WO2016163008A1

WO2016163008A1 - Fault diagnostic device and fault diagnostic method

Info

Publication number: WO2016163008A1
Application number: PCT/JP2015/061138
Authority: WO
Inventors: 涼次朝倉; 玉置　研二
Original assignee: 株式会社日立製作所
Priority date: 2015-04-09
Filing date: 2015-04-09
Publication date: 2016-10-13
Also published as: JP6247777B2; JPWO2016163008A1

Abstract

The purpose of the present invention is to provide a technology which, using a smaller quantity of information which indicates the state of a device, estimates and presents a suitable emergency response. Provided is a fault diagnostic device which presents a emergency response for a fault which has occurred with another device, in which: device state history information which includes device state information which denotes a state of the device when a fault has occurred and a history of the device state information, and emergency response history information, in which an association is made with the emergency response carried out when the fault occurred with the device, are stored in a storage unit; and a control unit creates, for each device state information item, at least two diagnostic models for calculating the frequency of emergency responses, calculates, using the diagnostic models, indices which denote the suitability of the respective emergency responses for each of at least two device state information items, and combines at least two of the indices which denote the suitability of the emergency responses, thereby identifying and presenting the emergency response for the fault which has occurred with the other device.

Description

Abnormality diagnosis apparatus and abnormality diagnosis method

The present invention relates to an abnormality diagnosis device and an abnormality diagnosis method.

Patent Document 1 states that “a failure countermeasure support system that at least predicts failure of a computer device and provides improvement information, a maintenance department terminal for performing maintenance work of the computer device, and a failure that occurs in the computer device. The repair department terminal that takes in the information and the contents of the restoration work from the maintenance department terminal via the network, the failure information that is taken in the repair department terminal, the contents of the restoration work, and the repair performed in the repair department Using mining technology that captures information via the network and analyzes a large amount of data stored in the information, finds the correlation pattern between the items and outputs the necessary information. Analyzing correlation patterns related to failure information and recovery work content An improvement method analysis unit that finds out a prediction of a failure that will occur in the future and an improvement measure method that indicates an improvement measure that is required when the predicted failure occurs frequently, and the improvement measure method that is found by the improvement method analysis unit in the network A product management department terminal that plans improvement measures from the improvement measure method and transmits the contents of the improvement measures to the maintenance department terminal, and the improvement method analysis unit includes the failure information and And a database for mining that stores at least the failure information analyzed by the mining technique and the improvement countermeasure method, and stores the contents of the improvement measures implemented at the product management department terminal. Only when it is transmitted to the terminal and improved by the improvement measures implemented by the maintenance staff belonging to the maintenance department terminal. There is a description of a failure countermeasure support system characterized in that the data of the mining database is automatically updated based on a good countermeasure method and failure information to improve the analysis accuracy of the failure tendency in the computer device. . In addition, Patent Document 2 describes “an abnormality detection / diagnosis method for detecting an abnormality or a sign of a plant or equipment and diagnosing the plant or equipment, wherein the plant or equipment is targeted for data acquired from a plurality of sensors. An abnormality of the facility is detected, a keyword is extracted from maintenance history information associated with the abnormality of the plant or the facility, the extracted keyword, and a keyword defined for the abnormality acquired from the plurality of sensors, Is used to generate a diagnostic model of the plant or equipment, and the plant or equipment is diagnosed using the generated diagnostic model.

Japanese Patent No. 4796925 Japanese Patent No. 5439265

In the above technique, according to the method described in Patent Document 1, as the information indicating the state and characteristics of the device (hereinafter referred to as device state) in the past history is smaller, the event and countermeasure are appropriately applied from the accumulated information. It can be said that it is difficult to judge. The information indicating the state and characteristics of the target device for diagnosing abnormality includes a plurality of items such as usage time (elapsed time since introduction), type of abnormality, alarm code, and year of manufacture. For example, if each of these items can take 10 types of values, the combination of the usage time, the type of abnormality, the alarm code, and the value that can be taken by the manufacturing year is 10 to the 4th power, and all countermeasures are presented. To do so, at least 10 4th order history information is required. In reality, since there are many items that take 10 or more values, a larger number of history information is required.

Also, the method described in Patent Document 2 is a method of presenting countermeasure work using one item of a keyword indicating a device state calculated from a sensor and a diagnostic model. Therefore, it is difficult to present an appropriate countermeasure work that matches the state of the apparatus in consideration of a plurality of pieces of information. For example, it is difficult to present an appropriate countermeasure work in consideration of the time of failure (initial failure period, wear failure period, etc., and a keyword indicating the device state calculated from the sensor.

An object of the present invention is to provide a technique for estimating and presenting appropriate countermeasure work using information indicating a smaller apparatus state.

The present application includes a plurality of means for solving at least a part of the above-described problems, and examples thereof are as follows. In order to solve the above problems, an abnormality diagnosis apparatus according to the present invention is an abnormality diagnosis apparatus that presents a countermeasure work for an abnormality that has occurred in another apparatus, and the storage unit indicates the state of the apparatus when the abnormality occurs. Device state history information including device state information and device state information history, and countermeasure work history information in which countermeasure work performed when an abnormality occurs in the device are stored, and the control unit Create at least two diagnostic models for each item of device status information, and use the diagnostic model to calculate an index indicating the appropriateness of countermeasure work for each item of at least two device status information. By combining at least two indicators indicating the appropriateness of the countermeasure work, the countermeasure work for the abnormality occurring in another device is specified and presented.

According to the present invention, it is possible to estimate and present an appropriate countermeasure work using information indicating a smaller apparatus state. Problems, configurations, and effects other than those described above will be clarified by the following description of embodiments.

1 is a diagram showing an outline of an abnormality diagnosis system according to a first embodiment of the present invention. It is a figure which shows the data structure stored in a maintenance history data storage area. It is a figure which shows the data structure stored in a separate diagnostic item data storage area. It is a figure which shows the data structure stored in an apparatus state data storage area. It is a figure which shows the data structure stored in a qualitative diagnostic model data storage area. It is a figure which shows the data structure stored in another qualitative diagnostic model data storage area. It is a figure which shows the data structure stored in a quantitative diagnosis model data storage area. It is a figure which shows the data structure stored in a separate diagnostic process result data storage area. It is a figure which shows the data structure stored in the countermeasure work total frequency data storage area. It is a figure which shows the data structure stored in an integrated diagnostic process result data storage area. It is a figure which shows the hardware constitutions of an abnormality diagnosis apparatus. It is a figure which shows the operation | movement flow of the outline | summary of an abnormality diagnosis apparatus. It is a figure which shows the operation | movement flow of the diagnostic process of countermeasure work. It is a figure which shows the example of the input screen of an abnormality diagnosis process. It is a figure which shows the example of the output screen of an abnormality diagnosis process. It is a schematic diagram which shows distribution of the data regarding the usage time of an apparatus state item. It is a schematic diagram which shows distribution of the data regarding the usage time of an apparatus state item.

