JP2001306131A - Apparatus for supporting turbine maintenance - Google Patents

Abstract

PROBLEM TO BE SOLVED: To achieve planning for a suitable maintenance schedule for a device of a turbine in a power generation plant, by easily and exactly utilizing data of other units using the grouping means, and generally estimate the rest of life of the device by eliminating the need for skill or the like. SOLUTION: The apparatus is provided with the following. About a turbine to be evaluated and the other similar turbines, the data storage means 101-103 save results data like operation results. Based on a design condition of the turbine, like a type of the turbine, etc., previously stored as standard information, and an operating condition, like the number of start and stop, running time, etc., the grouping means 104, 105 classify turbine data into various groups. About the data classified by the grouping means to belong to a same group, the data processing means 106-110 read out it from the data storage means, then execute statistical processing for calculation of the rest of life or the like. As support information, the displaying means 111 displays statistical process results by the data processing means.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a turbine maintenance management support apparatus for performing maintenance management support for a high temperature rotor, a passenger compartment, and the like of a steam turbine used in a commercial thermal power plant or the like.

[0002]

2. Description of the Related Art In the recent situation of thermal power generation facilities,
The construction of new facilities has been suppressed, and the proportion of facilities over a long operating time has tended to increase year by year, and the need to effectively use long-term operating plants has increased. Further, there is a possibility that the deterioration of the material of a high-temperature component of a long-term use plant is progressing due to long-term use at a high temperature. In addition, frequent start-stop and load adjustment operations are performed by using DSS operation of these facilities as intermediate load thermal power, and the operating conditions are more severe than at the time of construction, and there is a tendency to further accelerate the deterioration of members. It is in.

It is indispensable to grasp the deterioration state of the thermal power generation equipment and to estimate the service life in accordance with the operation prediction of the equipment in the future in order to operate the equipment stably and economically. In addition to the remaining life evaluation, periodic inspections, special inspections, and the like are performed to confirm the economic efficiency of turbine equipment. More recently, there has been a demand for a reduction in equipment maintenance costs, and various attempts have been made to realize the state of equipment by combining a remaining life prediction by a conventional method and a life prediction by another method.

[0004]

Incidentally, the remaining life diagnosis test of the turbine is a test performed on a turbine whose operation time exceeds 80,000 hours, and the deterioration state can be grasped only by the life diagnosis. However, depending on the turbine, re-diagnosis may be performed several years after the life diagnosis is performed, and as a result, an update time may be determined. For this reason, there has been a growing demand for a reduction in maintenance costs by reducing the number of life checks.However, in order to predict trends, it is necessary to perform an appropriate life check with only a small amount of data using information on each unit. Have difficulty.

Therefore, as a conventional technique for improving the extra life prediction, another unit similar to the turbine unit whose life is to be diagnosed is selected and the data of the other unit is used as reference data. It is considered. In the past, however, data was often obtained based on the experience of individual technicians.Even if this method was effective for a skilled technician, it would be effective if a young technician used it. There were problems such as being confused by the selection method and unclear evaluation / judgment method even from reference data, making it impossible to support highly accurate extra life diagnosis.

In addition, since the operating conditions of the unit greatly affect the remaining life evaluation data, selection of reference data requires design conditions and operating conditions such as a model and a main steam temperature. Because of the human judgment, the decision was made to rely on the know-how of a skilled person.

Further, conventionally, it has been known that the creep damage amount φc and the low cycle fatigue φf are applied as the remaining life evaluation data. In this case, as the management values, the crack generation limit φc = 1.0, φf = 1.0 is used. However, this management value is not always a value indicating the life of the device.

In general, since only the above-mentioned remaining life evaluation data is used as a judgment material and other measurement data is not used, comprehensive remaining life evaluation cannot be performed.

The inventor of the present invention makes use of the characteristics that cause almost the same deterioration when the material, shape, operating conditions and the like of the turbine are the same, and uses the data of each plant having the turbine of the same material and shape. Are grouped on the basis of information stored in advance, and the evaluation is performed by a statistical method for each group, so that it is possible to predict the remaining life with high reliability.

