cloudy weather on the date and time when the measurement using the measuring device is performed on the equipment of the plant to be inspected (currently if the measurement can be performed immediately) and the date and time when the measurement is performed. Is determined. When the date and time of measurement is nighttime or the weather is cloudy, the determination unit 134 determines that the equipment of the plant to be inspected is suitable for the measurement by the temperature measuring device 162, and proceeds to the process to S260. It's okay. The determination unit 134 may wait until night when the measurement is performed on the equipment of the plant to be inspected by using the measuring device. If the weather is other than cloudy (for example, sunny or rainy), the determination unit 134 may wait until night. You may wait until the weather becomes cloudy at the date and time of the event. The date and time of the measurement and the weather at that time fluctuate the temperature of the outer surface of the heat insulating material and / or the exterior material. For example, the surface temperature of the exterior material rises remarkably due to sunlight, and the surface temperature of the exterior material fluctuates remarkably due to rain. Therefore, the above condition is one of the conditions suitable for determining the suitability of the temperature measuring device.

As described with reference to FIG. 11, the determination unit 134 performs a non-destructive inspection based on predetermined conditions, in which the equipment of the plant to be inspected is carried out using a predetermined measuring device without peeling of the heat insulating material. From this, the type of non-destructive inspection suitable for the target equipment is extracted. In an example of this processing flow, the determination unit 134 determines whether or not the temperature measuring device 162 is suitable for measurement on the equipment of the plant to be inspected from among a plurality of non-destructive inspections based on predetermined conditions. Even if it is not suitable, it is determined whether or not the moisture measuring device 161 is suitable for measuring the equipment of the plant to be inspected. In this way, the determination unit 134 may determine that the measurement by the temperature measuring device 162 is preferentially performed.

FIG. 12 is a diagram showing S260 in the processing flow of the plant maintenance support device 110 of the present embodiment. In S260, the plant maintenance support device 110 executes S261 to S265.

In S261, the determination unit 134 selects a measuring device suitable for measurement on the equipment of the plant to be inspected based on the result of the determination of eligibility. As an example of this processing flow, the determination unit 134 selects at least one of the moisture measuring device 161 and the temperature measuring device 162. For example, in the flow of FIG. 11, when the moisture measuring device is selected, the determination unit 134 selects the moisture measuring device 161 and proceeds with the process to S262, and when the temperature measuring device is selected, the determination unit 134 The temperature measuring device 162 is selected and the process proceeds to S263.

Here, the moisture measuring device 161 may include a neutron moisture meter. The temperature measuring device 162 may include a thermo camera. The temperature measuring device 162 may include a temperature indicator paint or a contact thermometer. Both the neutron moisture meter and the thermo camera can measure at a position away from the equipment of the plant, and are therefore suitable as a measuring device for realizing non-peeling inspection and non-contact inspection. Also, when comparing the neutron moisture meter and the thermo camera, the thermo camera is generally smaller and cheaper to use, so when both the neutron moisture meter and the thermo camera are suitable for measurement. Can preferentially use a thermo camera.

In S262, the determination unit 134 uses the moisture measuring device 161 to measure at least one of the client terminals 151 to 153 via a communication network such as the Internet 140 so as to measure the equipment of the plant to be inspected. Instruct one. The instructions may be displayed on at least one display of the client terminals 151 to 153.

The user of the client terminals 151 to 153 measures the amount of water contained in the exterior material of the heat insulating material of the equipment of the plant to be inspected by the moisture measuring device 161. As a result of the determination in S251 of FIG. 11, when the operating temperature of the plant to be inspected is within a predetermined temperature range (for example, higher than 15 ° C and less than 80 ° C), the moisture measuring device 161 is an exterior material of the heat insulating material. The amount of water contained in the inside of the water will be measured. Under such temperature conditions, the moisture measuring device 161 may measure the amount of moisture contained in the exterior material of the heat insulating material under the condition that dew condensation does not occur on at least one of the heat insulating material and the exterior material. can. Further, as a result of the judgment in S252 and S253 of FIG. 11, the user can see that the surface of the exterior material of the plant equipment is uneven, or that the exterior material of the plant equipment is infrared rays such as stainless steel or aluminum. When it is composed of a reflective material, the moisture measuring device 161 is used to measure the amount of moisture contained inside the exterior material of the heat insulating material.

If a heating facility such as a trace is installed, the moisture that should be originally measured evaporates and cannot be measured. Therefore, it is desirable that no heating equipment is installed in the equipment of the plant to be inspected, which is the measurement target of the moisture measuring device 161. Similarly, if a heating facility such as a trace is installed, the generated moisture that fluctuates the temperature of the outer surface of the heat insulating material or the exterior material evaporates, resulting in uneven temperature or the heat insulating material and / or the exterior material. The difference between the surface temperature and the outside air temperature cannot be measured. Therefore, it is desirable that no heating equipment is installed in the equipment of the plant to be inspected to be measured by the temperature measuring device 162. The determination unit 134 acquires the measurement result of the water content measured by the water content measuring device 161 from the measurement result performed by the predetermined measuring device via the communication network such as the client terminals 151 to 153 and the Internet 140, and processes it. May proceed to S264.

In S263, the determination unit 134 uses the temperature measuring device 162 to measure at least one of the client terminals 151 to 153 via a communication network such as the Internet 140 so as to measure the equipment of the plant to be inspected. Instruct one. The instructions may be displayed on at least one display of the client terminals 151 to 153.

The user of the client terminals 151 to 153 measures the surface temperature of the exterior material of the heat insulating material of the equipment of the plant to be inspected by the temperature measuring device 162. The measurement of the surface temperature of the exterior material of the heat insulating material of the equipment of the plant to be inspected by the temperature measuring device 162 may include photographing the exterior material with a thermo camera. As a result of the judgments of S2501, S252, and S253 in FIG. 11, the operating temperature of the plant to be inspected is higher than the outside air temperature by a predetermined temperature (for example, 10 ° C.) or more, and the exterior material of the heat insulating material of the plant equipment is When the exterior material of the heat insulating material of the plant equipment is composed of the infrared low-reflection material and has a smooth surface, the measurement is performed by the temperature measuring device 162.

It should be noted that the user of the client terminals 151 to 153 may perform a step of discharging water to the exterior material of the heat insulating material of the plant equipment before measuring the surface temperature of the exterior material of the heat insulating material of the equipment of the plant to be inspected. good. As a result, it is possible to cause temperature unevenness, which will be described later, around the heat insulating material of the plant equipment. The determination unit 134 may acquire the measurement result of the surface temperature measured by the temperature measuring device 162 via a communication network such as the client terminals 151 to 153 and the Internet 140, and proceed to the process to S265.

In S264, the second evaluation unit 136 evaluates the necessity of inspecting the equipment of the plant to be inspected based on the measurement result of the water content from the moisture measuring device 161. The second evaluation unit 136 may determine that the larger the measured water content, the higher the need for inspection of the equipment of the plant. Here, when the water content is large, the water content may be absolutely large. A large amount of water may mean a relatively large amount of water. The high need for inspection of the equipment of the plant to be inspected may mean that the wall thinning depth of the equipment of the plant to be inspected is likely to be equal to or greater than the allowable wall thinning depth. ..