When an abnormality or failure (hereinafter referred to as "abnormality") occurs in the equipment in order to use factory manufacturing equipment, elevators, infrastructure equipment such as railway vehicles (hereinafter referred to as "equipment") at a high operating rate, etc. Therefore, it is necessary to quickly identify and implement appropriate countermeasure work that can resolve the abnormalities that have occurred. For this reason, as a method for identifying an appropriate countermeasure, record history information of countermeasure work performed in the past, and use this history information of countermeasure work and information indicating the device status at the time of a new abnormality to newly There has been proposed an abnormality diagnosis method that presents countermeasure work for an abnormality that has occurred.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. Note that components having the same function are denoted by the same reference symbols throughout the drawings for describing the embodiment, and the repetitive description thereof will be omitted.

Hereinafter, an abnormality diagnosis system 1 which is an example of an abnormality diagnosis system to which the first embodiment of the present invention is applied will be described with reference to the drawings.

FIG. 1 is a diagram showing an outline of an abnormality diagnosis system 1 according to the present invention. The abnormality diagnosis system 1 includes an abnormality diagnosis apparatus 10 that is communicably connected to the diagnosis target apparatus 1000 via a network 300. The abnormality diagnosis apparatus 10 includes a diagnosis unit 20, an input unit 30, an output unit 31, a communication IF unit 32, and a communication bus 33 that connects them. A user (such as a technician) uses the function of the abnormality diagnosis device 10 through operation of the input / output device connected to the input unit 30 and the output unit 31. The abnormality diagnosis apparatus 10 can be configured by a general computer (PC or the like), and implements a characteristic processing function (each processing unit of the abnormality diagnosis apparatus 10) by software program processing, for example.

The input device and the output device are connected to the input unit 30 and the output unit 31, respectively, and include an input device that accepts input on an input screen and an output device that outputs a diagnosis result or the like by a user operation. For example, the input device includes a keyboard and a mouse, and the output device includes a display, a printer, and the like. In this system, a graphical user interface (GUI) is configured and various information is displayed on the screen of the output device based on the processing of the input device and the calculation unit 21.

In the diagnosis unit 20, the calculation unit 21, the storage unit 22, and the IF unit 211 are connected to each other. The calculation unit 21 stores maintenance history data stored in the maintenance history data storage area 223 of the various storage units 22, individual diagnosis item data stored in the individual diagnosis item data storage area 224, and device status data storage area 225. The countermeasure operation is estimated using the stored apparatus state data, and a process of presenting is performed. Details of the diagnostic processing performed by the calculation unit 21 will be described later.

The storage unit 22 includes, for example, known elements such as an HDD (Hard Disk Drive) and an SSD (Solid State Drive). The storage unit 22 identifies a history of countermeasure work performed when a past abnormality has occurred, a maintenance history data storage area 223 for storing a history of the device state at the time of the occurrence of the abnormality, and a device state item used for estimating the countermeasure work An individual diagnosis item data storage area 224 for storing information to be stored, an apparatus state data storage area 225 for storing the state of the apparatus to be subjected to abnormality diagnosis, and a first diagnosis model ( A qualitative diagnosis model data storage area 226 for storing a qualitative diagnosis model), and a quantitative diagnosis model data storage area 227 for storing a second diagnosis model (quantitative diagnosis model) created by the individual diagnosis processing described later. And an individual diagnosis processing result data storage area 228 for storing an index indicating the appropriateness of countermeasure work calculated in the individual diagnosis processing described later, and an integrated diagnosis processing described later. That includes a countermeasure work total frequency data storage area 229, the integrated diagnostic processing result data storage area 230 for storing the information for estimating the measures work calculated by integrating the diagnostic process to be described later, the.

The storage unit 22 may be provided in the network 300 or another device connected via a network (not shown), and the calculation unit 21 may access information stored in the storage unit 22 via communication. .

The IF unit 211 is responsible for input / output interface control performed in the diagnosis unit 20.

The communication IF unit 32 performs communication with one or a plurality of diagnosis target apparatuses 1000 that are other apparatuses via the network 300. The network 300 may be any of various networks such as the Internet, a LAN (Local Area Network), a WAN (Wide Area Network), a mobile phone network, and a wireless communication network.

FIG. 2 is a diagram showing a data structure stored in the maintenance history data storage area 223. In the maintenance history data storage area 223, the history of countermeasure work performed when a failure has occurred in the diagnosis target device 1000 or the same type of device as the diagnosis target device 1000 and the history of the device state at the time of the failure are specified. Information to be stored is stored.

The maintenance history data storage area 223 includes a history ID 223a, a device status item 223b, and a countermeasure work item 223c.

The history ID 223a stores information for identifying countermeasure work performed in the past. For example,

natural numbers

1, 2, 3,... Consecutive values are stored in the order of storage.

In the device status item 223b, information for specifying the device status at the time of occurrence of a past abnormality and the characteristics of the device in which the abnormality has occurred is stored. In general, the information stored includes the type of abnormality (abnormality type), the alarm code issued by the device (alarm code), the result of inspecting the sensor measurement value of the device, and the result of inspecting the device with inspection equipment (current) Check), accumulated operating time (usage time) of the device, information on the manufacture of the device (year of manufacture), sensor measurement values of the device, measurement values when the device is measured with a measuring instrument (current measurement values), etc. . However, the present invention is not limited to this, and there may be a plurality of device status items corresponding to the diagnosis target device 1000 or the type of the diagnosis target device 1000.

In the countermeasure work item 223c, information for identifying the countermeasure work performed when a past abnormality has occurred is stored. The stored information includes at least one of a countermeasure location indicating the location and part of the device to which the countermeasure has been taken, and a countermeasure content indicating replacement or repair of the component. In the present embodiment, it is assumed that countermeasure points are included.

Note that each record in the maintenance history data storage area 223 indicates data when an abnormality occurs once, and therefore, data included in the same record is associated with each other. For example, in the first line (first record), in the event that an abnormality has occurred in the diagnosis target device 1000 or the same type of device as the diagnosis target device 1000 in the past, the diagnosis target device 1000 includes the first item of the device state item 223b. This indicates that the apparatus is in the device state specified by the information stored in the first line and the countermeasure work specified by the information stored in the first line of the countermeasure work item 223c has been performed. It should be noted that the information stored in the countermeasure work item 223c is preferably stored only for the countermeasure work that has solved the abnormality, but includes the countermeasure work that could not solve the abnormality and the unclear countermeasure work that could have solved the abnormality. It may be.