That is, an object of the present invention is to make a comprehensive judgment on turbine equipment of a power plant by utilizing data of other units and inspection data, estimate a remaining life of the equipment, and formulate an appropriate maintenance plan. To provide a turbine maintenance management support apparatus that can obtain support information for the turbine.

[0011]

In order to achieve the above object, according to the first aspect of the present invention, the operation performance of a turbine to be evaluated and other similar turbines, the damage rate of equipment, component replacement and repair, etc. Data storage means for storing actual data of the turbine, and various turbine data based on turbine design conditions such as turbine type, rotor material, main steam temperature, etc., and operation conditions such as the number of times of starting and stopping, and operating time, which are stored as reference information in advance. Grouping means for classifying the data into groups, data processing means for reading data classified by the grouping means and belonging to the same group from the data storage means, and performing statistical processing on turbine remaining life calculation and the like; Display means for displaying a statistical processing result by the data processing means as support information. To provide turbine maintenance support device to be.

According to the present invention, for example, even when the remaining life of a turbine having a small number of data is predicted, the data of another similar unit to be referred to is grouped based on information stored in advance. Since it can be applied, a highly reliable life expectancy result can be easily obtained without requiring skill or the like.

[0013] Since the evaluation results of the remaining life evaluation data differ depending on the operating conditions and the like even in the turbine unit of the same plant, it is difficult to accurately classify only the design conditions such as the main steam temperature and the steam pressure. Inappropriate data may be input as data used for statistical processing.

According to a second aspect of the present invention, there is provided the turbine maintenance management support apparatus according to the first aspect, further comprising a data excluding unit for excluding data inappropriate for statistical processing by grouping. Provide a turbine maintenance management support device.

According to the present invention, when statistical processing is performed as the same group, by excluding data for which a remaining life result differs due to a difference in operation state, a more reliable remaining life prediction result can be obtained.

According to a third aspect of the present invention, in the turbine maintenance management support apparatus according to the first or second aspect, a master curve registering means for registering a statistical processing result as a master curve as a remaining life prediction curve, and the master curve A turbine maintenance management support apparatus characterized in that it is provided with registration management means for registering and managing at least one of a remaining life diagnosis time and an update time based on the above.

According to the present invention, since the remaining life can be managed by the master curve registered in the master curve registration means, it is possible to judge the remaining life diagnosis, new management and the like without having to rely on the know-how of a skilled person. Becomes That is, in the related art, the remaining life diagnosis is performed uniformly by the operation time in all turbines, and the next remaining life diagnosis time or renewal time is determined based on the result, but according to the present invention, according to the present invention, The remaining life diagnosis and renewal can be performed at an appropriate time, and the repair cost can be reduced.

According to a fourth aspect of the present invention, in the turbine maintenance management support apparatus according to the third aspect, the registration management means for managing the remaining life diagnosis time and the like manages the rotating body and the stationary body of the turbine based on their management values. There is provided a turbine maintenance management support device including a rotating body management unit and a stationary body management unit.

According to the present invention, a rotating body whose life is caused by crack generation and a stationary body whose life is determined by the crack growth after crack generation are managed separately, so that a standard body corresponding to each characteristic can be obtained. Remaining life management becomes possible.

According to a fifth aspect of the present invention, there is provided the turbine maintenance management support device according to any one of the first to fourth aspects, wherein a rotor runout measurement storage unit for storing runout measurement data of the turbine rotor, and the runout of the turbine rotor. A turbine run-out management means for managing the trend of the measurement data, wherein the turbine life management of the turbine rotor is supported by monitoring the life expectancy of the turbine rotor and the run-out trend prediction in parallel to support the life diagnosis of the turbine rotor. Provide a support device.

According to the present invention, it is possible to enhance the monitoring of the rotor life by making a comprehensive judgment using not only the result of the remaining life diagnosis but also the data for determining the life of the rotor, which is another life determinant. It becomes possible to prevent it from occurring.