Here, the second evaluation unit 136 uses a pre-learned determination device based on the data in which the actually measured water content of the plant equipment and the generated wall thinning depth of the CUI are associated with each other. The need for equipment inspection may be determined. Such a determiner may be learned by a known machine learning technique. As will be described later, a correlation has been found between the need for inspection of plant equipment and the large amount of water in the plant equipment.

The second evaluation unit 136 ranks the data indicating the necessity of inspection of the equipment of the plant (for example, the probability that the CUI becomes the allowable wall thickness or more, or the probability) with respect to the client terminals 151 to 153. ) Is sent. The second evaluation unit 136 sends a message recommending the inspection of the equipment of such a plant to the client terminals 151 to 153 when the inspection necessity of the equipment of the plant exceeds a predetermined threshold value. It's okay. Here, the inspection of the equipment of the plant may be a peeling inspection (second inspection) performed by peeling off the exterior material or the heat insulating material.

In S265, the third evaluation unit 137 determines the necessity of inspection of the equipment of the plant to be inspected based on the measurement result of the surface temperature from the acquired temperature measuring device 162. The determination unit 134 determines that the larger the temperature unevenness of the surface temperature of the exterior material of the heat insulating material and the larger difference between the surface temperature and the outside air temperature, the higher the necessity of inspecting the equipment of the plant. good. The temperature unevenness of the surface temperature is the temperature difference between the average surface temperature of the exterior material of the heat insulating material of the equipment of the plant to be inspected and the maximum temperature and / or the minimum temperature, the temperature difference between the maximum temperature and the minimum temperature, or the surface. It may be the standard deviation of the temperature distribution or the like. Further, the difference between the surface temperature and the outside air temperature may be the difference between the average surface temperature of the exterior material of the heat insulating material of the equipment of the plant to be inspected and the outside air temperature.

The third evaluation unit 137 is based on data in which at least one of the actually measured temperature unevenness and the difference between the surface temperature and the outside air temperature and the generated wall thinning depth of the CUI are associated with each other in advance. The trained determiner may be used to determine the need for inspection of plant equipment. Such a determiner may be learned by a known machine learning technique. As will be described later, a correlation has been found between the necessity of inspecting the equipment of the plant and the large temperature unevenness of the surface temperature of the exterior material of the heat insulating material.

The third evaluation unit 137 ranks the data indicating the necessity of inspection of the equipment of the plant (for example, the probability that the CUI becomes the allowable wall thickness or more, or the probability) with respect to the client terminals 151 to 153. ) Is sent. When the inspection necessity of the equipment of the plant becomes equal to or more than a predetermined threshold value, the determination unit 134 measures the client terminals 151 to 153 for equipment maintenance measures including the inspection of the equipment of such a plant. You may send a message recommending. Here, the inspection of the equipment of the plant may be a peeling inspection (second inspection) performed by peeling off the exterior material or the heat insulating material, and as a countermeasure, in addition to the peeling inspection, post-maintenance and state monitoring. , Equipment updates, including repairs, may be included.

The evaluation of the inspection necessity based on the measurement result of the non-destructive inspection performed using the predetermined measuring device may be performed by correcting the result of the evaluation of the inspection necessity using the predictive model. That is, it may be performed by making a predetermined correction for the possibility of damage to the target equipment calculated by using the prediction model according to the measurement result. For example, the necessity of inspection can be evaluated by multiplying the cumulative probability of occurrence of damage to the target equipment calculated by the prediction model by a predetermined correction coefficient. That is, the larger the amount of water contained in the heat insulating material, the higher the possibility that corrosion under the heat insulating material has occurred and has progressed. Therefore, the value regarding the amount of water contained in the heat insulating material in the measurement result by the moisture measuring device 161 is The larger the value, the greater the possibility of damage, and the correction coefficient can be set. Further, the correction coefficient is set so that the possibility of damage increases as the degree of temperature unevenness is large in the measurement result by the temperature measuring device 162 and / or the temperature difference between the surface temperature and the outside air temperature is large. can do.

FIG. 13 is a diagram for verifying the prediction accuracy of the preliminary determination obtained in S232 in the processing flow of the plant maintenance support device 110 of the present embodiment. FIG. 13 is a model for predicting the risk level of the CUI of the present application as a probability for 987 points of data in which the equipment of the plant is inspected and the data on the type of the equipment of the plant and the wall thickness information are obtained. The results of ranking the inspection necessity of the plant equipment using the above, and the result of actually inspecting the plant equipment and totaling the numbers that were less than the required wall thickness of each rank are shown.

From FIG. 13, the ratio of the number of data having the required wall thickness or less to the number of data in which the inspection necessity of the plant equipment is classified into C rank is 0.046. Further, among the number of data classified into D rank, the ratio of the number of data having a required wall thickness or less is 0.15. Therefore, it was shown that the data classified into C rank and D rank are within the range of the set probability P, respectively. Further, regarding the data classified into A rank and B rank, the number of classified data is 207 points and 113 points, respectively. Therefore, it is a reasonable result that the number of data less than the required wall thickness is 0. I can say. Therefore, it was shown that the ranking of the inspection necessity of the equipment of the plant is properly performed by the model that predicts the risk degree of the CUI of the present application as a probability.

FIG. 14 is a diagram comparing the prediction accuracy of the preliminary determination obtained in S232 in the processing flow of the plant maintenance support device 110 of the present embodiment with the prediction accuracy of the preliminary determination obtained by using the conventional model. 14 shows the results of ranking the inspection necessity of plant equipment using a model that predicts the risk of CUI of the present application as a probability for the data of 987 points used in FIG. 13 in (A) and the conventional method. The results of ranking the inspection necessity of the plant equipment using the model are shown in (B), and the two are compared.

Here, as an index for evaluation, the actual margin wall thickness represented by the following mathematical formula 4 was used.
[Formula 4]
Actual margin wall thickness = initial wall thickness-required wall thickness-thinning depth In other words, if the actual margin wall thickness takes a negative value, corrosion has fallen below the required wall thickness, and the plant equipment is repaired or renewed. Indicates that

In FIG. 14 (A), in the case where the inspection necessity of the equipment of the plant is ranked by using the model that predicts the risk degree of the CUI of the present application as a probability, the ranks A to D are stairs with respect to the actual margin thickness. It is clear that they are lined up in a shape. Further, in the data classified into A rank, the data is distributed above the average value of the actual margin thickness of all the data. Furthermore, in the case of those classified as D rank, the data is concentrated below the average value of the actual margin thickness of all the data, and about half of the data has a negative actual margin thickness value, and the equipment of the plant Indicates that repair or renewal is required.

