Information processing device, information processing method, and program

Abstract

To allow for quantitatively grasping the degree of deterioration of equipment.SOLUTION: An information processing device is provided, comprising an acquisition unit for acquiring equipment operation data indicative of temporal changes in an operating state value of equipment, an extraction unit configured to extract an abnormality occurrence period in which the operating state value is less than an abnormality threshold value during an evaluation target period from the equipment operation data, and a computation unit configured to compute the degree of deterioration of the equipment based on a difference between the abnormality threshold value and the operating state value during the abnormality occurrence period.SELECTED DRAWING: Figure 5

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and a program. [Background technology]

[0002] Currently, efforts to achieve carbon neutrality are gaining momentum. For example, Reference 1 states that in order to achieve decarbonization of the power sector, it is necessary to shift to non-fossil fuel energy sources such as renewable energy. An electric furnace using generated, carbon dioxide-free electricity is disclosed. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2023-007360 A Summary of the Invention [Problem to be solved by the invention]

[0004] Designed to emit as little carbon dioxide as possible to achieve carbon neutrality By using the facility, the amount of carbon dioxide emitted can be reduced. However, since installed equipment gradually deteriorates, it may not be able to perform as well as it was initially intended to. Therefore, it is necessary to quantitatively determine the degree of deterioration of the equipment. It is desirable to have a system that can be evaluated in a practical manner. This is not limited to equipment, but can occur in any type of equipment.

[0005] Therefore, the present invention provides a technique that enables quantitative understanding of the degree of deterioration of equipment. The purpose of this document is to [Means for solving the problem]

[0006] The information processing device according to one aspect of the present invention is a setting device that shows a time series change in an operation status value of a facility. an acquisition unit that acquires equipment operation data; and An extraction unit that extracts an abnormality occurrence period in which an operation state value is less than an abnormality threshold value; Based on the difference between the abnormality threshold value and the operating state value, the deterioration degree of the equipment is calculated. and a calculation unit that outputs the Effect of the Invention

[0007] According to the present invention, a technique is provided that enables the degree of deterioration of equipment to be quantitatively understood. It is possible. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of a management system according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a diagram for explaining an example of equipment operation data of equipment. [Diagram 3] FIG. 11 is a diagram illustrating an example of a method for determining an abnormality threshold value. [Figure 4] FIG. 2 is a diagram illustrating an example of a hardware configuration of an information processing device. [Diagram 5] FIG. 2 is a diagram illustrating an example of a functional block configuration of an information processing device. [Figure 6] 11 is a flowchart illustrating an example of a processing procedure in which the information processing device determines and updates an abnormality threshold value. [Figure 7] 11 is a flowchart illustrating an example of a processing procedure for an information processing device to calculate a deterioration degree of equipment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] An embodiment of the present invention will be described with reference to the accompanying drawings. Those marked with the same symbol have the same or similar configuration.

[0010] <System configuration> FIG. 1 is a diagram showing an example of a management system 1 according to the present embodiment. The management system 1 includes: The information processing device 10 and one or more devices 20 are connected wirelessly or They may be connected via a wired communication network and be capable of communicating with each other. .

[0011] The information processing device 10 is a device that manages the operating status of the equipment 20. It is a machine that performs some function by being operated, and is not an inoperable equipment such as land and buildings. An example of a facility20 is the realization of a carbon-neutral society. These include equipment and devices that contribute to the realization of this goal. Natural Gas boilers and biomass fuel production equipment. The LNG boiler is capable of generating electricity without emitting carbon dioxide. This reduces carbon dioxide emissions compared to boilers that use heavy oil, etc. The biomass fuel production equipment promotes the use of biomass fuel by producing it. This will contribute to achieving carbon neutrality.

[0012] The facility 20 according to the present embodiment does not necessarily aim to realize a decarbonized society and carbon new Equipment 20 is not limited to equipment and devices that contribute to the realization of the standard. Any possible facility 20 may be used.