According to a sixth aspect of the present invention, in the turbine maintenance management support device according to any one of the first to fifth aspects, a cabin crack measurement data storage unit for storing cabin crack measurement data; A turbine for calculating the crack growth speed of the vehicle, and supporting life prediction of the vehicle room and monitoring the crack growth speed in parallel to support the life diagnosis of the vehicle room. Provided is a maintenance management support device.

According to the present invention, monitoring of the life of the passenger compartment can be strengthened by taking into account the crack growth rate after the occurrence of the crack in the passenger compartment. Prevention, simplification of repair time plan, reduction of repair cost, etc. can be effectively achieved.

[0024]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of a turbine maintenance management support apparatus according to the present invention will be described below with reference to the drawings.

First Embodiment (FIGS. 1 and 2) FIG. 1 is a block diagram showing a first embodiment of the present invention.
FIG.

In this embodiment, as shown in FIG. 1, a remaining life evaluation data storage unit 101, a replacement performance data storage unit 102, and a skin cut performance data storage unit 103 are provided as data storage means.

The remaining life evaluation data storage unit 101 stores a fatigue damage rate φf, a creep damage rate φc at the time of remaining life evaluation, a time at the time of remaining life evaluation, and a time from the start of plant operation to the remaining life evaluation at each part of the plant equipment. Data such as the number of times of starting and stopping and the total operation time are stored.

The replacement result data storage unit 102 stores data such as the time when a new replacement of the equipment of the plant is performed, the number of start / stop times from the start of operation of the plant at the time of the replacement of the new product to the replacement of the new product, and the operation time. In the skin cut result data storage unit 103, the time when the skin cut is performed for each part of the plant equipment, the number of times of start and stop from the start of the operation of the plant during the skin cut to the time of the skin cut, the operation time, and the like. Data is stored.

Next, as grouping means, a grouping classification information storage unit 104 and a grouping processing unit 10
5 is provided.

In the grouping classification information storage unit 104,
Design conditions such as rotor material, main steam temperature, reheat steam temperature and output, and operating conditions such as start and stop times, operation time,
Elapsed time information is saved. In the grouping processing unit 105, the life evaluation data storage unit 1
01, data input from the replacement result data storage unit 102 and the skin cut result data storage unit 103 are grouped (grouping) based on information in the grouping classification information storage unit 104 according to design conditions, operation conditions, and the like.
Thus, reading by the following data processing means is enabled.

Here, the grouping operation will be described with reference to FIG. FIG. 2 shows an example in which the remaining life diagnosis results of the turbine rotor center holes belonging to the same group are plotted on a graph in which the horizontal axis represents the total operation time and the vertical axis represents the creep damage amount φc.

As shown in FIG. 2, the results of the life diagnosis of a plurality of turbines belonging to the same group vary with respect to the total operation time as a deterioration index. At this time, it is conceivable that the maximum value of the turbines in the same group is predicted based on the average value, the minimum value, the results of typical turbines, and the like. Use values. If there is an actually measured value, a line parallel to the selected reference line and an actual line passing through the origin and the actually measured value can be selected.

The data processing means reads the data classified by the grouping processing unit 105 and belonging to the same group as described above, and performs statistical processing such as turbine remaining life calculation. It comprises an evaluation data reading unit 106, an aging parameter calculation unit 107, a remaining life evaluation data statistical processing unit 108, a deterioration tendency prediction unit 109, a remaining life prediction unit 110, and the like.

The remaining life evaluation data reading unit 106 reads the data of the turbines belonging to the same group from the life evaluation data storage unit 101, the replacement performance data storage unit 102, and the skin cut performance data storage unit 103. It is input to the aging parameter calculator 107.
The aging parameter calculation unit 107, based on the input data, determines the number of times of starting and stopping of the part to be skin-cut from the latest skin cut before the life evaluation to the remaining life evaluation and the latest skin cut before the life evaluation. Calculate the operating time of the equipment from the time of new product replacement to the time of life evaluation.