On the other hand, in FIG. 14 (B), in the case where the inspection necessity of the plant equipment is ranked using the conventional model, the A rank to the D rank are not arranged in a staircase pattern with respect to the actual margin wall thickness. Is clear. In addition, even if it is classified as A rank, there are many data that are less than the average value of the actual margin thickness of all data, and even if it is classified as D rank, data that is more than the average value of the actual margin thickness of all data is collected. It was shown to contain a lot. Furthermore, in the case where the inspection necessity of plant equipment is ranked using the conventional model, all the data (43 points) with the value of the wall thickness less than the required wall thickness are classified into D rank. The number of data points classified into D rank is 594 points, and the ratio of the number of data points equal to or less than the required wall thickness is 0.072. This is less than the D rank setting probability of 0.1. In other words, it became clear that the conventional model did not properly rank the inspection necessity of the plant equipment.

From the above results, it was clarified that the model that predicts the risk of CUI of the present application as a probability more appropriately evaluates the necessity of inspection of the equipment of the plant as compared with the conventional model.

FIG. 15 is a diagram comparing the prediction accuracy of the preliminary determination obtained in S232 in the processing flow of the plant maintenance support device 110 of the present embodiment with the prediction accuracy of the preliminary determination obtained by using the conventional model. A model that predicts the risk level of the CUI of the present application as a probability for 1020 points of data in which data on the type of plant equipment and wall thickness information is obtained by inspecting the plant equipment, and the conventional model. Was used to evaluate the need for inspection of plant equipment and represented in a matrix. From this matrix, each data can be classified into the following three groups.
(Group 1) The classified ranks of the application model and the conventional model are the same.
(Group 2) The rank of the conventional model evaluates the necessity of inspection of the equipment of the plant higher than the rank of the model of the present application.
(Group 3) The rank of the conventional model evaluates the necessity of inspection of the equipment of the plant lower than the rank of the model of the present application.

The number of data classified in (Group 1) is 320 points, and the ratio to all data is 31%. It is considered that the equipment of the plant classified in (Group 1) does not need to change the inspection range when the conventional model is changed to the model of the present application.

Next, the number of data classified into (Group 2) is 494 points, and the ratio to the total data is 48%. It is considered that the equipment of the plant classified in (Group 2) may be able to reduce the inspection range when the conventional model is changed to the model of the present application.

Next, the number of data classified into (Group 3) is 206 points, and the ratio to the total data is 20%. It is considered that the equipment of the plant classified in (Group 3) should have an additional inspection range when the conventional model is changed to the model of the present application.

Of the three groups, (Group 2), that is, the number of data in which the rank of the conventional model evaluates the necessity of inspection of the equipment of the plant higher than the rank of the model of the present application is 48% of the total. Compared to the conventional model, the model of the present application evaluates the inspection necessity of the equipment of the plant more accurately, so it is possible to reduce the inspection range for the equipment of the plant of 48% of the whole examples. It is considered to have sex.

Further, among the three groups, (Group 3), that is, the number of data in which the rank of the conventional model evaluates the necessity of inspection of the equipment of the plant lower than the rank of the model of the present application is 20% of the total. The equipment of these plants was classified as a rank with a high need for inspection in the model of the present application, although it had not been inspected so far because it was a rank with a low need for inspection in the conventional model. Therefore, it is considered better to add the inspection range for the equipment of the plant of 20% of the whole examples.

Therefore, for the plant equipment of the example of 28%, which is the difference between the two, it is considered that there is a possibility that the reliability of the inspection can be improved, the scope of the inspection can be reduced, and the inspection cost can be reduced.

FIG. 16 is a diagram verifying the result of the determination obtained in S264 in the processing flow of the plant maintenance support device 110 of the present embodiment. The applicants measured the water content inside the exterior material of the heat insulating material that covers the equipment of the plant to be inspected using a neutron moisture meter. It was found that the detection rate of was high.

Therefore, in the equipment where the operating temperature of the equipment of the plant to be inspected is 15 ° C to 80 ° C, a CUI having a wall thinning depth of a certain depth or more is detected for each water content measured by two neutron moisture meters. The probabilities are shown in FIG. (A) shows the result of measurement using the neutron moisture meter A, and (B) shows the result of the measurement using the neutron moisture meter B. In both (A) and (B), it was shown that the detection probability of CUI increased as the measured value of the water content measured by the neutron moisture meter increased. That is, there is a correlation between the water content and the CUI detection rate, and between the water content inside the exterior material of the heat insulating material measured by the neutron moisture meter and the water content on the pipe surface involved in the CUI. Was shown to be seen. Therefore, in plant equipment with an operating temperature of 15 ° C to 80 ° C, the amount of water inside the exterior material of the heat insulating material that covers the equipment of the plant to be inspected using a neutron moisture meter as a screening inspection for CUI inspection. It is considered that the measurement method of can be adopted.

FIG. 17A is a diagram verifying the result of the determination obtained in S265 in the processing flow of the plant maintenance support device 110 of the present embodiment. When the applicants measured the surface temperature of the exterior material of the heat insulating material that covers the equipment of the plant to be inspected using a thermo camera, the surface temperature of the place where the temperature abnormality was detected and the exterior material of the heat insulating material It was found that the larger the temperature difference (temperature unevenness) from the average surface temperature, the larger the data with a large wall thinning depth, and the more the CUI detection rate tends to increase.
FIG. 17B is a diagram verifying the result of the determination obtained in S265 in the processing flow of the plant maintenance support device 110 of the present embodiment. When the applicants measured the surface temperature of the exterior material of the heat insulating material that covers the equipment of the plant to be inspected using a thermo camera, the larger the difference between the surface temperature and the outside air temperature, the greater the wall thinning depth. We found that the data increased and the CUI detection rate also increased. In particular, the tendency was remarkable at the corrosion depth of about 0.1 mm to 0.5 mm at the initial stage of the progress of CUI.

FIGS. 17A and 17B show the results of ranking the probabilities of detecting a CUI having a wall thinning depth of a certain depth or more at a location where a temperature abnormality is detected according to the temperature difference from the average temperature section. As for the temperature rank of the measurement result using the thermo camera, the larger the temperature difference (temperature unevenness) between the surface temperature of the place where the temperature abnormality is detected and the average of the surface temperature of the exterior material of the heat insulating material, the more the surface. It was clarified that the larger the difference between the temperature and the outside air temperature, the higher the CUI detection probability of the data with deep wall thinning depth. Therefore, as a screening inspection for the CUI inspection, it is considered possible to adopt a method of measuring the surface temperature of the exterior material of the heat insulating material that covers the equipment of the plant to be inspected, using a thermo camera.

Further, the present invention provides a program for executing the above S210 to S290. The program may be stored in the program storage unit 121 of the plant maintenance support device 110. The plant maintenance support device 110 may be a computer that stores a program that executes the above S210 to S290.
Conservation support

FIG. 18 shows an example of the hardware configuration of the computer 1900 that functions as the plant maintenance support device 110. The computer 1900 according to the present embodiment is connected to the CPU peripheral portion having the CPU 2000, RAM 2020, graphic controller 2075, and display device 2080 connected to each other by the host controller 2082, and to the host controller 2082 by the input / output controller 2084. An input / output unit having a communication interface 2030, a hard disk drive 2040, and a CD-ROM drive 2060, and a legacy input / output unit having a ROM 2010, a flexible disk drive 2050, and an input / output chip 2070 connected to the input / output controller 2084. To prepare.