The information stored in the device status item 223b is data output from the diagnosis target device 1000 or information input by an operator. The information stored in the countermeasure work item 223c is information specified and confirmed by the worker after the actual work. When a new abnormality occurs, if the operator performs countermeasure work, information on the newly generated abnormality and countermeasures are added to the maintenance history data storage area 223, and know-how is further accumulated. It can be said. Details of the processing will be described later.

Note that the information stored in the device status item 223b may be a specific part of the data output from the diagnosis target device 1000. For example, only the sentence head (eg, A001) of the alarm code (eg: A001-11) may be stored.

FIG. 3 is a diagram showing a data structure stored in the individual diagnostic item data storage area 224. As shown in FIG. The individual diagnosis item data storage area 224 stores information for specifying an apparatus state item used for estimation of countermeasure work in an individual diagnosis process described later.

The individual diagnosis item data storage area 224 includes an individual diagnosis item ID 224a, an individual diagnosis item 224b, and an item type 224c.

In the individual diagnosis item ID 224a, information specifying a combination of the individual diagnosis item 224b and the information stored in the item type 224c is stored. For example, the natural

diagnostic numbers

1, 2, 3,... Are stored in order from the oldest stored combination of the individual diagnosis item 224b and the item type 224c.

In the individual diagnosis item 224b, information for specifying an item of an apparatus state used for creating a diagnosis model in an individual diagnosis process described later is stored. For example, the individual diagnosis item 224b stores information for specifying any item of the device status item 223b in the maintenance history data storage area 223. In the individual diagnosis process described later, for each record stored in the maintenance history data storage area 223, the value of the device status item 223b specified by the information stored in the individual diagnosis item 224b, the value of the countermeasure work item 223c, , A diagnostic model is created and used for estimation of countermeasure work.

The item type 224c stores information specifying the type of information stored in the device status item 223b of the maintenance history data storage area 223 specified by the individual diagnosis item 224b. For example, a symbol indicating one of a “qualitative” item type indicating a qualitative variable such as a character string and a “quantitative” item type indicating a continuous variable such as a numerical value is stored. In the individual diagnosis processing described later, it is used to select a diagnosis model to be created according to the distinction between qualitative variables and quantitative variables according to the information stored here.

In the individual diagnosis item data storage area 224, information given in advance by a designer or the like is stored. The individual diagnosis item 224b may store information for designating a plurality of device state items 223b as illustrated in the row (record) where the individual diagnosis item ID 224a is “2”.

FIG. 4 is a diagram showing a data structure stored in the device state data storage area 225. As shown in FIG. The device state data storage area 225 stores information for specifying the state of the diagnosis target device 1000 in which a new abnormality for diagnosis has occurred.

The device status data storage area 225 includes a device status item 225a at the time of new abnormality. The device status item 225a at the time of new abnormality is an item corresponding to the device status item 223b in the maintenance history data storage area 223. The information stored in the device state item 225a at the time of a new abnormality includes the type of abnormality (abnormality type), the alarm code (alarm code) issued by the device, and the sensor measurement value of the device, as in the device state item 223b. The result of the inspection and the result of inspecting the device with the inspection equipment (current check), the cumulative operating time (usage time) of the device, the information on the manufacture of the device (the year of manufacture), and the device sensor measurement value and measuring instrument Measured value (current measured value), etc. are measured. However, the present invention is not limited to this, and there may be a plurality of items of the device state corresponding to the diagnosis target device 1000 or the type of the diagnosis target device 1000.

Before performing the diagnosis process by the calculation unit 21, information is stored in the apparatus state data storage area 225 by the operator via the input unit 30. Alternatively, the calculation unit 21 stores information by reading data output from the diagnosis target device 1000 via the network 300 into the device state data storage area 225 in response to an instruction from the operator. Also good. Note that the information stored in the device status item 225a at the time of a new abnormality may be a specific part of the data output from the diagnosis target device 1000. For example, only the sentence head (eg A001) of the alarm code (eg A001-11) may be stored.

The information stored in the device state data storage area 225 is added to the maintenance history data storage area 223 after the operator performs countermeasure work. Details of this processing will also be described later.

FIG. 5 is a diagram showing a data structure stored in the qualitative diagnosis model data storage area 226. In particular, the model data stored in the qualitative diagnosis model data storage area 226 is a qualitative diagnosis in which one item of the device state item 223b specified in the individual diagnosis item 224b of the individual diagnosis item data storage area 224 is a diagnosis item. Model, in other words, the first diagnostic model. The qualitative diagnosis model data storage area 226 includes an individual diagnosis item 226a, a combination frequency 226b of countermeasure work items (countermeasure points), and a combination frequency total 226c.

In the individual diagnosis item 226a, information specifying the type of information stored in the device status item 223b specified by the information stored in the individual diagnosis item 224b is stored.

The combination frequency 226b with the countermeasure work item (countermeasure location) includes the combination frequency of the information stored in the device status item 223b and the information stored in the countermeasure work item 223c (the number of occurrences of events solved by the combination). ) Is stored. The combination frequency 226b with the countermeasure work item (countermeasure location) includes a plurality of items, and each item is stored in the countermeasure work item 223c or information indicating the countermeasure work stored in the countermeasure work item 223c. This item corresponds to information indicating countermeasure work that may be performed. These items may be automatically created by searching the information stored in the countermeasure work item 223c, or may be defined in advance and expanded and changed in a timely manner. In the present embodiment, the combination frequency 226b with the countermeasure work item (countermeasure location) stores “1” as an initial value for convenience of frequency calculation described later. A value may be stored as an initial value.

The combination frequency total 226c stores information that identifies the sum of each line of information stored in the combination frequency 226b with the countermeasure work item (countermeasure location). Thus, it can be said that the qualitative diagnosis model data storage area 226 stores the first diagnosis model representing the frequency of implementation of countermeasure work in a predetermined device state for each item of the device state information.

FIG. 6 is a diagram showing a data structure stored in another qualitative diagnostic model data storage area 226 ′. In particular, the model data stored in another qualitative diagnosis model data storage area 226 ′ includes two or more items of the device state item 223 b specified in the individual diagnosis item 224 b of the individual diagnosis item data storage area 224 as diagnosis items. Is a qualitative diagnostic model, in other words, another first diagnostic model. Another qualitative diagnosis model data storage area 226 ′ includes an individual diagnosis item 226d, a combination frequency 226b of countermeasure work items (measurement points), and a combination frequency total 226c.

The individual diagnosis item 226d stores information for specifying a plurality of types of information stored in the device status item 223b specified by the information stored in the individual diagnosis item 224b.