The remaining life evaluation data statistical processing section 108 performs statistical processing to set a deterioration tendency prediction line serving as a reference for turbines belonging to the same group.

As described above, using the prediction line selected by the remaining life evaluation data statistical processing unit 108, the deterioration tendency prediction unit 1
In 09, the rate of increase of the fatigue damage rate φf stored in the life evaluation data storage unit with respect to the number of times of starting and stopping from the latest new replacement or skin cut before the life evaluation of the life evaluation data, and creep damage The rate of increase of the rate φc with respect to the operating time since the latest new replacement before the life evaluation of the life evaluation data is calculated. The remaining life prediction unit 110 calculates the remaining life of the part based on the linear fracture mechanics, using the increase rate calculated by the deterioration tendency prediction unit.

Further, in this embodiment, a display unit 111 such as a display is provided as a display unit for displaying the calculation result. In the display unit 111, a life diagnosis result graph, a life diagnosis result, a remaining life diagnosis result, a selected curve, an operation time, a start / stop time, an elapsed time, and the like of turbines belonging to the same group are displayed as images and the like.

According to the above-described embodiment, data of similar units employed as a technique for enhancing the extra life prediction is classified by the grouping processing unit 105 based on the information in the grouping classification information storage unit 104. Since it can be used as reference data, it is not necessarily limited to skilled personnel, and individual technicians can relatively easily select similar units, evaluate and judge based on reference data, etc. It is possible to support extra life diagnosis with high cost. In other words, comprehensive judgment can be performed on turbine equipment of a power plant by utilizing data of other units and inspection data, and it is easy to obtain support information for estimating the remaining life of equipment and formulating an appropriate maintenance plan. This makes it possible to predict the remaining life with high reliability.

Second Embodiment (FIGS. 3 and 4) FIG. 3 is a block diagram showing a second embodiment of the present invention.
Is a graph for explaining the operation. In the present embodiment, there is provided a data exclusion unit for excluding data inappropriate for statistical processing by grouping.

That is, as shown in FIG. 3, in this embodiment, together with the grouping processing unit 205 similar to FIG.
It has a data exclusion unit 212 as data exclusion means. Means indicated by reference numerals 201 to 211 in FIG.
It shows the same means as 101 to 111 in FIG.

In the graph of FIG. 4, the horizontal axis indicates the number of times of starting and stopping, and the vertical axis indicates the low-cycle fatigue damage amount φf, and plots the results of remaining life diagnosis of the inner surface of the main steam valve belonging to the same group. ing. As shown in FIG. 4, even if the grouping is performed as the same group in the grouping processing unit 205, data a that deviates from a certain range may exist. This is an example in which the progress of low-cycle fatigue damage is accelerated due to severe use such as sudden start / stop during use during operation.

When performing statistical processing, if such abnormal data is included, it is impossible to obtain an appropriate result in the calculation of the maximum value, the average value, and the like. Can be excluded.

According to the present embodiment, when statistical processing is performed as the same group, data in which the remaining life result differs due to a difference in operation state is excluded, so that a more reliable remaining life prediction result can be obtained.

Third Embodiment (FIG. 5) FIG. 5 is a block diagram showing a third embodiment of the present invention. The means indicated by reference numerals 301 to 312 in FIG. 5 are the same as the means indicated by reference numerals 201 to 212 in FIG.

In this embodiment, as shown in FIG. 5, a master curve registration unit 313 for registering a statistical processing result as a remaining life prediction curve (master curve), a remaining life diagnosis time and an update time based on the master curve. And a registration management unit 314 for registering and managing at least one of the remaining life times.

That is, in the above-described first and second embodiments, in addition to the life diagnosis result of the turbine to be supported, statistical processing is performed using the life diagnosis result of the same group to predict the deterioration tendency. However, in the present embodiment, a master curve registration unit 313 is provided in addition to the deterioration tendency prediction unit 309, thereby adding a function of registering the turbine deterioration tendency prediction as a master curve in advance. . Then, the deterioration tendency prediction is performed without performing the operations of the grouping processing unit 305, the remaining life evaluation data reading unit 306, the aging parameter calculation unit 307, and the remaining life evaluation data statistical processing unit 308. Has been achieved.

