JP2010277241A - Apparatus and method for processing information and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To accurately perform reliability prediction of equipment with a small number of sensors. <P>SOLUTION: An information processing apparatus 100 sets the equipment 11 equipped with a large number of components and the small number of sensors 12 as a target of the reliability prediction, and a reference value information storage part 105 stores reference value information. The reference value information is information indicating sensor measurement values of the sensors 12 assumed in standard operation environment and values assumed when measuring the respective components by the sensors in the standard environment as reference values. A sensor measurement value input part 101 inputs the sensor measurement values actually measured by the sensors 12, a comparison part 103 compares each sensor measurement value and a reference value of each sensor of the reference value information, an estimation part 104 calculates an estimation value in each component based on a comparison result and a reference value of each component, and a reliability prediction part 106 performs the reliability prediction by use of the estimation value of each component. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to an apparatus that performs information processing on sensor measurement values of a sensor installed on a management target, and performs information processing on sensor measurement values of a sensor installed on a management target device in a monitoring / control system, for example. Relates to the device.

Various monitoring and control systems require long-term equipment operation.
In the monitoring / control system, reliability of a management target device is predicted using sensor information, and a maintenance cycle (replacement time) of the management target device is obtained (for example, Patent Document 1).
In addition, a technique for predicting the reliability of a management target device and its component parts using a reliability prediction model is also disclosed (for example, Non-Patent Document 1).
Here, the reliability prediction is to predict the life or maintenance cycle (replacement time) of the management target device.

JP 2005-182465 A

Nakamura Taizo and Sakakibara Satoshi, "Reliable Method to Learn Easy", Nikka Giren Shuppan Shuppansha, December 24, 2004, p. 68-83

In order to accurately calculate the maintenance cycle of equipment (replacement and repair accompanying product life), it is necessary to know in detail the environmental conditions (temperature, humidity, applied voltage, energization time, etc.) of the environment in which the equipment is installed. There is a need to arrange a large number of sensors in the device.
On the other hand, since the arrangement of a large number of sensors leads to an increase in equipment cost, measurement is actually performed with one to several sensors, and environmental information is not accurately grasped in a part where no sensors are arranged. There is a problem that an error occurs in the predicted value of the maintenance cycle (equipment life).

  The main object of the present invention is to solve the above-mentioned problems, and to realize accurate maintenance cycle (equipment life) prediction with a small number of sensors.

An information processing apparatus according to the present invention includes:
A reference value information storage unit that stores a reference value for a predetermined parameter of a sensor installed in the management object and a reference value information indicating a reference value for the parameter for each component of the management object;
A sensor measurement value input unit for inputting a sensor measurement value actually measured for the parameter by the sensor;
The component of the management object using the sensor measurement value input by the sensor measurement value input unit, the reference value of the sensor indicated in the reference value information, and the reference value for each component of the management object And an estimated value calculating unit for calculating an estimated value for each parameter.

  According to the present invention, since the estimated value in the component where the sensor is not arranged is calculated based on the sensor measurement value and the reference value, accurate maintenance cycle prediction can be performed with a small number of sensors.

FIG. 3 shows a configuration example according to the first embodiment. FIG. 3 shows a configuration example according to the first embodiment. FIG. 6 illustrates an operation example of the information processing apparatus according to Embodiment 1; FIG. 3 is a flowchart for explaining an operation example of the information processing apparatus according to the first embodiment. FIG. 9 illustrates an operation example of an information processing device according to Embodiment 2; FIG. 6 is a flowchart for explaining an operation example of the information processing apparatus according to the second embodiment. FIG. 10 is a diagram for explaining a selection procedure of reference value information according to the second embodiment. FIG. 10 illustrates a configuration example according to Embodiment 3; FIG. 6 shows a configuration example according to Embodiment 4;

Embodiment 1 FIG.
In the present embodiment and the second and subsequent embodiments, the installation environment information of the part where the sensor is not arranged is supplemented by using the device design data (simulation result or the like), so that an accurate maintenance cycle (with a small number of sensors) An example of realizing (device life) prediction will be described.

  FIG. 1 illustrates a configuration example according to the present embodiment.