The host controller 2082 connects the RAM 2020 to the CPU 2000 and the graphic controller 2075 that access the RAM 2020 at a high transfer rate. The CPU 2000 operates based on the programs stored in the ROM 2010 and the RAM 2020, and controls each part. The graphic controller 2075 acquires image data generated on a frame buffer provided in the RAM 2020 by the CPU 2000 or the like, and displays the image data on the display device 2080. Alternatively, the graphic controller 2075 may include a frame buffer internally for storing image data generated by the CPU 2000 or the like. Various information (for example, measurement data, first, second, third evaluation results, etc.) generated inside the plant maintenance support device 110 can be displayed on the display device 2080.

The input / output controller 2084 connects the host controller 2082 to a communication interface 2030, a hard disk drive 2040, and a CDROM drive 2060, which are relatively high-speed input / output devices. The communication interface 2030 communicates with other devices via a network by wire or wirelessly. In addition, the communication interface functions as hardware for communication. The hard disk drive 2040 stores programs and data used by the CPU 2000 in the computer 1900. The CD-ROM drive 2060 reads a program or data from the CD-ROM 2095 and provides it to the hard disk drive 2040 via RAM 2020.

Further, the input / output controller 2084 is connected to the ROM 2010, the flexible disk drive 2050, and the relatively low-speed input / output device of the input / output chip 2070. The ROM 2010 stores a boot program executed by the computer 1900 at startup, and / or a program depending on the hardware of the computer 1900. The flexible disk drive 2050 reads a program or data from the flexible disk 2090 and provides it to the hard disk drive 2040 via RAM 2020. The input / output chip 2070 connects the flexible disk drive 2050 to the input / output controller 2084, and inputs / outputs various input / output devices via, for example, a parallel port, a serial port, a keyboard port, a mouse port, and the like. Connect to controller 2084.

The program provided to the hard disk drive 2040 via the RAM 2020 is stored in a recording medium such as a flexible disk 2090, a CD-ROM 2095, or an IC card and provided by the user. The program is read from the recording medium, installed on the hard disk drive 2040 in the computer 1900 via the RAM 2020, and executed in the CPU 2000.

The program installed in the computer 1900 and making the computer 1900 function as the plant maintenance support device 110 includes an acquisition module, a machine learning module, a preliminary determination module, a determination module, and an output module. These programs or modules may act on the CPU 2000 or the like to cause the computer 1900 to function as an acquisition unit 131, a model generation unit 132, a first evaluation unit 133, a determination unit 134, and an output unit 135, respectively.

The information processing described in these programs is read into the computer 1900, and the acquisition unit 131, the model generation unit 132, and the first unit are specific means in which the software and the various hardware resources described above cooperate with each other. It functions as an evaluation unit 133, a determination unit 134, and an output unit 135. Then, by realizing the calculation or processing of information according to the purpose of use of the computer 1900 in the present embodiment by these specific means, a unique plant maintenance support device 110 according to the purpose of use is constructed.

As an example, when communicating between the computer 1900 and an external device or the like, the CPU 2000 executes a communication program loaded on the RAM 2020, and a communication interface is based on the processing content described in the communication program. Instruct 2030 to process communication. Under the control of the CPU 2000, the communication interface 2030 reads out the transmission data stored in the transmission buffer area or the like provided on the storage device such as the RAM 2020, the hard disk drive 2040, the flexible disk 2090, or the CD-ROM 2095, and transfers the transmission data to the network. The received data transmitted or received from the network is written to a receive buffer area or the like provided on the storage device. As described above, the communication interface 2030 may transfer the transmission / reception data to / from the storage device by the DMA (direct memory access) method, and instead, the CPU 2000 may transfer the transfer source storage device or the communication interface 2030. The transmitted / received data may be transferred by reading data from the data and writing the data to the communication interface 2030 or the storage device of the transfer destination.

Further, the CPU 2000 is all or necessary from files or databases stored in an external storage device such as a hard disk drive 2040, a CD-ROM drive 2060 (CD-ROM 2095), and a flexible disk drive 2050 (flexible disk 2090). Parts are read into the RAM 2020 by DMA transfer or the like, and various processes are performed on the data on the RAM 2020. Then, the CPU 2000 writes the processed data back to the external storage device by DMA transfer or the like. In such processing, the RAM 2020 can be regarded as temporarily holding the contents of the external storage device. Therefore, in the present embodiment, the RAM 2020 and the external storage device are collectively referred to as a memory, a storage unit, a storage device, or the like.

Here, the storage device or the like stores information necessary for information processing of the plant maintenance support device 110, for example, measurement data and probability information as necessary, and stores the measurement data, probability information, and the like as necessary in each component of the plant maintenance support device 110 as needed. Supply.

Various information such as various programs, data, tables, and databases in the present embodiment are stored in such a storage device and are subject to information processing. The CPU 2000 can also hold a part of the RAM 2020 in the cache memory and read / write on the cache memory. Even in such a form, the cache memory plays a part of the function of the RAM 2020. Therefore, in the present embodiment, the cache memory is also included in the RAM 2020, the memory, and / or the storage device, unless otherwise indicated. do.

Further, the CPU 2000 includes various operations described in the present embodiment, information processing, condition determination, information retrieval / replacement, and the like, which are specified by the instruction sequence of the program for the data read from the RAM 2020. Is processed and written back to RAM 2020. For example, when the CPU 2000 determines a condition, whether or not the various variables shown in the present embodiment satisfy conditions such as large, small, above, below, and equal to other variables or constants. If the condition is satisfied (or not satisfied), it branches to a different instruction sequence or calls a subroutine.

Further, the CPU 2000 can search for information stored in a file in the storage device, a database, or the like. For example, when a plurality of entries in which the attribute value of the second attribute is associated with the attribute value of the first attribute are stored in the storage device, the CPU 2000 describes the plurality of entries stored in the storage device. By searching for an entry in which the attribute value of the first attribute matches the specified condition and reading the attribute value of the second attribute stored in that entry, it is associated with the first attribute that satisfies the predetermined condition. The attribute value of the second attribute obtained can be obtained.

The program or module shown above may be stored in an external recording medium. As the recording medium, in addition to the flexible disk 2090 and the CD-ROM 2095, an optical recording medium such as a DVD or a CD, a magneto-optical recording medium such as MO, a tape medium, a semiconductor memory such as an IC card, or the like can be used. Further, a storage device such as a hard disk or RAM provided in a dedicated communication network or a server system connected to the Internet may be used as a recording medium, and a program may be provided to the computer 1900 via the network.

In the present disclosure, the plant support device 110 has been shown to have a CPU 2000 as a processor, but the type of processor is not particularly limited. For example, GPU2000, ASIA, FPGA and the like can be appropriately used as the processor. Further, in the present disclosure, the plant support device 110 has a configuration in which the hard disk drive 2040 is provided as the auxiliary storage device, but the type of the auxiliary storage device is not particularly limited. For example, another storage device such as a slit state drive may be used instead of the hard disk drive 2040 or together with the hard disk drive 2030.