Further, in the above-described prior art, the crack generation time at which the creep damage φc and the low cycle fatigue damage φf adopted as life prediction data become 100% is defined as:
Although it was evaluated as one life, there are many turbines that do not crack even when the creep damage φc and the low cycle fatigue damage φf reach 100%. It is thought that it can be managed by changing to 105%.

Therefore, in the present embodiment, the remaining life predicting section 30
Remaining life diagnosis / update time management unit 31 for managing the management value of 6
5 and the addition of a remaining life diagnosis / update timing registration unit 314 for registering a management value in the remaining life diagnosis / update timing management unit 315 allow management by changing the management value, which is more practicable. It can be.

According to the present embodiment, since the remaining life can be managed by the master curve registered in the master curve registering means, it is not necessary to rely on the know-how of the skilled person, and the remaining life diagnosis, new management, etc. Can be determined.
Therefore, in the past, the remaining life diagnosis was performed uniformly by the operation time in all turbines, and the next remaining life diagnosis time or update time was determined based on the result. The remaining life diagnosis and renewal can be performed at an appropriate time for each turbine, and the repair cost can be reduced.

Fourth Embodiment (FIG. 6) FIG. 6 is a configuration diagram showing a fourth embodiment of the present invention. The means indicated by reference numerals 401 to 415 in FIG. 6 are the same as the means indicated by reference numerals 301 to 315 in FIG.

In this embodiment, as shown in FIG. 6, an extended configuration of the remaining life diagnosis / update timing registration unit 414 and the remaining life diagnosis / update timing management unit 415 is shown.

That is, conventionally, regarding the crack initiation life of the turbine equipment, the creep damage φc and the low cycle fatigue damage φf are controlled at 100%, and the life of the turbine equipment tends to be regarded as 100% damage.

However, in a rotating device such as a rotor, for example, after a crack is generated, the crack may grow at a high speed, which may lead to a large accident such as scattering of the rotor. Therefore, for example, when the life diagnosis time is φ
In some cases, c = 80% or φf = 80%, and the update timing may be managed as φc = 100% or φf = 100%.

However, in the case of a stationary body such as a vehicle cabin, for example, it is considered that the life diagnosis timing can be managed as φc = 120% or φf = 120%.

In the present embodiment, by utilizing this feature, the remaining body diagnosis / update time registration section 414 is provided with the rotating body registration section 41.
4a and a stationary body registration section 414b, and a rotating body registration section 415a and a stationary body registration section 415b are prepared in a remaining life diagnosis / update time management section 415, and a remaining life diagnosis / It is possible to register and manage the renewal time separately.

According to the present embodiment as described above, it is possible to separately manage the rotating body having the life of the crack generation and the stationary body having the life determined by the crack propagation after the crack generation. Corresponding standard remaining life management becomes possible.

Fifth Embodiment (FIG. 7) FIG. 7 is a block diagram showing a fifth embodiment of the present invention. The units indicated by reference numerals 501 to 515 in FIG. 7 are the same as the units indicated by reference numerals 401 to 415 in FIG.

As shown in FIG. 7, in this embodiment, in addition to the configuration of the fourth embodiment, a rotor runout measurement storage unit 516 for storing runout measurement data of the turbine rotor, and a tendency of the runout measurement data of the turbine rotor are shown. A rotor runout tendency management unit 517 to be managed is provided, and the life prediction of the turbine rotor and the runout trend prediction are monitored in parallel to support the life diagnosis of the turbine rotor.

For example, regarding the life of the rotor, there are not only the creep damage and low-cycle fatigue damage confirmed by the remaining life diagnosis, but also elements that determine the life, such as the rotor run-out measured in the periodic inspection.