In FIG. 1, a device 11 is an example of a management target, and is a device that is a target of reliability prediction (lifetime prediction).
Parts 1 to N are components of the device 11.
The sensor 12 measures installation environment information of the device 11. The sensor 12 has various parameters such as temperature, humidity, atmospheric pressure, applied voltage, current, and energization time as measurement targets. One sensor may measure the values of two or more parameters, or a plurality of sensors 12 may be arranged for each parameter.

The information processing apparatus 100 performs reliability prediction (lifetime prediction) of the device 11.
The sensor measurement value input unit 101 inputs sensor measurement values actually measured by the sensor 12.
The estimated value calculation unit 102 calculates the sensor measurement value input by the sensor measurement value input unit 101, the sensor reference value indicated in reference value information described later, and the reference value for each component (each component) of the device 11. The estimated value is calculated for each part (each component) of the device 11.
The estimated value calculation unit 102 includes a comparison unit 103 and an estimation unit 104. The comparison unit 103 performs a comparison process between the sensor measurement value and the sensor reference value, and the estimation unit 104 performs a process of estimating the environmental value under the current operating condition based on the comparison result of the comparison unit 103 and the reference value of each component. I do.
The reference value information storage unit 105 stores reference value information. As shown in FIG. 3, the reference value information is information indicating a reference value of the sensor 12 for a predetermined parameter and a reference value for each component of the device 11 for the parameter. The reference value is a value assumed when the position of the sensor and the position of each component are measured by the sensor in a standard operating environment. In the example of FIG. 3, when the parameter to be measured by the sensor 12 is temperature, in a standard operating environment, the position of the sensor 12 is 25 degrees, the position of the part 1 is 40 degrees, the position of the part 2 is 35 degrees, It is assumed that a measurement value of 30 degrees is obtained at the position of the part 3 and 20 degrees at the position of the part N. Each reference value is a value obtained at the stage of development of the device 11 by, for example, simulation (thermal simulation, vibration simulation, etc.) or actual measurement (measurement of part surface temperature by a thermocouple, etc.).
The reliability prediction unit 106 performs reliability prediction of the device 11 using the sensor measurement value and the estimated value for each component calculated by the estimated value calculation unit 102.

As a hardware configuration of the information processing apparatus 100, for example, a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), a magnetic disk device, a communication board, and the like are connected by a bus.
In this case, a program that realizes a function described as “to part” (except for the reference value information storage unit 105 in the information processing apparatus 100) is stored in, for example, a magnetic disk device, and the CPU reads these programs as appropriate. Each function is executed.

The RAM temporarily stores at least part of an operating system program and application programs to be executed by the CPU.
The RAM stores various data necessary for processing by the CPU.

The ROM stores a BIOS (Basic Input Output System) program, and the magnetic disk device stores a boot program.
When the information processing apparatus 100 is activated, the BIOS program and the boot program for the magnetic disk device are executed, and the operating system is activated by the BIOS program and the boot program.

  In addition, what is described as “to part” may be “to circuit” and “to device”, and may also be “to step”, “to procedure”, and “to processing”. . That is, what is described as “˜unit” may be realized by firmware. Alternatively, it may be implemented only by software, or only by hardware such as elements, devices, substrates, and wirings, by a combination of software and hardware, or by a combination of firmware.

1 shows an example in which the device 11 that is the target of reliability prediction and the information processing apparatus 100 that performs reliability prediction are different devices (different hardware), but as shown in FIG. The target device for degree prediction and the execution device for reliability prediction may be the same device.
In FIG. 2, a reliability evaluation unit 200 is provided as an example of the information processing apparatus in the device 11, and the reliability evaluation unit 200 predicts the reliability of the device 11. The internal configuration of the reliability evaluation unit 200 is the same as that of the information processing apparatus 100 shown in FIG. The operation of the reliability evaluation unit 200 is the same as the operation of the information processing apparatus 100 described later.
The configuration shown in FIG. 2 will be described in more detail in the third and fourth embodiments.

Next, the operation will be described with reference to FIGS.
In the following, description will be made along the configuration of FIG. 1 in which the device 11 and the information processing apparatus 100 are separated, but the same operation is performed even in the configuration of FIG.