[0013] The operating state of the equipment 20 refers to a state in which the equipment 20 is operating and exerting a specified capacity. In this embodiment, the operating state of the equipment 20 is expressed by a numerical value. The value indicating the capacity of the equipment 20 is called the "operational status value." It may be expressed as a percentage, with 100% being the maximum possible capacity. For example, in the case of a solar power generation facility, the operating status is not limited to the The state value may be expressed in terms of power generation (e.g., watts) or the power generation at a given point in time relative to the maximum power generation capacity. The percentage of the amount of electricity consumed may be expressed as a percentage (e.g., 30%). In this case, the operating status value may be expressed as the production volume at a given time (e.g., X kg / day). However, it may be expressed as a percentage of maximum production capacity at a given time (e.g., 90%). good.

[0014] FIG. 2 is a diagram for explaining an example of equipment operation data of the equipment 20. The vertical axis of the graph shown in Figure 2A is the operating status. The horizontal axis represents the time. The data consists of a number of samples (each sample is a pair of a health value and a timestamp). During the period from t4 to t5, the equipment 20 may be intentionally stopped for equipment inspection or the like. The information indicating the period during which the equipment 20 was intentionally stopped may be, for example, The information may be input to the information processing device 10 by an administrator of the equipment 20 or the like.

[0015] Here, the abnormality threshold is a threshold for determining whether the operation state value of the equipment 20 is abnormal. In this embodiment, when the operation state value is less than the abnormality threshold value, it is determined that an abnormality has occurred in the equipment 20. On the other hand, if the operation state value is equal to or greater than the abnormality threshold, the equipment 20 is determined to be normal. The abnormality threshold may be determined in advance by an administrator or the like, or may be determined by a predetermined method. The method for determining the abnormality threshold value will be described later. During the period from t1 to t3, the operation state value is less than the abnormal threshold value. The period from t1 to t3 indicates that some abnormality occurred in the equipment 20.

[0016] The probability density function f(x) shown in FIG. 2B is calculated based on the probability density function f(x) for a given period (for example, one month ago to the present, etc.). ) of the operating status values ​​during the period in which equipment 20 was intentionally stopped, excluding the period The probability density distribution for the dynamic state value is shown. The shape of the probability density function f(x) is determined by the equipment 20. For example, if equipment 20 is always in full operation, the operation status value is always Since the value is close to 100%, the shape of the probability density function f(x) is as shown in Figure 2B. On the other hand, on average, the plant is operating at about 50% capacity, but depending on the time period, In the case of equipment 20 that fluctuates its operating volume depending on the load, the shape of the probability density function f(x) is normal. The probability density distribution is expected to be close to the distribution included in the equipment operation data, for example. A histogram is created by counting the number of samples for each operating state value. Alternatively, the histogram may be graphed to obtain the value.

[0017] In this embodiment, when the operation state value is less than the abnormality threshold, the operation state value is increased from the abnormality threshold. The value obtained by subtracting the state value is called the "degree of abnormality." In other words, the degree of abnormality (t) at time t is the degree of abnormality. The abnormality level (t) can be calculated using the formula: abnormality threshold value - operating state value (t). The magnitude of the normality indicates the abnormality at time (t2). Since the value is obtained by subtracting the operating state value from the threshold value, the larger the value, the more abnormality has occurred in the equipment 20. Indicates a high degree of normality.

[0018] FIG. 3 is a diagram illustrating an example of a method for determining the abnormality threshold. For example, the abnormality threshold is set to an operating state value For the probability density function f(x), integrate the operating state value x from a specified value to the maximum value. The predetermined value at which the cumulative probability (i.e., the upper probability) obtained by For example, in the example of FIG. 3, the operating state value is multiplied from a predetermined value to a maximum value. If the cumulative probability obtained by dividing the The operating state value x1, where the area of ​​the The predetermined probability is not limited to 95% and may be, for example, 80% or 99%.

[0019] In this embodiment, the period for evaluating the deterioration of the equipment 20 (hereinafter, referred to as the “evaluation period”) ) for the period when the operating status value was below the abnormal threshold, the integrated abnormal value is called Specifically, the degree of deterioration of equipment is calculated by the following formula (1): It can be calculated.