As described above, in the present disclosure, the first evaluation method for evaluating (estimating) the risk level of the CUI of the equipment to be inspected by using the model generated based on the measurement data of the equipment of the plant measured in advance. , A method of extracting a method suitable for the equipment of the plant to be inspected from multiple non-destructive inspection methods performed using a predetermined measuring device, and the result of measuring the equipment of the plant to be inspected by the predetermined measuring device ( The second evaluation and the third evaluation method for evaluating the risk level of the CUI of the equipment to be inspected based on the measurement result) are disclosed. Further, in the present disclosure, as the inspection of the CUI of the equipment to be inspected, the non-peeling inspection performed without peeling the heat insulating material and / or the exterior material covering the equipment and the peeling of the heat insulating material and / or the exterior material are performed. Disclosed the peeling inspection to be performed. Further, as a non-peeling inspection, an inspection by a moisture measuring device and an inspection by a temperature measuring device were disclosed. Further, in this disclosure, as a countermeasure for the equipment to be inspected, a method of selectively carrying out at least one of equipment renewal, full peeling inspection, partial peeling inspection, post-maintenance, and condition monitoring is disclosed.

From the above-mentioned estimation and first evaluation of CUI risk using a model, multiple non-destructive inspection methods performed using a predetermined measuring device, extraction of a method suitable for the equipment of the plant to be inspected, non-using a moisture measuring device. The peeling inspection and the second evaluation, the non-peeling inspection by the temperature measuring device and the third evaluation can be used individually or in combination as appropriate for the evaluation of the necessity of the peeling inspection.

For example, it is necessary to carry out at least two or more of the first evaluation, extraction of non-destructive inspection method, second evaluation, and third evaluation, and integrate the obtained multiple evaluation results to perform a peeling inspection. Can be evaluated.

Further, the plant maintenance support device 110 estimates the CUI risk level by a model, a non-peeling inspection by a moisture measuring device, and a non-peeling inspection by a temperature measuring device based on the attribute information of the equipment of the plant to be inspected. However, it may have a second determination unit for determining whether it is appropriate for evaluating the necessity of peeling inspection of the equipment to be inspected. The second determination unit may transmit the eligibility determination result to any of the client terminals 151 to 153.

In this disclosure, a method for evaluating the necessity of inspection of plant equipment using the risk level of CUI as an index is disclosed. However, as an index for evaluating the necessity of inspection of the equipment of the plant, an index other than the risk level of CUI may be used in combination. For example, the need for inspection of plant equipment can be evaluated based on the degree of impact of the consequences of damage to the plant equipment by the CUI. The degree of impact of the result can be defined by, for example, the amount of damage that can occur when the equipment of the plant is damaged, the magnitude of the assumed human damage, and the like.

Further, in the present disclosure, when the inspection necessity is evaluated for a plurality of target equipments and / or a plurality of allowable wall thinning depths for a predetermined equipment, the inspection necessity is relatively high. The output may emphasize the evaluation results for the equipment and / or the allowable wall thinning depth. For example, a relatively high evaluation result can be displayed at a higher level than other evaluation results, or a relatively high evaluation result can be displayed by coloring it differently from other evaluation results.

Although the present invention has been described above using the embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various changes or improvements can be made to the above embodiments. It is clear from the claims that embodiments with such modifications or improvements may also be included in the technical scope of the invention.

The execution order of each process such as the operation, procedure, step, and stage in the device, system, program, and method shown in the claims, the specification, and the drawing is particularly "before", "before", etc. It should be noted that it can be realized in any order unless the output of the previous process is used in the subsequent process. Even if the claims, the description, and the operation flow in the drawings are explained using "first", "next", etc. for convenience, it means that it is essential to carry out in this order. is not it.

Based on the above, some or all of the above embodiments may be described as in the following appendix, but are not limited to the following.

(Appendix 1)
Provided is a method of being mounted on one or more computers to support the maintenance of equipment that constitutes at least a part of a plant and is covered with a heat insulating material and whose corrosion state cannot be visually confirmed.
The method may comprise the step of preparing a predictive model. The predictive model may be generated using a set of data including pre-measured wall thinning depths for a plurality of facilities with different installation conditions. The prediction model may calculate the probability density f (x; μ) of the wall thinning depth x based on the parameter μ of the statistical distribution determined according to the installation situation.
The method may comprise the step of acquiring the installation status of one or more target equipment.
The method may comprise obtaining one or more permissible wall thinning depths for the subject equipment.
The method may include a step of evaluating the inspection necessity of the target equipment based on the allowable wall thinning depth and the probability density of the target equipment and the prediction model.
In the above method, the parameter μ may be determined at least based on the type of equipment, the installation period, and the operating temperature.
In the above method, the acquisition step may include at least acquiring the equipment type, installation period, and installation status of the target equipment including the operating temperature for the target equipment.
In the above method, the parameter μ may be determined by a function including a coefficient calculated based on the type of equipment, the installation period, and the operating temperature.
In the above method, the influence of the parameter μ, the installation period, and the operating temperature on the coefficient may vary depending on the type of the equipment.
In the above method, at the stage of evaluating the inspection necessity, the wall thinning depth of the target equipment is the allowable wall thinning depth based on the probability density f (x; μ) and the allowable wall thinning depth. The above or the step of calculating the cumulative probability of exceeding the above may be included.
In the above method, the type of equipment may include at least one of a pipe, a tank, and a tower.
In the above method, at the stage of evaluating the inspection necessity, it is necessary to inspect the possibility that the wall thinning depth of the target equipment is equal to or greater than the allowable wall thinning depth based on the probability density. It may further include a step of outputting as a result of ranking.
In the above method, at the stage of acquiring the allowable wall thinning depth, the data of the wall thinning depth acquired in advance for the same type of equipment as the target equipment is referred to, and the probability density f ( It may include a step of accepting an input of an arbitrary allowable wall thinning depth in a state where at least one of x; μ) can be presented.
In the above method, at the stage of acquiring the allowable wall thinning depth, a plurality of allowable wall thinning depths having different values may be acquired.
In the above method, the step of evaluating the inspection necessity is set to each of the plurality of allowable wall thinning depths when a plurality of the allowable wall thinning depths are acquired in the step of acquiring the allowable wall thinning depth. It may include assessing the need for testing.
In the above method, the probability density may be an exponential distribution. Further, in the above method, the parameter μ may be determined by an exponential function including a coefficient whose measured value is calculated based on the type of equipment, the installation period, and the operating temperature.