First, the sensor 12 measures the installation environment data of the device 11 and acquires the sensor measurement value 13.
When the sensor 12 is a temperature sensor and the number of installation is one, only the temperature value near the sensor 12 is acquired as the installation environment data of the device 11.
At this time, the temperature value of the component close to the sensor 12 (for example, the component 2 in FIG. 3) is close to the sensor measurement value 13, but the temperature of the component far from the sensor 12 (for example, the component N in FIG. 3). The value may be significantly different from the sensor measurement 13.
Therefore, the estimated value 17 is derived from the sensor measurement value 13 and the reference value of the reference value information 14, and the installation environment data (temperature in this example) of the components 1 to N is accurately grasped.

In the information processing apparatus 100, the sensor measurement value input unit 101 inputs the sensor measurement value 13 from the sensor 12 (S 401) (sensor measurement value input step), and passes the input sensor measurement value 13 to the comparison unit 103.
Next, the comparison unit 103 reads the reference value information 14 from the reference value information storage unit 105 (S402) (reference value information reading step).

Next, the comparison unit 103 compares the sensor measurement value 13 with the sensor reference value in the reference value information 14, and derives the difference between the sensor reference value and the sensor measurement value 13 (S403) (estimated value calculation step). .
Specifically, the difference is derived by the following formula 1.
Output α of comparison unit 103 = sensor measurement value 13−reference value of sensor (Expression 1)

Next, the estimation unit 104 derives the estimated value 17 of each component from the reference value of each component based on the derivation result of Equation 1 (S404) (estimated value calculating step).
In the present embodiment, the measurement target is temperature, and for example, the estimated value 17 can be derived for each part by the following equation.
Estimated value of part n = reference value of part n + α (Expression 2)
However, n = 1, 2, 3... N.

  Note that the method of deriving the estimated value is not limited to the above Equations 1 and 2, and other methods may be used.

The estimated value 17 (environment estimated value for each component) obtained in this manner is used as an input to the reliability predicting unit 106, and the reliability predicting unit 106 uses the estimated value 17 of each component so that the device 11 actually Accurately derive the reliability of each component in the environment in which it is used.
Note that the reliability prediction method of the reliability prediction unit 106 may be a generally known reliability prediction method (for example, the method described in Non-Patent Document 1).

As described above, in the environmental information complementing method according to the present embodiment, the environmental value of the part where the sensor is not installed is estimated, and the reliability in the actual use environment is grasped for each component part. Therefore, detailed reliability prediction (lifetime prediction) can be made on a component basis.
In addition, since the installation environment value of the entire device can be grasped with a small number of sensors and the number of sensors installed can be minimized, the device cost can be kept low.
In addition, when there are multiple parts with specific usage environment conditions (for example, the upper limit temperature of use is different from others) and each of the environmental conditions is exceeded, some kind of abnormal processing (power off, abnormality notification, etc.) is required. Since the environmental conditions of a plurality of parts can be grasped with one sensor, the same effect as that provided with a plurality of sensors on all target parts can be obtained.

  As described above, in the present embodiment, in a system that predicts reliability based on a reliability prediction model or the like from equipment installation environment data measured by a sensor, sensors are arranged using a small number of sensor data and equipment design data. We explained the monitoring and control equipment that can predict the reliability of equipment with high accuracy by complementing the environmental information of the parts that are not.

Embodiment 2. FIG.
In the first embodiment described above, the environmental value of the entire device is estimated with a small number of sensors. However, when the reference value varies depending on the usage method of the user, an appropriate reference value with a small number of sensors. The embodiment which selects and estimates an environmental value is shown.

FIG. 5 is an explanatory diagram showing an embodiment of a reference value selection and environment value complementation method in such a case.
In FIG. 5, sensors 21 to 24 are sensors that measure the installation environment information of the device.
A measurement value 130 indicates a measurement result of the sensors 21 to 24.
The reference value information 25 indicates the reference value of each component assuming a plurality of user usage methods assumed in the device design. There are a plurality of types of reference value information 25.