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[0020] For example, if you want to evaluate the deterioration of equipment 20 over the past year (i.e., the evaluation period If the operating status value is greater than or equal to the abnormal threshold value from one year ago to the present, By integrating the abnormal values ​​for the period when the In addition, the ratio of equipment 20 in the period from two years ago to one year ago can be calculated. If you want to evaluate deterioration (i.e., the evaluation period is from 2 years ago to 1 year ago), 2 The period from one year ago to one year ago when the operating status value was below the abnormal threshold is considered an abnormal value. By integrating, the "degree of equipment deterioration" from two years ago to one year ago is calculated. In this way, it is possible to compare the "degree of deterioration of equipment" during different evaluation periods. By doing so, it becomes possible to grasp the extent to which the deterioration of the equipment 20 has progressed. Using machine learning technology, we have been able to estimate the trend of changes in the degree of deterioration of equipment over multiple evaluation periods. By analyzing trends, it will also be possible to estimate the "degree of equipment deterioration" in the future.

[0021] The information processing device 10 may also have a function related to the calculation of insurance money. As an example of insurance in which the device 10 calculates the insurance amount, for example, the deterioration of the equipment 20 is insured. For example, the information processing device 10 may provide insurance based on the degree of deterioration of the equipment. The amount of insurance payable to the insured may be calculated based on the amount of the insured's insurance premium. Since the deterioration of the facility 20 is clearly stated as a reason for exemption, it is not covered by the insurance payment. However, according to the present embodiment, the deterioration degree of the equipment 20 Since it is possible to calculate the damage, it becomes possible to provide insurance against deterioration of the equipment 20.

[0022] <Hardware configuration> FIG. 4 is a diagram illustrating an example of a hardware configuration of the information processing device 10. CPU (Central Processing Unit), GPU (Graphical Processing Unit) and other processors processor 11, memory (e.g., RAM or ROM), HDD (Hard Disk Drive) and / or The storage device 12 such as an SSD (Solid State Drive), a network for wired or wireless communication, A network interface (IF) 13, an input device 14 for receiving input operations, and an information output device The input device 14 includes, for example, a keyboard, a touch panel, The output device 15 is, for example, a display, a touch panel, etc. and / or speakers, etc.

[0023] The information processing device 10 may be configured as one or more physical servers, or may be a high-performance It may be configured using a virtual server running on a hypervisor. Alternatively, it may be configured using a cloud server.

[0024] <Function block configuration> FIG. 5 is a diagram showing an example of a functional block configuration of the information processing device 10. A storage unit 100, an acquisition unit 101, an extraction unit 102, a calculation unit 103, and a determination unit 104. The storage unit 100 includes a storage device 101 included in the information processing device 10. 2. Also, the acquisition unit 101, the extraction unit 102, and the calculation unit 10 3, the determination unit 104, and the insurance payment calculation unit 105 are implemented by the processor 11 of the information processing device 10. This can be realized by executing a program stored in the storage device 12. The storage unit 100 can be realized by the storage device 12. The program may be stored in a storage medium. The storage medium storing the program may be used by a computer. Non-transitory computer readable medium The non-transitory storage medium is not particularly limited, but may be, for example, a USB (Universal Serial Bus) memory or CD-ROM (Compact Disc Read-Only Memory) or other storage media It may be a body.

[0025] The storage unit 100 stores an equipment operation DB (Data Base) 100a. 0a is a database that stores equipment operation data for each piece of equipment 20.

[0026] The acquisition unit 101 acquires time-series changes in the operation state values ​​of the equipment 20 from the equipment operation DB 100a. Obtain equipment operation data that shows the progress of

[0027] The extraction unit 102 extracts, from the equipment operation data acquired by the acquisition unit 101, The period during which the operation state value is less than the abnormality threshold (the abnormality occurrence period) is extracted. For example, the extraction unit 10 2 is the period when an abnormality occurs when extracting the period when an abnormality occurs from the equipment operation data shown in A of Figure 2. Then, extract the period t1 to t3.