In the present embodiment, the first diagnosis model, that is, the qualitative diagnosis model data storage area 226 and another qualitative diagnosis model data storage area 226 ′ are created after an instruction to start the abnormality diagnosis process is issued. However, the present invention is not limited to such a configuration, and it may be created at a regular timing regardless of whether the abnormality diagnosis is instructed or not.

FIG. 7 is a diagram showing a data structure stored in the quantitative diagnosis model data storage area 227. In particular, the model data stored in the quantitative diagnosis model data storage area 227 is a quantitative diagnosis model, in other words, a second diagnosis model. The quantitative diagnosis model data storage area 227 includes a neighborhood frequency 227a and a neighborhood frequency total 227b of countermeasure work items (countermeasure locations).

In the neighborhood frequency 227a of the countermeasure work item (countermeasure location), information stored in the item of the device status item 225a at the time of new abnormality specified by the information stored in the individual diagnosis item 224b according to the item to be diagnosed, The information stored in the corresponding item of the device status item 223b and the information specifying the number of data (neighboring frequency) that are close to each other are stored. The neighborhood frequency 227a of countermeasure work items (countermeasure locations) includes a plurality of items. Each item is an item corresponding to information indicating countermeasure work stored in the countermeasure work item 223c or information indicating countermeasure work that may be stored in the countermeasure work item 223c. These items may be automatically created by searching the information stored in the countermeasure work item 223c, or may be defined in advance and expanded and changed in a timely manner. In the present embodiment, “1” is stored as an initial value in the vicinity frequency 227a of the countermeasure work item (countermeasure location) for convenience of frequency calculation described later, but other values are used as initial values. It may be stored.

In the neighborhood frequency total 227b, information specifying the sum of information stored in each item of the neighborhood frequency 227a of the countermeasure work item (countermeasure location) is stored.

FIG. 8 is a diagram showing a data structure stored in the individual diagnosis processing result data storage area 228. The individual diagnosis processing result data storage area 228 stores the ratio of countermeasure work items associated with individual diagnosis items. That is, for each individual diagnosis item, the results of taking measures are stored as a ratio for each place where measures were taken.

The individual diagnosis processing result data storage area 228 includes an individual diagnosis item ID 228a and a ratio 228b of countermeasure work items (countermeasure points).

In the individual diagnosis item ID 228a, information associated with the individual diagnosis item ID 224a in the individual diagnosis item data storage area 224 is stored. In the ratio 228b of countermeasure work items (countermeasure points), the ratio of the number of cases for which countermeasures have been taken regarding the individual diagnosis item ID 228a is stored for each item of countermeasure points. Specifically, for each item associated with the countermeasure work item 223c in the maintenance history data storage area 223, it is stored as a ratio of the number of implementations.

FIG. 9 is a diagram showing a data structure stored in the countermeasure work total frequency data storage area 229. The total countermeasure work frequency data storage area 229 stores the total frequency 229a of the countermeasure work items (countermeasure points) and the ratio of the countermeasure work items associated with the individual diagnosis items. That is, the results of taking countermeasures are stored as a ratio for each place where countermeasures were taken.

The countermeasure work total frequency data storage area 229 includes a total frequency 229a of countermeasure work items (countermeasure points) and a total frequency total 229b.

In the total frequency 229a of the countermeasure work item (countermeasure location), information for specifying the number of pieces of information data (total frequency) stored in the item of the device status item 223b is stored. Note that the total frequency 229a of countermeasure work items (countermeasure points) includes a plurality of items. Each item is an item corresponding to information indicating countermeasure work stored in the countermeasure work item 223c or information indicating countermeasure work that may be stored in the countermeasure work item 223c. These items may be automatically created by searching the information stored in the countermeasure work item 223c, or may be defined in advance and expanded and changed in a timely manner. In the present embodiment, the total frequency 229a of countermeasure work items (countermeasure points) stores “1” as an initial value for convenience of frequency calculation described later, but other values are used as initial values. It may be stored.

In the total frequency total 229b, information specifying the sum of the information stored in each item of the total frequency 229a of the countermeasure work item (countermeasure part) is stored.

FIG. 10 is a diagram showing a data structure stored in the integrated diagnosis processing result data storage area 230. As shown in FIG. The integrated diagnosis processing result data storage area 230 includes an integrated diagnosis processing result 230a of countermeasure work items (countermeasure points) and a processing result total 230b.

In the integrated diagnosis processing result 230a of the countermeasure work item (countermeasure location), information specifying the result of calculating the product of the individual diagnosis processing result data storage area 228 and the information stored in the countermeasure work total frequency data storage area 229 Is stored. The integrated diagnosis processing result 230a of countermeasure work items (countermeasure points) includes a plurality of items. Each item is an item corresponding to information indicating countermeasure work stored in the countermeasure work item 223c or information indicating countermeasure work that may be stored in the countermeasure work item 223c. These items may be automatically created by searching the information stored in the countermeasure work item 223c, or may be defined in advance and expanded and changed in a timely manner. In the present embodiment, the integrated diagnosis processing result 230a of the countermeasure work item (countermeasure point) includes the ratio 228b of the countermeasure work item (countermeasure point) and the countermeasure work item (countermeasure point) in the countermeasure work total frequency data storage area 229. ) To match each item of the total frequency 229a. For example, when the first item of the ratio 228b of the countermeasure work item (countermeasure part) and the total frequency 229a of the countermeasure work item (countermeasure part) similarly indicates “bearing”, the integrated diagnosis of the countermeasure work item (countermeasure part) Similarly, the first item of the processing result 230a indicates “bearing”.

In the processing result total 230b, information specifying the sum of the information stored in each item of the integrated diagnosis processing result 230a of the countermeasure work item (measurement location) is stored.

FIG. 11 is a diagram illustrating a hardware configuration of the abnormality diagnosis apparatus 10. The abnormality diagnosis device 10 is typically a personal computer device, but is not limited thereto, and may be a smart phone, a mobile phone terminal, or an electronic information terminal such as a PDA (Personal Digital Assistant).

The abnormality diagnosis apparatus 10 includes an arithmetic device such as a CPU (Central Processing Unit) 111, a main storage device such as a memory 112, an external storage device 113 such as a hard disk (Hard Disk Drive) or SSD (Solid State Drive), and a CD. (Compact Disk) or DVD (Digital Versatile Disk) or other portable storage medium 114D for reading / writing electronic data 114, an input device 115 such as a keyboard or mouse, and an output device 116 such as a display or printer. And a communication device 117 such as NIC (Network Interface Card) and a bus connecting them.

The communication device 117 is a wired communication device that performs wired communication via a network cable, or a wireless communication device that performs wireless communication via an antenna. The communication device 117 performs communication with other devices connected to the network.