Further, the information processing apparatus 100 according to the present embodiment includes a comparison / selection unit 107 instead of the comparison unit 103 described in the first embodiment.
The comparison / selection unit 107 compares the measurement value 130 with the reference value of the reference value information 25 and selects the optimum reference value.
In the present embodiment, the estimation unit 104 estimates the environmental value under the current operating condition based on the output of the comparison / selection unit 107 and the reference value information 25.
More specifically, the comparison / selection unit 107 includes, for each of the reference value information 25, a plurality of reference value information 25, a reference value of the plurality of sensors indicated by the reference value information 25, and a sensor measurement value input unit. The degree of approximation of a plurality of sensors input by 101 with a plurality of sensor measurement values is analyzed, and specific reference value information is selected from a plurality of types of reference value information 25 based on the analysis result.
Further, the comparison / selection unit 107 compares the plurality of sensor measurement values input by the sensor measurement value input unit 101 with the sensor reference values indicated in the selected reference value information 25.
Then, the estimation unit 104 calculates an estimated value for each component using the comparison result of the comparison / selection unit 107 and the reference value for each component indicated in the reference value information 25 selected by the comparison / selection unit 107. .
The information processing apparatus 100 according to the present embodiment is as illustrated in FIG. 1 except that the comparison unit 103 is replaced with a comparison / selection unit 107.
Further, in the configuration in which the reliability evaluation unit 200 is provided as an example of the information processing apparatus in the device 11 as illustrated in FIG. 2, except that the comparison unit 103 is replaced with the comparison / selection unit 107. As shown in FIG.

Next, the operation of the information processing apparatus 100 according to the present embodiment will be described with reference to FIGS.
When a device has a plurality of functions, there is a possibility that the environmental stress applied to the components inside the device varies from user to user depending on how the user uses the device. For example, in the case of a device equipped with both display processing and communication processing, the display function component user A uses the display processing component frequently and the communication function center user B uses the communication processing component use frequency. As a result, for example, in the case of temperature, the temperature of the display processing component is high for user A, and the temperature of the communication processing component is high for user B. Become.
Assuming such a difference in user device usage, the reference value information 25 has a plurality of reference value information (1 to m) assuming different usage methods.
The comparison / selection unit 107 compares the sensor measurement value 130 with the reference value of the sensor in the reference value information 25, and the one having the sensor value pattern closest to the measurement value pattern of the sensor measurement value 130 is 1 to 1 of the reference value information 25. Select from m. In this way, a reference value that matches the user's device usage method is selected from the measurement value pattern of the measurement value 130.

In the information processing apparatus 100, the sensor measurement value input unit 101 inputs the sensor measurement values 130 from the plurality of sensors 21 to 24 (S 601) (sensor measurement value input step), and compares the input plurality of sensor measurement values 130. It passes to the selection unit 107.
Next, the comparison / selection unit 107 reads multiple types of reference value information 25 from the reference value information storage unit 105 (S602) (reference value information reading step).

Next, the comparison / selection unit 107 selects reference value information closest to the operating condition (S603) (estimated value calculation step).
An example of a specific selection method will be described with reference to FIG.

FIG. 7 is an explanatory diagram showing specific processing of the comparison / selection unit 107.
The comparison / selection unit 107 generates the measurement value graph 31 and the reference value graph 32.
The measurement value graph 31 shows a pattern of a plurality of sensor measurement values 130, and the reference value graph 32 shows a reference value pattern for the sensors 21 to 24 for each reference value information 25.
Next, the comparison / selection unit 107 performs cross-correlation between each graph (1 to m) of the measurement value graph 31 and the reference value graph 32 (S701).
Next, the comparison / selection unit 107 compares the similarity between the measured value graph 31 and each graph (1 to m) of the reference value graph 32 from the correlation value obtained in S701.
Next, the comparison / selection unit 107 selects one of the reference value graphs 32 having the highest correlation value (closest to the measurement value graph 31) from 1 to m based on the comparison result of S702.