Therefore, not only the life diagnosis data,
The result of the periodic inspection such as the rotor runout is taken in, and the life of the rotor is comprehensively determined. For this purpose, a rotor runout data storage section 516 and a rotor runout tendency management section 517 are provided. The information is input to the remaining life prediction unit 510.

The rotor runout data storage unit 516 stores the rotor runout data obtained during the periodic inspection, and the rotor runout tendency management unit 517 manages the data. Various prediction lines such as a primary straight line and a secondary curve are used for the trend management.

The turbine maintenance management support device according to the present embodiment can set four types of data, namely, a linear straight line, a quadratic curve, an exponential curve, and data of similar units. However, the cause of rotor runout is caused by creep damage. Because it is possible, 1
Mainly trend management by the following straight line.

The remaining life estimating unit 510 calculates the increase rate with respect to the operating time from the latest new product replacement as a result of the rotor runout tendency managing unit 517 and the life evaluation of the life evaluation data as the result of the deterioration tendency estimating unit 505. The remaining life of the part is calculated based on linear fracture mechanics using the increase rate with respect to the operation time from the latest new product exchange before the hour. The display unit 517 displays the results of the rotor runout trend management and the deterioration trend prediction as the result of the remaining life prediction unit, and displays information for comprehensively determining the life of the rotor.

According to the present embodiment, not only the result of the remaining life diagnosis but also a comprehensive judgment is made using data for judging the life of the rotor, which is another life determinant, so that the monitoring of the life of the rotor can be strengthened and the accident can be strengthened. Can be prevented beforehand.

Sixth Embodiment (FIG. 8) FIG. 8 is a configuration diagram showing a sixth embodiment of the present invention. The means indicated by reference numerals 601 to 615 in FIG. 8 are the same as the means indicated by reference numerals 401 to 415 in FIG.

As shown in FIG. 8, in this embodiment, in addition to the fourth embodiment, a means for monitoring the life of the vehicle compartment from multiple aspects is provided. In other words, the vehicle includes a cabin crack measurement data storage unit 616 for storing cabin crack measurement data, and a cabin crack growth speed calculation unit 617 for calculating a cabin crack growth speed. By monitoring the speed in parallel, the system assists in the diagnosis of vehicle life span.

For example, the life of the vehicle compartment can be used by repair even after a crack is generated, and the service limit is the time when the vehicle compartment thickness reaches the service limit thickness (Tsr). .

Therefore, in the present embodiment, creep damage and low cycle fatigue damage confirmed by life diagnosis are 100%.
%, The life of the vehicle compartment is managed by controlling the crack growth rate by assuming that a crack has occurred at the time of reaching the%.
A cabin crack tendency management unit 617 is provided, and these pieces of information are input to the remaining life prediction unit 610.

The remaining life estimating unit 610 uses the rate of increase in operating time from the latest new replacement before the time of the life evaluation of the life evaluation data, which is the result of the cabin thickness tendency management unit 617, to obtain linear fracture mechanics. The remaining life of the part is calculated based on In the display unit 611, as a result of the remaining life prediction unit,
The result of the cabin thickness tendency management unit and the result of the deterioration tendency prediction are displayed, and information for comprehensively determining the life of the rotor is displayed.

According to the present embodiment, the life monitoring of the vehicle compartment can be strengthened by taking into account the crack growth rate after the occurrence of the crack in the vehicle compartment, thereby enabling a comprehensive evaluation including the remaining life of the vehicle compartment. It can prevent accidents, facilitate repair time planning, reduce repair costs, and so on.

[0071]

As described above in detail, according to the turbine maintenance management support apparatus of the present invention, the data of other units can be easily and accurately utilized by the grouping means for the turbine equipment of the power plant. This makes it possible to comprehensively estimate the remaining life of the equipment without requiring skill and the like, to formulate an appropriate maintenance plan, and to obtain a highly reliable life prediction result.

[Brief description of the drawings]

FIG. 1 shows a first embodiment of a turbine maintenance management support apparatus according to the present invention.
FIG. 1 is a configuration diagram illustrating an embodiment.