The arithmetic device is, for example, the CPU 111. The main storage device is a memory 112 such as a RAM (Random Access Memory). The external storage device 113 is a non-volatile storage device such as a so-called hard disk, SSD, or flash memory that can store digital information.

The input device 115 is a device that receives input information including a pointing device such as a keyboard and a mouse, or a microphone that is a voice input device.

The output device 116 is a device that generates output information including a display, a printer, or a speaker that is an audio output device.

The arithmetic unit 21 described above is realized by a program that causes the CPU 111 to perform processing. This program is stored in the memory 112, the external storage device 113 or the portable storage medium 114D, loaded onto the memory 112 for execution, and executed by the CPU 111.

In addition, the storage unit 22 is realized by the memory 112 and the external storage device 113.

Further, the communication IF unit 32 is realized by the communication device 117. The input unit 30 and the output unit 31 are realized by the input device 115 and the output device 116, respectively.

The above is the hardware configuration example of the abnormality diagnosis device 10 of the abnormality diagnosis system 1 in the present embodiment. However, the configuration is not limited to this, and other hardware may be used. For example, the stand-alone abnormality diagnosis apparatus 10 that is not connected to a network may be used.

In addition, each storage area stored in the storage unit 22 may update information by crawling and collecting information stored in another server device connected to the network or an external storage device. However, it may be updated by receiving data from the supplier.

Although not shown, the abnormality diagnosis apparatus 10 has known elements such as an OS (Operating System), middleware, and applications, and particularly has an existing processing function for displaying a GUI screen on an input / output device such as a display. Prepare. The calculation unit 21 performs processing for drawing and displaying a predetermined screen using the above-described existing processing function, processing of data information input by the user via the screen, and the like.

[Description of Operation] Next, the operation of the abnormality diagnosis system 1 in this embodiment will be described.

FIG. 12 is a diagram showing a general operation flow performed by the abnormality diagnosis device 10 in the present embodiment. The overall operation flow starts when an abnormality diagnosis processing start instruction is received from a user (operator) while the abnormality diagnosis device 10 is activated (step S101).

The calculation unit 21 of the abnormality diagnosis apparatus 10 performs a countermeasure work diagnosis process (step S102). Specifically, the arithmetic unit 21 of the abnormality diagnosis apparatus 10 performs a countermeasure work diagnosis process described later.

The worker performs countermeasure work (step S103). Specifically, the worker applies the countermeasure work presented from the abnormality diagnosis apparatus 10 to the actual diagnosis target apparatus 1000 to perform the countermeasure work.

When the worker completes the countermeasure work, the worker inputs the result (step S104). Specifically, the worker delivers input information to the abnormality diagnosis apparatus 10 as to which countermeasure work has been performed among the presented countermeasure work.

The abnormality diagnosis apparatus 10 performs maintenance history data accumulation processing (step S105). Specifically, the abnormality diagnosis apparatus 10 receives an input as to which of the countermeasure work presented in the countermeasure work presented in the diagnosis process of the countermeasure work and associates it with an event as maintenance history data in the storage unit 22. Store.

The above is the overall operation flow. By executing the entire operation flow, the operator can see the result of the abnormality diagnosis, carry out the countermeasure work if necessary and record the result. Also, by taking a record, information on measures that should contribute to more accurate abnormality diagnosis can be accumulated.

FIG. 13 is a process flow diagram of the countermeasure work diagnosis process. The countermeasure work diagnosis process is started when a process start instruction is received from the user in a state where the abnormality diagnosis apparatus 10 is activated.

In the diagnosis process of the countermeasure work in the present embodiment, an individual diagnosis process for calculating an index indicating the appropriateness of the countermeasure work for each information item indicating the apparatus state or for each combination of information items indicating the apparatus state; An integrated diagnosis process is performed in which an appropriate measure work is calculated by combining indexes indicating the appropriateness of the measure work calculated in the diagnosis process.

In summary, the process of step S200 is a process for storing data used in the individual diagnosis process and the integrated diagnosis process, and each process from step S201 to step S206 corresponds to the individual diagnosis process. To S209 corresponds to the integrated diagnosis process.

In the individual diagnosis process, the calculation unit 21 uses the information stored in the individual diagnosis item data storage area 224 to perform a first qualitative diagnosis for each item indicating the device state included in the individual diagnosis item 224b. A diagnostic model or a second diagnostic model for quantitative diagnosis is created (step S201, step S202, step S204), and each countermeasure work is used as an index indicating the appropriateness of the countermeasure work using the created diagnostic model. Is performed, and the calculated ratio is stored in the individual diagnosis processing result data storage area 228 (steps S203 and S205). In addition, the calculation unit 21 performs a process of creating a diagnostic model and storing a ratio that is an index indicating appropriateness in the individual diagnosis processing result data storage area 28 for all the individual diagnosis items stored in the individual diagnosis item data storage area 224. Information on the diagnosis item 224b is performed (step S206).

In the integrated diagnosis process, the calculation unit 21 calculates the ratio of countermeasure work in the entire maintenance history data storage area 223 (step S207), and sets values indicating a combination of measures indicating appropriateness of the countermeasure work as steps S203, S205, The product of the ratio of the countermeasure work calculated in step S207 is calculated (step S208), and the countermeasure work having a large ratio product is presented as an estimation result (step S209).

First, the calculation unit 21 stores data indicating the device state (step S200). Specifically, when the information indicating the device state is input to the device state input field 401 on the input screen 400 illustrated in FIG. 14 and the operation unit 21 detects that the abnormality diagnosis execution instruction button 402 is pressed, Data indicating the state is stored in the device state data storage area 225.

The information for accepting input in the device status input field 401 is associated with the device status item 225a at the time of new abnormality in the device status data storage area 225, and the calculation unit 21 sets the input data to the corresponding items. Store.

It should be noted that part or all of the information for accepting input in the device status input field 401 may be data output from the diagnosis target device 1000 via the network 300. Further, the device status input field 401 may include an item for which information is not input. The input screen 400 will be described later.

Next, the computing unit 21 determines whether or not the i-th (i is a natural number) diagnostic item is a qualitative variable (step S201). Specifically, the calculation unit 21 determines the type of information (qualitative variable or quantitative variable) for the information stored in the individual diagnosis item 224b in the i-th row (i is a natural number) of the individual diagnosis item data storage area 224. ) Using the information of the item type 224c of the corresponding record.

When the type of information is “qualitative” indicating a qualitative variable (in the case of “Yes” in step S201), the calculation unit 21 determines the first diagnostic model for the i-th individual diagnostic item. Is created (step S202). Specifically, the calculation unit 21 creates a first diagnosis model for the qualitative variable for information stored in the i-th row of the individual diagnosis item 224b in the individual diagnosis item data storage area 224, The qualitative diagnosis model data storage area 226 is stored.