Thereafter, the same processing as in the first embodiment is performed using the selected reference value information 25.
That is, the comparison / selection unit 107 compares the sensor measurement value 130 with the sensor reference value in the selected reference value information 25, and derives the difference between the sensor reference value and the sensor measurement value 130 (S604) (estimation). Value calculation step).
Specifically, the difference is derived by the following formula 3.
Output β of comparison / selection unit 107
= {Total value of sensor measurement values 130−total value of sensor reference values} ÷ number of sensors (Equation 3)
In Equation 3, the total value of the sensor measurement values 130 is the total of the sensor measurement values of the sensors 21 to 24, and the total value of the sensor reference values is the sensors 21 to 21 indicated in the selected reference value information 25. This is the total of 24 reference values. That is, in Equation 3, the average value of the differences between the sensor reference value and the sensor measurement value 130 is derived for a plurality of sensors.

Next, the estimation unit 104 derives the estimated value 17 of each component from the reference value of each component based on the derivation result of Expression 3 (S605) (estimated value calculating step).
For example, as in the first embodiment, the estimated value 17 can be derived for each part by the following equation.
Estimated value of part n = reference value of part n + β (Expression 4)
However, n = 1, 2, 3... N.

  Note that the method for deriving the estimated value is not limited to Equation 3 and Equation 4 above, and other methods may be used.

  As described above, the environmental information complementing method according to the present embodiment has a plurality of reference values (1 to m) that are assumed to be different in the user's device usage method, and is the standard closest to the user's usage mode from the sensor information. By selecting the value, it is possible to estimate the environmental value and to predict the reliability (life prediction) with high accuracy according to the actual use environment and conditions.

  As described above, the present embodiment has a plurality of design data assuming different usage methods, compares the sensor measurement data with the installation environment conditions of each design data, and obtains the design data closest to the actual use conditions from the comparison result. The device reliability prediction method for selecting the device reliability with high accuracy by selecting and complementing the environmental information of the part where the sensor is not arranged using the design data has been described.

  In addition, by calculating the cross-correlation between the sensor measurement data and the installation environment conditions of the design data held by the equipment, and comparing the actual use conditions with the similarity of the environment conditions of each design data, The design data selection method to select the nearest design data was explained.

Embodiment 3 FIG.
FIG. 8 shows the reliability prediction process and the environmental information complementing method shown in the first and second embodiments as built-in functions, and the device itself makes its own reliability prediction (life prediction) from the information of the built-in sensor. It is a block diagram of the apparatus to perform.
That is, in the present embodiment, a configuration in which the reliability evaluation unit 200 is arranged in the device 11 illustrated in FIG. 2 will be described.

In FIG. 8, a device 11 is a target device for life prediction.
The sub component 42 is a sub device that constitutes the device 11.
The reliability evaluation unit 200 is a part that performs reliability prediction (lifetime prediction) in the subcomponent 42. The reliability evaluation unit 200 is an example of an information processing apparatus.
The CPU 44 is a processor that controls the processing of the subcomponent 42.
The sensor 45 measures installation environment data of the subcomponent 42.
The sensor input unit 46 is an input circuit that receives an input from the sensor 45.
The ROM 47 is a non-volatile memory that stores device design data (reference value information in the first and second embodiments) for deriving an estimated value.
The maintenance request notification unit 48 is a circuit that notifies the life notification (replacement request) of the subcomponent 42.
The notification lamp 49 is a lamp that is turned on in response to a request from the maintenance request notification unit 48.
The maintenance request output unit 4A is a signal output circuit that notifies a maintenance request to an external device in response to a request from the maintenance request notification unit 48. The maintenance request notification unit 48 and the maintenance request output unit 4A are examples of a notification output unit.
The RAM 4B is a volatile memory serving as a work memory for the CPU 44 to operate.
The ROM 4C is a non-volatile memory that stores programs and data for the CPU 44.
I / O 4D and 4E are interface circuits for the subcomponent 42 to communicate with an external device.
The main bus 4F is a bus for the CPU 44 to access the memory and I / O.
The sensor measurement value input unit 101, the comparison unit 103, the estimation unit 104, and the reliability prediction unit 106 shown in FIG. 2 are computer programs, for example, stored in the ROM 4C, loaded into the RAM 4B at the time of execution, and the CPU 44. It is executed by.