[0028] The calculation unit 103 calculates a difference value between the abnormality threshold value and the operating state value during the abnormality occurrence period (i.e., The degree of deterioration of the equipment is calculated based on the normal level.

[0029] The calculation unit 103 also calculates the probability density of the operation state value from the equipment operation data for a predetermined period. Generate a distribution (probability density).

[0030] The determination unit 104 determines the operation state value based on a predetermined value for the probability density distribution calculated by the calculation unit 103. The cumulative probability obtained by integrating from the maximum value to the abnormal value is the predetermined value when the cumulative probability becomes the predetermined probability. The determination unit 104 determines the threshold value as the equipment operation data for the predetermined period after updating. The abnormality threshold may be updated using the following formula:

[0031] The insurance payment calculation unit 105 calculates the amount of insurance payment based on the degree of deterioration of the equipment.

[0032] <Processing Procedure> (Determination of abnormality threshold) FIG. 6 is a flow diagram showing an example of a processing procedure in which the information processing device 10 determines and updates the abnormality threshold value. This is a chart.

[0033] In step S100, the acquisition unit 101 accesses the facility operation DB 100a and acquires the facility operation data for a predetermined period of time. The equipment operation data of the equipment 20 in the predetermined period is obtained. The length of the period is arbitrary as long as the period is set to the predetermined period. The predetermined period is determined according to the deterioration rate of the equipment 20. For example, in the case of equipment 20 that is subject to rapid deterioration due to high load operation, Therefore, it is preferable that the abnormality threshold be updated frequently. For example, the past month or the past week may be set. For such equipment 20, it is considered that there is little need to update the abnormality threshold frequently. Therefore, the predetermined period may be set to a long period (for example, the past six months or the past year).

[0034] In step S101, the calculation unit 103 calculates the equipment operation data acquired in step S100. The probability density was calculated from the equipment operation data for the period excluding the period when the equipment 20 was intentionally stopped. Generate a probability density distribution. To generate a probability density distribution, we need to find the probability density function f(x). The probability density distribution can be generated, for example, by using an existing library. As described above, the probability density distribution can be calculated by using the samples included in the equipment operation data. The number of pulls may be generated by counting each operation status value.

[0035] In step S102, the determination unit 104 determines whether On the other hand, the operating state value when the upper probability becomes a predetermined probability is determined as the abnormality threshold value. The rate is arbitrary, but it may be set to, for example, 80%, 95%, 99%, etc. The predetermined probability may be determined according to the type of equipment 20, etc.

[0036] In addition, when the probability density distribution can be approximated by a normal distribution, the determination unit 104 uses the Mahalanobis The abnormality threshold may be determined using the distance. The Mahalanobis distance is a certain negative value (e.g., -1, which corresponds to an upper probability of 95%). 96) may be set as the abnormality threshold value.

[0037] (Update of abnormality threshold) Next, a process procedure when the information processing device 10 updates the abnormality threshold value will be described. 20 is due to the improvement of processing capacity through maintenance, etc., and the installation of new equipment through equipment renewal. In order to improve processing capacity, facilities may be upgraded or upgraded. In such a case, if an anomaly threshold based on a probability density distribution calculated in the past is used, It may become difficult to correctly determine an abnormality in the equipment 20. 0 updates the probability density distribution and updates the anomaly threshold using the updated probability density distribution. do.

[0038] The probability density distribution and the abnormality threshold are updated by repeating the process shown in Fig. 6 at a predetermined interval. That is, the acquisition unit 101 of the information processing device 10 may perform the process of step S100. In the procedure, the equipment operation DB 100a is accessed again to obtain the equipment operation data of the equipment 20 during a predetermined period. In addition, the calculation unit may acquire the updated operation data (i.e., the updated equipment operation data). 103 is a processing procedure of step S101, in which probability density distribution is performed using the updated equipment operation data. The cloth may be updated. The abnormality threshold may be updated based on the updated probability density.