And the calculating part 21 calculates the ratio of the combination frequency for every countermeasure work (step S203). Specifically, the computing unit 21 identifies the column of the device status item 223b based on the information of the item stored in the i-th row of the individual diagnosis item 224b (hereinafter, the column identified in step S202 is The frequency for each combination of the information stored in the specific column of the device status item 223b and the information stored in the specific column of the device status item 223b and the information stored in the countermeasure work item 223c is expressed as the first diagnostic model ( Qualitative diagnosis model).

Regarding the calculation of the first diagnostic model, different models are used for the case where the specific column is one column, that is, only one item, and the case where there are a plurality of columns, that is, a plurality of items, and different calculation methods are taken. FIG. 5 and FIG. 6 show respective configuration examples of the qualitative diagnostic model data storage area 226 and another qualitative diagnostic model data storage area 226 ′.

For the qualitative diagnosis model data storage area 226, the individual diagnosis item 226a consists of one item, and for the qualitative diagnosis model data storage area 226 ′, the individual diagnosis item 226d consists of two or more items, For the diagnostic item 226d, the total combination frequency is calculated for each combination of items.

Regarding the qualitative diagnosis model data storage area 226, the calculation unit 21 reads information stored in a specific column (eg, abnormality type) of the device state item 223b in order from the first row in the process of step S202, and performs individual diagnosis items. If the information is not stored in 226a, the information is created by adding it to the individual diagnosis item 226a. A list of information stored in the specific column of the device status item 223b may be created in advance and used as data of the individual diagnosis item 226a.

In addition, the calculation unit 21 reads and stores a combination of information stored in the column of the device status item 223b and information stored in the countermeasure work item 223c in order from the first row of the maintenance history data storage area 223. A process of adding 1 to the combination frequency total 226c specified by the information combination as a value indicating the frequency of the combination (counting up) is performed. The computing unit 21 performs this value addition processing up to the last row of the maintenance history data storage area 223, that is, all records stored in the maintenance history data storage area 223.

In addition, the calculating part 21 is good also as a structure which does not perform a count-up process about all the cases of the maintenance history data storage area 223, but a process which starts a process from the middle line, or a process which complete | finishes a process in the middle line.

Further, in a row of the maintenance history data storage area 223, an item relating to a combination of information stored in the specific column of the device status item 223b and information stored in the countermeasure work item 223c is stored in the qualitative diagnosis model data storage. When the data does not exist in the area 226, or when the data of the specific column of the device status item 223b or the countermeasure work item 223c is missing (when no data is stored), the combination frequency may not be counted up. .

In addition, for each individual diagnosis item 226a, the calculation unit 21 calculates the sum of the stored values for the combination frequency 226b with the countermeasure work item (countermeasure location I), and stores the sum in the combination frequency total 226c.

For another qualitative diagnostic model data storage area 226 ′, the calculation unit 21 uses the information stored in the specific column (eg, two columns of alarm code and current check) of the device status item 223b in the process of step S202. If the information is read in order from the first line and is not stored in the individual diagnostic item 226d, the information is created by adding to the individual diagnostic item 226d. A list of information stored in the specific column of the device status item 223b may be created in advance and used as data for the individual diagnosis item 226d.

Further, the calculation unit 21 reads and stores a combination of information stored in the column of the device status item 223b and a combination of information stored in the countermeasure work item 223c in order from the first row of the maintenance history data storage area 223. A process of adding 1 (counting up) as a value indicating the frequency of the combination to the total combination frequency 226c specified by the combination of information performed is performed. The computing unit 21 performs this value addition processing up to the last row of the maintenance history data storage area 223, that is, all records stored in the maintenance history data storage area 223.

In addition, in a row of the maintenance history data storage area 223, items related to the combination of the information stored in the specific column of the device status item 223b and the information stored in the countermeasure work item 223c are different qualitative items. When the diagnosis model data storage area 226 ′ does not exist, or when the combination of the specific column of the device state item 223b or the data of the countermeasure work item 223c is missing (when data is not stored), the combination frequency is set. It is also possible not to count up.

In addition, for each individual diagnosis item 226d, the calculation unit 21 calculates the sum of the stored values for the combination frequency 226b with the countermeasure work item (measure point I), and stores the sum in the combination frequency total 226c.

In the present embodiment, the first diagnostic model is created after the abnormality diagnosis process is instructed. However, the first diagnostic model is not limited to such a configuration, and is created at a regular timing before the abnormality diagnosis is instructed. Anyway.

And the calculating part 21 calculates the ratio of the combination frequency for every countermeasure work (step S203). Specifically, the calculation unit 21 uses the information stored in the qualitative diagnosis model data storage area 226 or another qualitative diagnosis model data storage area 226 ′ for each countermeasure work in the apparatus state at the time of new abnormality. The ratio of the combination frequency is calculated as an index indicating the appropriateness of the countermeasure work, and is stored in the individual diagnosis processing result data storage area 228.

Then, the computing unit 21 specifies the item (one or a plurality of items) of the device state item 225a at the time of the new abnormality in the device state data storage area 225 using the information stored in the i-th row of the individual diagnosis item 224b. And get the information stored in that column. The computing unit 21 describes the acquired information as a device state value at the time of new abnormality.

When there is one item specified by the individual diagnosis item 224b, the calculation unit 21 specifies a record that matches the device state value at the time of new abnormality for the individual diagnosis item 226a in the qualitative diagnosis model data storage area 226. (Example: Identify the line of “abnormal noise”).

Further, the calculation unit 21 divides the value stored in the specified record for each item of the combination frequency 226b with the countermeasure work item (countermeasure location) by the value stored in the record of the combination frequency total 226c. To calculate the combination frequency ratio. Then, the computing unit 21 stores the calculated combination frequency ratio in the individual diagnosis processing result data storage area 228 as an index indicating the appropriateness of the countermeasure work.

When there is no record in the individual diagnosis item 226a that matches the device status value at the time of a new abnormality, the index indicating the appropriateness of the countermeasure work is the same value (for example, 1) for all the countermeasure works. Are stored in the individual diagnosis processing result data storage area 228.

Note that the ratio 228b of countermeasure work items (countermeasure items) in the individual diagnosis processing result data storage area 228 includes the ratio of the combination frequency for each countermeasure work calculated in step S203 or the countermeasure calculated in step S205 described later. Information for specifying the ratio of the neighborhood frequency for each work is stored.