(Appendix 2)
A method is provided that constitutes at least a portion of the plant and is mounted on one or more computers to assist in the maintenance of equipment that is covered with insulation and whose corrosion status cannot be visually confirmed.
The method may include, for one or more target equipment, a stage of acquiring the equipment type, installation period, and installation status including operating temperature.
The method may comprise obtaining one or more permissible wall thinning depths for the subject equipment.
The method is at least a predictive model in which the type of equipment, the installation period, and the operating temperature are variables, and whether the thickness reduction depth of the equipment due to corrosion under the heat insulating material is equal to or more than a predetermined depth. A step may be prepared to prepare a predictive model for predicting.
The method may include the prediction model and a step of evaluating the inspection necessity of the target equipment based on the installation status of the target equipment and the allowable wall thinning depth.
In the above method, the prediction model may be a model that outputs the probability that the wall thinning depth of the equipment due to corrosion under the heat insulating material becomes equal to or more than a predetermined depth.
In the above method, the step of evaluating the inspection necessity is a step of acquiring the installation status of a plurality of the target equipments at the stage of acquiring the installation status, and / or a step of acquiring the allowable wall thickness reduction depth. When a plurality of allowable wall thinning depths are obtained in the above, it may be included to output so as to emphasize the evaluation result for the target equipment and / or the allowable wall thinning depth for which the inspection necessity is relatively high.
In the above method, the stage of evaluating the inspection necessity is the possibility of damage to the target equipment calculated based on the allowable wall thickness and the prediction model, and the degree of impact of the result when the equipment is damaged. May include assessing the need for testing based on.
The above method may be executed by a predetermined arithmetic unit having a processor and a memory. Further, the above method may be executed by a plurality of arithmetic units having a processor and a memory. Here, the plurality of arithmetic units may be realized by a predetermined system configured to enable wireless or wired communication. Furthermore, the above method may be realized by using a program executed by one or a plurality of arithmetic units.

(Appendix 3)
Provided is a method of preserving equipment that constitutes at least a part of the plant and is covered with heat insulating material and whose corrosion condition cannot be confirmed from the outside.
The method is based on the installation status of one or more target equipments and the allowable wall thickness reduction depth, and whether the wall thickness reduction depth of the target equipment is equal to or greater than the allowable wall reduction depth. A pre-evaluation step may be provided to evaluate the inspection necessity of the target equipment based on the prediction model to be predicted.
The method is a step of performing a peeling inspection accompanied by peeling of the heat insulating material or updating the target equipment for the target equipment whose inspection necessity evaluation result in the preliminary evaluation stage is of the first degree or higher. You may be prepared.
The method is for the target equipment in which the evaluation of the inspection necessity in the pre-evaluation stage is in a high predetermined range of less than the first degree and higher than the second degree smaller than the first degree. It may be provided with a step of performing a non-destructive inspection without peeling of the heat insulating material.
The method may further include a step of selecting a non-destructive inspection method suitable for the target equipment by using a determination model for determining based on the installation status of the target equipment before performing the non-destructive inspection. ..
In the above method, the determination model is based on the operating temperature of the target equipment, the outside air temperature, the difference between the operating temperature and the outside air temperature, the type of surface processing of the exterior material of the heat insulating material, and the surface of the exterior material of the heat insulating material. Non-destructive suitable for the target equipment based on at least one of the conditions of the above shape and the presence or absence of the heating equipment provided between the heat insulating material and the target equipment covered with the heat insulating material. It may be a model that selects and outputs the inspection method.
The above method applies to an evaluation stage in which the inspection necessity of the target equipment is evaluated based on the inspection result of the non-destructive inspection, and the target equipment in which the evaluation of the inspection necessity in the evaluation stage is of a third degree or higher. , The peeling inspection, or the step of updating the target equipment may be further included.
In the above method, the peeling is performed on the target equipment in which the evaluation of the inspection necessity in the evaluation stage is less than the third degree and is in the predetermined range of the fourth degree or more smaller than the third degree. It may further include a step of performing a partial peeling inspection having a smaller peeling ratio than when performing the inspection.
In the above method, condition monitoring and abnormalities due to corrosion under the heat insulating material occur in the target equipment for which the result of the evaluation of the necessity of inspection in the evaluation stage is within the predetermined range of less than the fourth degree. It may further include the step of performing at least one of the post-maintenance measures to deal with such cases.
In the above method, the evaluation of the inspection necessity in the pre-evaluation stage includes the possibility of damage to the target equipment calculated based on the prediction model, the installation status of the target equipment, and the allowable wall thickness reduction depth, and the above-mentioned possibility of damage to the target equipment. This may be done based on the degree of impact as a result of damage to the target equipment.
In the above method, the evaluation of the inspection necessity in the pre-evaluation stage includes the possibility of damage to the target equipment calculated based on the prediction model, the installation status of the target equipment, and the allowable wall thickness reduction depth, and the above-mentioned possibility of damage to the target equipment. This may be done based on the degree of impact as a result of damage to the target equipment. Further, in the above method, the evaluation of the inspection necessity in the evaluation stage is the result of the possibility of damage to the target equipment calculated based on the inspection result of the non-destructive inspection and the result when the target equipment is damaged. It may be done based on the degree of influence.
In the above method, the evaluation of the inspection necessity in the evaluation stage may include correcting the evaluation of the possibility of damage calculated in the pre-evaluation stage based on the inspection result of the non-destructive inspection.
In the above method, the evaluation stage is the evaluation of the inspection necessity based on the inspection result of the non-destructive inspection, and the inspection necessity based on the measurement result of the second evaluation unit 136 and / or the third evaluation unit 137. May include an evaluation of.