[0039] For example, the information processing device 10 first uses the equipment operation data from "January 1 to January 31". In this case, the information processing device 10 determines the abnormality threshold value based on the above. The abnormality threshold is determined using the equipment operation data from February 2016 to February 28. The threshold value may be updated. After that, the information processing device 10 updates the threshold value every month from the most recent one. The abnormality threshold is updated by repeating the process of determining the abnormality threshold using monthly equipment operation data. This may be repeated. For example, even if equipment is renewed in April, The information processing device 10 detects abnormalities in June using the equipment operation data from "May 1 to May 31." By determining the threshold value, the abnormality threshold value can be updated to a value that reflects the equipment 20 status after equipment replacement. It will be possible to do this.

[0040] In addition, in the processing procedure of steps S100 and S101, the information processing device 10 Therefore, the probability density distribution may be updated using Bayesian updating. This is a general formula for expressing the size update.

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[0041] If the probability density distribution is a normal distribution, the calculation unit 103 calculates the probability density distribution after updating by The mean and variance of the good.

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[0042] (Calculation of the degree of deterioration of equipment) FIG. 7 is a flow diagram showing an example of a processing procedure for the information processing device 10 to calculate the deterioration degree of the facility. This is a chart.

[0043] In step S200, the calculation unit 103 calculates whether the operation state value is greater than or equal to the abnormality threshold value during the evaluation period. If there is no abnormality occurrence period, the If not, the process ends; if present, the process proceeds to step S201.

[0044] In step S201, the calculation unit 103 calculates the equipment More specifically, the calculation unit 103 calculates the degree of deterioration of the abnormality during the abnormality occurrence period. The value obtained by integrating the time series change in the degree of deterioration over the period in which the abnormality occurred is regarded as the degree of deterioration of the equipment. The calculation is as follows.

[0045] For example, the evaluation period is from January 1 to January 31. Between 8:00 and 11:00 on January 20th, and between 8:00 and 10:00 on January 20th, the operating status value was below the abnormal threshold. In this case, the calculation unit 103 calculates the abnormality degree (t ) and the integrated value of the degree of anomaly (t) from 8:00 to 10:00 on January 20th. The calculated value is the degree of deterioration of the equipment.

[0046] <Calculation of insurance benefits> The insurance payment calculation unit 105 calculates the amount of insurance payment based on the degree of deterioration of the equipment. For example, The insurance money calculation unit 105 calculates the insurance money for compensating for the deterioration of the equipment 20 based on the following formula (5): The insurance payment amount for the above may be calculated. Insurance payment amount = Degree of deterioration of equipment × Coefficient (5) The coefficient is a value determined in advance based on, for example, the type, model, and date of installation of the equipment 20. It's fine.

[0047] In addition, the insurance money calculation unit 105 compensates for the breakdown of the equipment 20 based on the following formula (6): The amount of insurance payment for the insurance may be calculated. The "manufacturer-published performance of equipment" and "degree of deterioration of equipment" values ​​are normalized values. By using formula (6), the insurance payment amount decreases as the equipment 20 deteriorates. do. Insurance payment amount = ("Facility manufacturer's published performance" - "Degree of deterioration of facility") x coefficient... (6)

[0048] <Summary> According to the embodiment described above, the information processing device 10 is The integrated value of the operating state value below the abnormality threshold is defined as the degree of deterioration of the equipment. This makes it possible to quantitatively grasp the degree of deterioration of the equipment 20, which progresses gradually. This makes it possible.

[0049] In addition, the information processing device 10 uses an abnormality threshold value to determine whether the operating state of the equipment 20 is abnormal. Normally, the operation status value is not constant while the equipment 20 is in operation. In this embodiment, the equipment 20 As long as the operating state does not fall below the abnormal threshold, the equipment 20 is determined to be operating normally. By doing so, the fluctuation in the operating state of equipment 20 when it is operating normally can be prevented from being mistakenly detected as abnormal. This makes it possible to eliminate the mistaken assumption that

[0050] In addition, the information processing device 10 uses the newly collected latest equipment operation data to Update the probability density distribution of the operating state value of 0 and update the abnormality threshold based on the updated probability density distribution. The processing capacity of facility 20 has been improved through maintenance, etc., and the design has been Equipment is replaced with new equipment due to equipment renovation, and equipment is expanded to improve processing capacity. Even in such a case, the abnormality threshold can be updated to a more appropriate value. It becomes possible to renew.