Here, the value of the calculated combination frequency ratio indicates the ratio of the countermeasure work that has been able to resolve the past abnormality that occurred in the device state that matches the new abnormality. If the device states match, there is a high possibility that the abnormality can be solved by the same countermeasure, and therefore the magnitude of the ratio value can be said to be an index representing the appropriateness of the countermeasure work.

When there are a plurality of items specified by the individual diagnosis item 224b, the calculation unit 21 performs the same processing using another qualitative diagnosis model data storage area 226 ′, calculates the combination frequency ratio, Stored in the work item (measure item) ratio 228b.

The information in the individual diagnosis processing result data storage area 228 in which information is stored in this way is used in the process of step S208 of the integrated diagnosis process described later.

When the type of information stored in the i-th row of the item type 224c of the individual diagnosis item data storage area 224 is “quantitative” indicating a quantitative variable (in the case of “No” in step S201). The computing unit 21 creates a second diagnostic model for the i-th individual diagnostic item (step S204). Specifically, the calculation unit 21 creates a second diagnostic model for the quantitative variable using information stored in the i-th record of the individual diagnostic item 224b, and stores the quantitative diagnostic model data. Store in area 227.

And the calculating part 21 calculates the ratio of the neighborhood frequency for every countermeasure work (step S205). Specifically, the calculation unit 21 determines the column (specific column) of the device status item 223b in the maintenance history data storage area 223 and the device status data based on the item information stored in the i-th row of the individual diagnosis item 224b. The column of the device state item 225a at the time of the new abnormality in the storage area 225 is specified, and the information stored in the specific column of the device state item 223b and the column of the device state item 225a at the time of the new abnormality are stored Using the distance to the information, the frequency (neighbor frequency) for each countermeasure operation is calculated as the second diagnostic model.

For example, in the process of step S204, the calculation unit 21 reads information stored in a specific column (eg, usage time) of the device status item 225a at the time of new abnormality (the read information is hereinafter referred to as “d1”). The computing unit 21 identifies k (k is a natural number) records in order from the smallest distance (absolute value of the difference in value) between the information stored in the specific column of the device state item 223b and d1. . Note that k is a predetermined value and takes a value such as 10, for example. Further, a predetermined ratio with respect to the number of records of maintenance history data stored in the maintenance history data storage area 223 (for example, 10% of the number of records of data) may be set as the value of k.

FIG. 16 is a schematic diagram showing the distribution of data related to the usage time of the device status item. FIG. 16 is used as an example to illustrate the concept of processing for specifying k neighboring records. It can be seen that k (k = 5 in FIG. 16) items are specified in order from the data with the smallest distance between d1 and the stored information.

The calculation unit 21 acquires information stored in the countermeasure work item 223c for the k records specified here, and matches the acquired information and each item of the neighborhood frequency 227a of the countermeasure work item (countermeasure location). If there is something to do, the number of data is added (counted up) to the matched item. By this processing, the number of countermeasure work that can resolve a past abnormality that occurred in a device state similar to a new abnormality can be acquired.

Note that the calculation unit 21 may specify a range of nearby values so as to identify a record within a predetermined distance (eg, 500) from d1 instead of identifying the k nearby records. good. Alternatively, by comparing the distance between the device status information and the information obtained by removing the device status information from the device status history information, the countermeasure work performed when the device status history information is closer than the predetermined value to the device status information. A second diagnostic model indicating the frequency of implementation may be created using countermeasure work history information.

In addition, the calculation unit 21 stores the information stored in the plurality of specific columns of the device state item 223b and the plurality of specified columns of the device state item 225a at the time of new abnormality by using a formula for calculating the Euclidean distance. The distance from the recorded information may be calculated to specify k records.

The information stored in the specific column of the device status item 223b is a numerical value as long as the distance between the information stored in the device status item 225a and the device status item 223b at the time of new abnormality can be defined. Not limited to this, it may be data such as text, images, moving images, and voices.

For example, for image data such as thermography, the distance between image data can be calculated using information on the frequency of pixels that can be calculated for each image data. Therefore, if the image data is stored in the maintenance history data storage area 223 so as to correspond to the countermeasure work, the calculation unit 21 calculates a distance from the newly captured image data, and the image data with a short distance is calculated. By calculating the number of countermeasure work for, information on the neighborhood frequency can be calculated. The same calculation can be performed for moving image data if the moving image data is cut out and handled as a still image.

Also, for text data such as work reports, if the number of matching words is calculated for words included in stored text data and words included in text data newly created by the worker, The distance between data can be calculated. Therefore, if the text data is stored in the maintenance history data storage area 223 so as to correspond to the countermeasure work, the calculation unit 21 calculates the distance between the newly input text and the text data with a short distance. By calculating the number of countermeasure work for, information on the neighborhood frequency can be calculated. The same calculation can be performed by once converting voice data into a character string.

Also, the frequency of counting according to the distance may be weighted, for example, the frequency of the record in the maintenance history data storage area 223 that is closer to d1 is counted more frequently.

Then, the calculation unit 21 uses the information stored in the quantitative diagnosis model data storage area 227 to calculate the neighborhood frequency ratio for each countermeasure work as an index indicating the appropriateness of the countermeasure work, and the individual diagnosis processing result data Store in the storage area 228.

The calculation unit 21 acquires the value stored in each item of the neighborhood frequency 227a of the countermeasure work item (measure location), and divides the acquired value by the information stored in the neighborhood frequency total 227b, thereby calculating the neighborhood frequency. Calculate the ratio. The computing unit 21 specifies the calculated ratio of the neighborhood frequencies as an index indicating the appropriateness of the countermeasure work by the individual diagnosis item ID 228a of the ratio 228b of the individual countermeasure work items (countermeasure points) in the individual diagnosis processing result data storage area 228. Stores so that columns correspond to the rows.

Similar to the description in the first diagnosis model, the value of the neighborhood frequency ratio calculated here also indicates the ratio of the countermeasure work that has been able to resolve the past abnormality that occurred in the device state similar to the new abnormality. It can be said. If the apparatus states are similar, there is a high possibility that an abnormality can be solved by the same countermeasure. Therefore, the magnitude of the value of the neighborhood frequency ratio is an index indicating the appropriateness of the countermeasure work.

Of course, even if it is a quantitative variable, it can be changed to a qualitative variable, and the combination frequency can be calculated by the first diagnostic model. For example, if a section of a quantitative variable is defined so that a value of usage time of 3000 or more and less than 4000 is assigned to a qualitative variable of “3000 units”, it can be handled as a qualitative variable.

However, if a section is defined in advance, a past maintenance history similar to the device status at the time of a new abnormality may not be specified. Such an example is shown in FIG.