(Appendix 4)
Provided is a method of preserving equipment that constitutes at least a part of the plant and is covered with heat insulating material and whose corrosion condition cannot be confirmed from the outside.
The method is based on a prediction model that predicts the wall thinning depth of the equipment based on the installation status of the equipment, and the installation status and allowable wall thinning depth of a plurality of target equipments, and it is necessary to inspect a plurality of the target equipments. May include a pre-evaluation step to evaluate.
The method may include performing a non-destructive inspection of at least one of the plurality of target equipment without peeling of the heat insulating material.
The method may include an evaluation step of evaluating the inspection necessity of the target equipment based on the inspection result of the non-destructive inspection.
The method renews the target equipment for each of the plurality of target equipments based on the result of the evaluation of the inspection necessity in the pre-evaluation stage and the result of the evaluation of the inspection necessity in the evaluation stage. , Peeling inspection, partial peeling inspection, condition monitoring, and at least one of post-maintenance measures to deal with abnormalities due to corrosion under the heat insulating material may be selectively performed.
The above method may further include a step of selecting a non-destructive inspection method suitable for the target equipment by using a determination model for determining based on the installation status of the target equipment before performing the non-destructive inspection. ..
In the above method, the determination model is based on the operating temperature of the target equipment, the outside air temperature, the difference between the operating temperature and the outside air temperature, the type of surface processing of the exterior material of the heat insulating material, and the surface of the exterior material of the heat insulating material. Non-destructive suitable for the target equipment based on at least one of the conditions of the above shape and the presence or absence of the heating equipment provided between the heat insulating material and the target equipment covered with the heat insulating material. It may be a model that extracts the inspection method.
In the above method, for the target equipment whose inspection necessity evaluation result in the pre-evaluation stage is of the first degree or higher, a peeling inspection accompanied by peeling of the heat insulating material or updating of the target equipment is performed. The heat insulating material is used for the target equipment in which the evaluation of the inspection necessity in the pre-evaluation stage is less than the first degree and is higher than the second degree less than the first degree. A non-destructive inspection without peeling may be performed.
In the above method, the peeling inspection or the renewal of the target equipment may be performed on the target equipment whose inspection necessity is evaluated to the third degree or higher in the evaluation stage.
In the above method, the peeling is performed on the target equipment whose evaluation of inspection necessity in the evaluation stage is less than the third degree and within a predetermined range of the fourth degree or more smaller than the third degree. A partial peeling inspection with a smaller peeling rate than when the inspection is carried out may be performed.
In the above method, at least one of condition monitoring and post-maintenance may be performed on the target equipment in which the result of the evaluation of inspection necessity in the evaluation stage is within the predetermined range of less than the fourth degree.
In the above method, the evaluation of the inspection necessity in the pre-evaluation stage includes the possibility of damage to the target equipment calculated based on the prediction model, the installation status of the target equipment, and the allowable wall thickness reduction depth, and the above-mentioned possibility of damage to the target equipment. This may be done based on the degree of impact as a result of damage to the target equipment. Further, in the above method, the evaluation of the necessity of inspection in the first evaluation stage includes the possibility of damage to the target equipment calculated based on the inspection result of the nondestructive inspection and the case where the target equipment is damaged. It may be done based on the degree of influence of the result of.
In the above method, the evaluation of the inspection necessity in the first evaluation stage may include correcting the evaluation of the possibility of damage calculated in the pre-evaluation stage based on the inspection result of the non-destructive inspection. ..
In the above method, the prediction model may be a model that predicts the probability that the wall thinning depth of the target equipment is equal to or greater than the allowable wall thinning depth.
The method may include the step of acquiring the installation status of the target equipment and the allowable wall thinning depth.
The method is a stage of evaluating the inspection necessity of the target equipment based on the acquired installation status, the allowable wall thickness reduction depth, and a prediction model for predicting the wall thickness reduction depth of the equipment based on the installation status. May include.
The method is suitable for the target equipment from the types of countermeasures including a peeling inspection with peeling of the heat insulating material and a non-destructive inspection without peeling of the heat insulating material based on the evaluation result of inspection necessity. It may include the step of extracting one or more countermeasures.
The method may include the step of outputting at least one of the above types when one or more types are extracted.
In the above method, the types of countermeasures further include renewal of the target equipment, condition monitoring, and post-maintenance to deal with an abnormality caused by corrosion under the heat insulating material (CUI) in the target equipment. good.
In the above method, the stage of evaluating the inspection necessity includes the allowable wall thinning depth, the installation status, the possibility of damage to the target equipment calculated based on the prediction model, and the target equipment. It may include assessing the need for inspection based on the degree of impact of the consequences in the event of breakage.
In the above method, at the stage of evaluating the inspection necessity, it is evaluated that the degree of inspection necessity is higher when the possibility of damage is higher than when the possibility of damage is low, and the degree of influence of the result is lower than when the degree of influence is low. If it is high, it may be at the stage where the degree of necessity of inspection is evaluated to be high.
In the above method, when the degree of necessity of inspection is evaluated to be higher than the first degree in the evaluation result, the peeling inspection may be extracted as a type of countermeasure.
In the above method, the peeling inspection included in the type of the countermeasure is the first peeling inspection for peeling the first ratio or more of the heat insulating material of the target equipment and the second peeling inspection for peeling less than the first ratio. And may be included.
In the above method, when the non-destructive inspection is extracted at the stage of extracting the type of the countermeasure, the first inspection for measuring the surface temperature of the exterior material covering the surface of the heat insulating material of the target equipment and the target equipment. The second inspection for measuring the amount of water contained in the heat insulating material and the non-destructive inspection method including the second inspection may be extracted together.
In the above method, the installation status of the target equipment may include information regarding the operating temperature of the equipment. In the above method, when the non-destructive inspection is output at the stage of extracting the type of the countermeasure, the type of the non-destructive inspection method to be extracted may be changed according to the operating temperature.
In the above method, the prediction model is at least a prediction model in which the type of equipment, the installation period, and the operating temperature are variables, and the thickness reduction depth of the equipment due to corrosion under the heat insulating material is at least a predetermined depth. Alternatively, it may be a predictive model that outputs the probability of becoming super.
The above method may be executed by a predetermined arithmetic unit having a processor and a memory. The above method may also be performed by a plurality of arithmetic units having a processor and memory. The plurality of arithmetic units may be realized by a predetermined system configured to enable wireless or wired communication. Furthermore, the above method may be realized by using a program executed by one or a plurality of arithmetic units.

(Appendix 6)
Provided is a method for preserving equipment that constitutes at least a part of a plant and is covered with a heat insulating material and whose corrosion state cannot be confirmed from the outside.
The method may include the step of acquiring the installation status of the target equipment and the allowable wall thinning depth.
The method is to evaluate the inspection necessity of the target equipment by using the acquired installation condition, the allowable wall thinning depth, and a prediction model that predicts the wall thinning depth of the equipment based on the installation condition. May include.
The method is suitable for the target equipment from the types of countermeasures including a peeling inspection with peeling of the heat insulating material and a non-destructive inspection without peeling of the heat insulating material based on the evaluation result of inspection necessity. It may include the step of setting one or more countermeasures.
In the above method, the types of countermeasures further include renewal of the target equipment, condition monitoring, and post-maintenance to deal with an abnormality caused by corrosion under the heat insulating material (CUI) in the target equipment. good.
In the above method, the stage of evaluating the inspection necessity includes the allowable wall thinning depth, the installation status, the possibility of damage to the target equipment calculated based on the prediction model, and the target equipment. It may include assessing the need for inspection based on the degree of impact of the consequences in the event of breakage.
In the above method, at the stage of evaluating the inspection necessity, it is evaluated that the degree of inspection necessity is higher when the possibility of damage is higher than when the possibility of damage is low, and the degree of influence of the result is lower than when the degree of influence is low. It may be included to evaluate that the degree of need for inspection is higher when the value is high.
In the above method, when the degree of necessity of inspection is evaluated to be higher than the first degree in the evaluation result, the peeling inspection may be executed as a type of countermeasure.
In the above method, the peeling inspection included in the type of the countermeasure is the first peeling inspection for peeling the first ratio or more of the heat insulating material of the target equipment and the second peeling inspection for peeling less than the first ratio. And may be included.
In the above method, when a non-destructive inspection is output at the stage of setting the type of the countermeasure, the first inspection for measuring the surface temperature of the exterior material covering the surface of the heat insulating material of the target equipment and the target equipment. The second inspection for measuring the amount of water contained in the heat insulating material and the non-destructive inspection method including the second inspection may be set together.
In the above method, the installation status of the target equipment may include information regarding the operating temperature of the equipment. In the above method, when the non-destructive inspection is output at the stage of outputting the type of the countermeasure, the type of the non-destructive inspection method to be output may be changed according to the operating temperature.

(Appendix 7)
A computer-mounted method is provided to maintain equipment that constitutes at least a portion of a plant and is capable of under-insulation corrosion (CUI).
The method includes the steps of acquiring the installation status and the allowable wall thinning depth for each of the plurality of target equipments.
The method determines the need for inspection of each of the plurality of target equipments based on the acquired installation status and allowable wall thickness reduction, and a prediction model that predicts the thickness reduction depth of the equipment based on the installation status. Including the stage of evaluation.
The method includes a step of outputting to emphasize the equipment having a relatively high inspection need among the plurality of target equipments.