[0051] Conventional insurance products check whether there is equipment failure or accident, and then decide whether to pay insurance claims and whether to insure. Since the amount of insurance payment had already been decided, it took time to pay the insurance money. When considering insurance as an example of the embodiment of the present invention, the following is considered: This will allow the insurance company to determine the amount of insurance payment for equipment failures and accidents. This reduces the need to confirm whether there is a fault, and makes it possible to quickly determine the amount of insurance payment. .

[0052] The above-described embodiment is intended to facilitate understanding of the present invention and does not limit the present invention. The flowcharts, sequences, and implementations described in the embodiments are not intended to be interpreted as being related to the present invention. The elements of the embodiment, as well as their arrangement, materials, conditions, shapes, sizes, etc. are merely examples. The present invention is not limited to the above and may be modified as appropriate. The components may be partially substituted or combined. [Explanation of symbols]

[0053] 1 Management system, 10 Information processing device, 11 Processor, 12 Storage device, 13 Network IF (Network Interface), 14 Input device, 15 Output device, 20 Setting 101 Acquisition unit, 102 Extraction unit, 103 Calculation unit, 104 Determination unit, 105 Insurance Gold Calculation Department

Claims

1. An acquisition unit that acquires equipment operation data showing the time-series changes in the operating status values ​​of the equipment, An extraction unit extracts from the aforementioned equipment operation data the periods in which abnormalities occur during the evaluation period in which the operating status value is less than the abnormal threshold, A calculation unit that calculates the degree of deterioration of the equipment based on the difference between the abnormality threshold and the operating status value during the period in which the abnormality occurred, It has, The calculation unit calculates the degree of equipment deterioration by calculating the difference value during the period in which the abnormality occurred, and then calculating the value obtained during the period in which the abnormality occurred. Information processing device.

2. The calculation unit calculates the probability density of the operating state value from the equipment operating data over a predetermined period. The system includes a determination unit that determines the abnormal threshold value as the value at which the cumulative probability obtained by integrating the operating state value from a predetermined value to a maximum value with respect to the probability density becomes a predetermined probability. The information processing apparatus according to claim 1.

3. The determination unit updates the abnormal threshold using the equipment operation data for the predetermined period after the update. The information processing apparatus according to claim 2.

4. The system has an insurance payment calculation unit that calculates the amount of insurance payment by inputting the degree of deterioration and coefficient of the aforementioned equipment into a predetermined calculation formula. The information processing apparatus according to claim 1.

5. An information processing method performed by an information processing device, The steps include acquiring equipment operation data that shows the time-series changes in the operating status values ​​of the equipment, From the aforementioned equipment operation data, the steps include extracting the period during which the operating status value is below the abnormal threshold during the evaluation period in which abnormalities occurred, A step of calculating the degree of deterioration of the equipment based on the difference between the abnormality threshold and the operating status value during the period in which the abnormality occurred, Includes, The calculation step involves calculating the degree of equipment deterioration by taking the difference value during the period in which the abnormality occurred and calculating the value obtained during the period in which the abnormality occurred. Information processing methods.

6. The steps include acquiring equipment operation data that shows the time-series changes in the operating status values ​​of the equipment, From the aforementioned equipment operation data, the steps include extracting the period during which the operating status value is below the abnormal threshold during the evaluation period in which abnormalities occurred, A step of calculating the degree of deterioration of the equipment based on the difference between the abnormality threshold and the operating status value during the period in which the abnormality occurred, Have the computer run it, The calculation step involves calculating the degree of equipment deterioration by taking the difference value during the period in which the abnormality occurred and calculating the value obtained during the period in which the abnormality occurred. program.

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