FIG. 2 is a characteristic diagram for explaining the operation of the embodiment.

FIG. 3 shows a second embodiment of the turbine maintenance management support apparatus according to the present invention.
FIG. 1 is a configuration diagram illustrating an embodiment.

FIG. 4 is a characteristic diagram for explaining the operation of the embodiment.

FIG. 5 shows a third embodiment of the turbine maintenance management support apparatus according to the present invention.
FIG. 1 is a configuration diagram illustrating an embodiment.

FIG. 6 shows a fourth embodiment of the turbine maintenance management support apparatus according to the present invention.
FIG. 1 is a configuration diagram illustrating an embodiment.

FIG. 7 shows a fifth embodiment of the turbine maintenance management support apparatus according to the present invention.
FIG. 1 is a configuration diagram illustrating an embodiment.

FIG. 8 shows a sixth embodiment of the turbine maintenance management support apparatus according to the present invention.
FIG. 1 is a configuration diagram illustrating an embodiment.

[Explanation of symbols]

 101 to 601 remaining life evaluation data storage unit 102 to 602 actual data storage unit 103 to 603 skin cut actual data storage unit 104 to 604 grouping classification information storage unit 105 to 605 grouping processing unit 106 to 606 remaining life evaluation data reading unit 107 to 607 Aging parameter calculation unit 108-608 Remaining life evaluation data statistical processing unit 109-609 Deterioration tendency prediction unit 110-610 Remaining life prediction unit 111-611 Display unit 111 212-612 Data exclusion unit 313-613 Master curve registration unit 314- 614 Remaining life diagnosis / update time registration unit 314 to 614 Remaining life diagnosis / update time registration unit 315 to 615 Remaining life diagnosis / update time management unit 516 Rotor runout data storage unit 517 Rotor runout trend management unit 616 Cabin crack data storage unit 617 car room Crack trend management unit

Claims (6)

[Claims] 1. A turbine maintenance management support device that performs remaining life evaluation based on operation data of turbine equipment in an operating plant and displays items necessary for future maintenance management, the turbine to be evaluated and Data storage means for storing the actual performance data of other similar turbines, such as operation results, equipment damage rate, parts replacement and repair, and turbine design such as turbine type, rotor material, main steam temperature, etc. stored as reference information in advance Grouping means for classifying turbine data into various groups based on operating conditions such as conditions and start / stop times, operation time, and the like, and data that is classified by this grouping means and belongs to the same group is read from the data storage means, Data processing means for performing statistical processing on turbine remaining life calculation, etc. A display unit for displaying, as support information, a statistical processing result by the data processing unit. 2. The turbine maintenance management support device according to claim 1, further comprising a data exclusion unit for excluding data inappropriate for statistical processing by grouping. 3. The turbine maintenance management support device according to claim 1, wherein a master curve registration means for registering a statistical processing result as a master curve as a remaining life prediction curve, and a remaining life based on the master curve. A turbine maintenance management support device comprising a registration management means for registering and managing at least one of a diagnosis time and an update time, such as a remaining life diagnosis time. 4. The turbine maintenance management support device according to claim 3, wherein the registration management means for remaining life diagnosis time and the like manages the rotating body and the stationary body of the turbine based on their management values. A turbine maintenance management support device comprising stationary body management means. 5. The turbine maintenance management support device according to claim 1, wherein a rotor runout measurement storage unit that stores runout measurement data of the turbine rotor.
A rotor runout trend managing unit that manages the trend of the runout measurement data of the turbine rotor, and supports life diagnosis of the turbine rotor by monitoring life expectancy and runout trend prediction of the turbine rotor in parallel. Turbine maintenance management support equipment. 6. The turbine maintenance management support device according to claim 1, wherein a cabin crack measurement data storage means for storing cabin crack measurement data, and a crack growth speed of the cabin. A turbine maintenance management support device comprising: a cabin crack growth speed calculation means for calculating the life of the cabin and monitoring the life of the cabin by monitoring the life of the cabin and the crack growth speed in parallel.