Next, the operation will be described.
The CPU 44 predicts the reliability of the subcomponent 42 from the measured value obtained from the sensor input unit 46 and the reference value information stored in the ROM 47 by the method described in the first embodiment or the second embodiment. (Life calculation) is performed.
As a result, if the CPU 44 (reliability predicting unit 106) determines that maintenance (repair, replacement, etc.) of the subcomponent 42 itself is necessary, a maintenance request (lighting of the notification lamp 49, maintenance request output) is sent from the maintenance request notification unit 48. Signal output of the unit 4A).
In this way, the subcomponent 42 performs its own reliability prediction process and notifies only the necessity of maintenance to the outside, so that it is not necessary to transfer the sensor measurement data itself to the inside of the device 11 or outside the device. All communication resources between devices can be used for processing inherent to the device.
Further, since a maintenance request is output in units of subcomponents, there is an advantage that maintenance personnel can easily determine the replacement target.
Furthermore, since it is possible to predict the life with high accuracy in units of sub-components, it is possible to use each component to the limit of the usable period, and there is an advantage that maintenance costs can be reduced.

  In the configuration shown in the first embodiment, the information processing apparatus 100 is provided with the maintenance request notification unit 48, the notification lamp 49, and the life notification signal output unit 4A, and the information processing apparatus 100 needs to maintain the device 11. A maintenance request may be issued.

  As described above, in the present embodiment, the device configuration method in which the reliability prediction unit based on the reliability prediction model is mounted as a built-in function of the device, and the device itself performs reliability prediction independently from the sensor information in the device has been described.

Embodiment 4 FIG.
The third embodiment is such that the device itself performs its own reliability prediction (life prediction) from the information of the built-in sensor. Next, environmental information supplement processing and reliability prediction (life prediction) A configuration method is shown in which a dedicated processor is mounted so that the processing does not affect the processing performance of the main processing of the apparatus.

FIG. 9 shows a configuration example of the device 11 according to the present embodiment.
In FIG. 9, the sub CPU 51 is a dedicated processor that performs environmental information complementation and reliability prediction (life prediction) processing.
The RAM 52 is a volatile memory serving as a work area for the sub CPU 51 to operate.
The ROM 53 is a nonvolatile memory that stores programs and data for the sub CPU 51.
The bus bridge 54 is a bridge that separates the sub CPU bus 55 and the main bus 4F.
The sub CPU bus 55 is a bus for the sub CPU 51 to access a memory or the like.
Elements having the same reference numerals as those in FIG. 8 are the same elements as those in FIG.

In the third embodiment, the CPU 44 of the sub-component 42 performs environmental information complementing processing and reliability prediction (lifetime prediction) processing.
In the configuration shown in the third embodiment, it is necessary to divide the resources of the CPU 44 for environmental information supplement processing and reliability prediction (lifetime prediction) processing. There is a possibility that the processing performance of the assigned original process may deteriorate.
In the fourth embodiment, the sub CPU 51 is provided, and the sub CPU 51 performs environmental information complementing processing and reliability prediction (lifetime prediction) processing.
Further, the bus bridge 54 is provided to separate the main bus 4F and the sub CPU bus 55 so that the bus access of the sub CPU 51 does not affect the bus access of the CPU 44, so that the resources of the CPU 44 are used for the main processing of the sub component 42. All can be used.
If communication between the sub CPU 51 and the CPU 44 is not required, the bus bridge 54 is not mounted, and the main bus 4F and the sub CPU bus 55 may be separated.

  As described above, by providing a dedicated hardware resource such as a dedicated processor, it is possible to perform environmental information supplement processing and reliability prediction (lifetime prediction) processing without affecting the processing performance of the apparatus. .

  As described above, in this embodiment, the reliability prediction means based on the reliability prediction model is mounted as a built-in function of the apparatus, and these are processed by a dedicated processor without affecting the processing performance of the main function of the apparatus. An apparatus configuration method for performing reliability prediction independently has been described.

  DESCRIPTION OF SYMBOLS 11 Apparatus, 12 Sensor, 100 Information processing apparatus, 101 Sensor measured value input part, 102 Estimated value calculation part, 103 Comparison part, 104 Estimation part, 105 Reference value information storage part, 106 Reliability prediction part, 107 Comparison / selection part , 200 Reliability evaluation section.