(Appendix 8)
A method is provided that constitutes at least a portion of the plant and is implemented in a computer to assist in the maintenance of equipment that is covered with insulation and whose corrosion status cannot be visually confirmed.
The method includes the stage of acquiring the installation status of the target equipment.
The method is to determine the type of non-destructive inspection suitable for the target equipment based on the installation status, and to predict the wall thinning depth of the equipment based on the installation status. Includes the step of performing at least one of the assessment of the need for inspection.
The method comprises outputting at least one of a suitable non-destructive inspection type and the evaluation result of the inspection necessity.
In the above method, the necessity of inspection of the target equipment is evaluated by determining the type of non-destructive inspection suitable for the target equipment and using a prediction model that predicts the wall thinning depth of the equipment based on the installation status. That may be done in this order. In the above method, the evaluation of the inspection necessity of the target equipment may be performed on the target equipment without suitable non-destructive inspection.

100 Plant maintenance support system 110 Plant maintenance support device 120 Storage unit 121 Program storage unit 122 Measurement data storage unit 123 Probability information storage unit 130 Calculation unit 131 Acquisition unit 132 Model generation unit 133 First evaluation unit 134 Judgment unit 135 Output unit 136 Second Judgment Unit 137 Third Judgment Unit 140 Internet 151 Client Terminal 152 Client Terminal 153 Client Terminal 161 Moisture Measuring Device 162 Temperature Measuring Device 400 Regression Straight Line between Thinning Depth and Frequency 600 Probability Density Function 610 Cumulative Probability 1900 Computer 2000 CPU
2010 ROM
2020 RAM
2030 Communication interface 2040 Hard disk drive 2050 Flexible disk drive 2060 CD-ROM drive 2070 Input / output chip 2075 Graphic controller 2080 Display device 2082 Host controller 2084 Input / output controller 2090 Flexible disk 2095 CD-ROM

Claims (20)

It is a method implemented in a computer to maintain at least a part of the plant, which is covered with a heat insulating material and whose corrosion state cannot be confirmed from the outside.
The stage of acquiring the conditions including the operating temperature of the target equipment and determining whether the target equipment is suitable for non-destructive inspection using a predetermined measuring device.
Based on the above conditions, a first inspection for measuring the surface temperature of the exterior material covering the surface of the heat insulating material of the target equipment, a second inspection for measuring the amount of water contained in the heat insulating material of the target equipment, and a second inspection. The stage of extracting a method suitable for the measurement of the target equipment from a plurality of non-destructive inspection methods that do not involve peeling of the heat insulating material including
When,
When one or more types of non-destructive inspection are extracted, the stage to output the type and
How to include. The conditions further include the outside air temperature, the difference between the operating temperature and the outside air temperature, the type of the exterior material of the heat insulating material, the shape of the surface of the exterior material of the heat insulating material, and the heat insulating material and the heat insulating material. The method according to claim 1, further comprising at least one of the conditions of the presence or absence of a heating facility provided between the covered facility and the target facility. The method according to claim 2, wherein the extraction step selects the first inspection when the condition that the operating temperature of the target equipment is 10 degrees or more higher than the outside air temperature is satisfied. The method according to claim 2 or 3, wherein the extraction step selects the first inspection when the exterior material of the heat insulating material satisfies the condition composed of the infrared low-reflection material. The method according to any one of claims 2 to 4, wherein the extraction step selects the first inspection when the exterior material of the heat insulating material satisfies the condition of having a smooth surface. The extraction step selects a type of non-destructive inspection different from the second inspection when the condition that dew condensation occurs on at least one of the heat insulating material and the exterior material is satisfied, claims 1 to 4. The method described in any one of the above. The output step is from claim 1, wherein when both the first inspection and the second inspection are extracted based on the conditions, the first inspection is recommended. The method according to any one of 6. The prediction model is further provided with a prediction stage for preliminarily predicting the inspection necessity of the target equipment by the prediction model generated based on the plurality of detection values of the wall thinning depth acquired in advance for the plurality of the equipment. The method according to any one of claims 1 to 7, wherein the extraction step is executed for the target equipment for which an inspection necessity of a predetermined degree or more is recognized in the step. An arithmetic unit having a processor and memory and performing the method according to any one of claims 1 to 8.
The device. Equipped with multiple arithmetic units with processor and memory
The plurality of arithmetic units are configured to be capable of wireless or wired communication, and are configured to perform the method according to any one of claims 1 to 8.
system. A program for causing one or more arithmetic units having a processor and a memory to execute the method according to any one of claims 1 to 8. It is a method for preserving equipment that constitutes at least a part of the plant and is covered with heat insulating material and whose corrosion state cannot be confirmed from the outside.
The stage of acquiring the conditions including the operating temperature of the target equipment and determining whether the target equipment is suitable for non-destructive inspection using a predetermined measuring device.
Based on the above conditions, a first inspection for measuring the surface temperature of the exterior material covering the surface of the heat insulating material of the target equipment, a second inspection for measuring the amount of water contained in the heat insulating material of the target equipment, and a second inspection. At the stage of selecting at least one of the methods suitable for the measurement of the target equipment from a plurality of non-destructive inspection methods that do not involve peeling of the heat insulating material including.
At the stage of performing the selected non-destructive inspection on the target equipment,
How to include. The conditions further include the outside air temperature, the difference between the operating temperature and the outside air temperature, the type of surface processing of the exterior material of the heat insulating material, the shape of the surface of the exterior material of the heat insulating material, and the heat insulating material and the above. The method according to claim 12, further comprising at least one of the conditions of the presence or absence of a heating facility provided between the target facility and the target facility coated with a heat insulating material. The method according to claim 12 or 13, wherein the first inspection is performed when the condition that the operating temperature of the target equipment is 10 degrees or more higher than the outside air temperature is satisfied. The method according to any one of claims 12 to 14, wherein the first inspection is performed when the exterior material of the heat insulating material satisfies the condition composed of the infrared low-reflection material. The method according to any one of claims 12 to 15, wherein the first inspection is performed when the exterior material of the heat insulating material satisfies the condition of having a smooth surface. The method according to any one of claims 12 to 16, wherein the second inspection is performed when the condition that dew condensation does not occur on at least one of the heat insulating material and the exterior material is satisfied. The method according to any one of claims 12 to 17, wherein when both the first inspection and the second inspection can be selected based on the above conditions, the first inspection is preferentially performed. The method according to any one of claims 12 to 18, wherein the first inspection is performed using a thermo camera and the second inspection is performed using a neutron moisture meter. Further provided with a prediction step for preliminarily predicting the inspection necessity of the target equipment by using a prediction model generated based on a plurality of detection values of the wall thinning depth acquired in advance for the plurality of the equipment. The method according to any one of claims 12 to 19, wherein the selected step is executed for the target equipment for which an inspection necessity of a predetermined degree or more is recognized in the prediction step.

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