Claims (10)

A reference value information storage unit that stores a reference value for a predetermined parameter of a sensor installed in the management object and a reference value information indicating a reference value for the parameter for each component of the management object;
A sensor measurement value input unit for inputting a sensor measurement value actually measured for the parameter by the sensor;
The component of the management object using the sensor measurement value input by the sensor measurement value input unit, the reference value of the sensor indicated in the reference value information, and the reference value for each component of the management object And an estimated value calculating unit for calculating an estimated value for each parameter. The estimated value calculation unit
The sensor measurement value input by the sensor measurement value input unit is compared with the reference value of the sensor indicated in reference value information, and the reference value for each component of the management object indicated in the comparison result and reference value information The information processing apparatus according to claim 1, wherein an estimated value for the parameter is calculated for each component of the managed object. The reference value information storage unit
Stores multiple types of reference value information,
The estimated value calculation unit
A specific reference value information is selected from a plurality of types of reference value information based on the sensor measurement value input by the sensor measurement value input unit, and the sensor measurement value input by the sensor measurement value input unit is selected. An estimated value for the parameter is calculated for each component of the management object using a reference value of the sensor indicated in reference value information and a reference value for each component of the management object. The information processing apparatus according to claim 1 or 2. The information processing apparatus includes:
The management object where multiple sensors are installed is the management object.
The reference value information storage unit
Storing a plurality of types of reference value information indicating a reference value for each sensor installed in the management object;
The sensor measurement value input unit is
Input a plurality of sensor measurement values from a plurality of sensors installed in the management object,
The estimated value calculation unit
For each reference value information, analyze the approximate degree of the reference values of the plurality of sensors indicated in the reference value information and the plurality of sensor measurement values input by the sensor measurement value input unit, and based on the analysis result, 4. The information processing apparatus according to claim 3, wherein specific reference value information is selected from a plurality of types of reference value information. The information processing apparatus further includes:
Using the estimated value calculated by the estimated value calculating unit, predicting the reliability of the managed object, and determining whether or not maintenance work is required for the managed object; ,
5. A notification output unit that outputs a notification that maintenance work is necessary when the reliability prediction unit determines that maintenance work is necessary. 6. The information processing apparatus described in 1. The information processing apparatus includes:
Equipment that is divided into multiple subcomponents is the management target,
The information processing apparatus according to claim 1, wherein the information processing apparatus is included in any subcomponent of the device. The information processing apparatus includes:
Equipment that is divided into multiple subcomponents is the management target,
Included in any subcomponent of the device,
The sensor measurement value input unit, the estimated value calculation unit, and the reliability prediction unit,
6. The sensor measurement value input, the estimation value calculation, and the reliability prediction are performed independently of an original process assigned to a subcomponent including the information processing apparatus. The information processing apparatus described. The sensor measurement value input unit, the estimated value calculation unit, and the reliability prediction unit,
The information processing apparatus according to claim 7, wherein a hardware resource different from a hardware resource used for an original process assigned to a subcomponent including the information processing apparatus is used. A sensor measurement value input step in which a computer inputs a sensor measurement value actually measured with respect to a predetermined parameter by a sensor installed on the management object;
A reference from which the computer reads reference value information from a reference value information storage area for storing a reference value for the parameter of the sensor and reference value information indicating a reference value for the parameter for each component of the managed object A value information reading step;
The computer uses the sensor measurement value input in the sensor measurement value input step, the reference value of the sensor indicated in reference value information, and the reference value for each component of the management target, and the management target And an estimated value calculating step for calculating an estimated value for the parameter for each component of the object. A sensor measurement value input process for inputting a sensor measurement value actually measured with respect to a predetermined parameter by a sensor installed on the management target;
Reference value information read processing for reading reference value information from a reference value information storage area for storing reference value for the parameter of the sensor and reference value information indicating the reference value for the parameter for each component of the management object When,
The component of the management object using the sensor measurement value input by the sensor measurement value input process, the reference value of the sensor indicated in the reference value information, and the reference value for each component of the management object A program causing a computer to execute an estimated value calculation process for calculating an estimated value for the parameter for each of the parameters.

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