FIG. 17 is a schematic diagram showing the distribution of data related to the usage time of the device status item in the maintenance history data table. In FIG. 17, the data indicated by “S” 552 is closest to the usage time of the apparatus at the time of a new abnormality, but is not specified. This is because when the specification is performed using a qualitative variable such as a usage time of 3000 or more and less than 4000, the usage time is close in this way, but it may not be specified because it deviates from a predefined section. Even such maintenance history data that cannot be specified in a pre-defined section can be specified without omission by performing k-neighborhood thinking and neighborhood calculation processing.

And the calculating part 21 determines whether all the individual diagnostic items were calculated (step S206). Specifically, the processing unit 21 stores information in the ratio 228b of countermeasure work items (countermeasure points) in the individual diagnosis processing result data storage area 228 for all records stored in the individual diagnosis item data storage area 224. If it is performed, the control proceeds to step S207. If all the records have not been processed, the calculation unit 21 increments i and returns control to step S201 again.

When all the individual diagnosis items have been calculated (in the case of “Yes” in step S206), the calculation unit 21 calculates the total frequency of the countermeasure work (step S207). Specifically, the computing unit 21 calculates the execution frequency for each countermeasure work using the information stored in the countermeasure work item 223c of the maintenance history data storage area 223, and stores it in the countermeasure work total frequency data storage area 229. To do.

More specifically, in the process of step S207, the calculation unit 21 reads information stored in each record of the countermeasure work item 223c, and the total frequency 229a of countermeasure work items (countermeasure points) specified by the stored information. 1 is added (counted up) to this column.

Also, the calculation unit 21 performs a process of taking the sum of the values stored in each record of the total frequency 229a of the countermeasure work items (countermeasure points) and storing the sum in the total frequency total 229b.

The information in the countermeasure work total frequency data storage area 229 in which information is stored in this way is used in the process of step S208 described later.

And the calculating part 21 calculates the product of a ratio for every countermeasure work (step S208). Specifically, the calculation unit 21 calculates the product of the ratio for each countermeasure work using information stored in the individual diagnosis processing result data storage area 228 and the countermeasure work total frequency data storage area 229, and performs integrated diagnosis. As a result of the processing, it is stored in the integrated diagnosis processing result data storage area 230.

More specifically, in the process of step S208, the calculation unit 21 calculates information to be stored in each item of the integrated diagnosis processing result 230a of the countermeasure work item (countermeasure part) according to the following equation (1).

Calculating according to equation (1), the product of the ratio, which is an index indicating the appropriateness of the countermeasure work, is calculated. The product of this ratio becomes an index indicating the appropriateness of each countermeasure work when the results calculated for the individual diagnosis items are combined.

Calculating section 21 calculates a value p _m using equation (1) for each of all the items of the integrated diagnostic processing results 230a, and stores the calculated value.

It is also multiplied by a coefficient for each p _m in equation (1). It is also possible to use a value which took the x _nm of the log and route instead of x _nm.

Also, the calculation unit 21 calculates the sum of the information stored in each item of the integrated diagnosis processing result 230a of the countermeasure work item (countermeasure point), and stores it in the processing result total 230b.

And the calculating part 21 presents the countermeasure work with a large product of a ratio as an estimation result (step S209). Specifically, the calculation unit 21 presents the estimation result of the countermeasure work to the worker using the information stored in the integrated diagnosis processing result data storage area 230.

More specifically, the calculation unit 21 performs countermeasure work corresponding to the column in descending order of items stored in the integrated diagnosis processing result 230a of the countermeasure work item (countermeasure location) in the integrated diagnosis processing result data storage area 230. Is presented as an estimation result.

FIG. 15 is a diagram showing an example of an output screen 420 for abnormality diagnosis processing. In the rank 421, information indicating the rank order of values stored in the integrated diagnosis processing result 230a of countermeasure work items (countermeasure points) is displayed. The order displayed in the rank 421 may be calculated by correcting the information stored in each column of the integrated diagnosis processing result 230a of the countermeasure work item (countermeasure point) with the cost information for each countermeasure work. good.

In the countermeasure work item (countermeasure point) 422, information indicating the countermeasure work corresponding to each item of the integrated diagnosis processing result 230a of the countermeasure work item (countermeasure point) is displayed.

In the point 423, information for specifying a value stored in each column of the integrated diagnosis processing result 230a of the countermeasure work item (countermeasure part) is displayed. In the present embodiment, a value obtained by dividing the value stored in the integrated diagnosis processing result 230a of the countermeasure work item (countermeasure location) by the value stored in the processing result total 230b is displayed.

In the abnormality elimination confirmation area 424, a button for inputting that the countermeasure work has been resolved is displayed.

The worker can quickly resolve the abnormality by performing a countermeasure work with a higher rank displayed in the rank 421 or a countermeasure work with a large point displayed in the point 423.

The individual diagnosis item ID 431, the individual diagnosis item 432, the item type 433, and the countermeasure work item (countermeasure part) ratio 434 are information indicating details of the diagnosis process.
In the individual diagnosis item ID 431, information stored in the individual diagnosis item ID 224a of the individual diagnosis item data storage area 224 is displayed.

In the individual diagnosis item 432, information stored in the individual diagnosis item 224b is displayed.

In the item type 433, information stored in the item type 224c is displayed.

In the countermeasure work item (countermeasure part) ratio 434, information stored in the countermeasure work item (countermeasure part) ratio 228b of the individual diagnosis processing result data storage area 228 is stored in the individual diagnosis item ID 228a and the individual diagnosis item 224a. Is displayed so as to correspond to the information. Further, the countermeasure work calculated as the first rank is highlighted and highlighted.

In the recalculation 435 excluding items, a button for accepting designation from the operator regarding the individual diagnosis items displayed in the individual diagnosis items 432 is displayed. When the input to this button is made, the calculation unit 21 recalculates the estimation result when the individual diagnosis item is excluded using the equation (1), and re-outputs the estimation result of the countermeasure work. As a result, it is possible to exclude individual diagnosis items that the operator determines cannot be used for estimation based on past work experience.

In the frequency total 441, information stored in the total frequency 229a of the countermeasure work items (countermeasure points) in the countermeasure work total frequency data storage area 229 is displayed so that the items correspond to each other. Also, the countermeasure work item calculated as the first rank is highlighted and highlighted.

This enables the operator to grasp the individual diagnosis items that contribute to the estimation result. Further, the data displayed in the countermeasure work item (countermeasure part) ratio 434 or the frequency total 441 may be the ranking of the stored numerical values for each record.

The above is the processing flow of the diagnostic process for countermeasure work. By performing the processing flow of countermeasure work diagnosis processing, even if only a small number of history information is accumulated, it is possible to realize presentation of appropriate countermeasure work in consideration of a plurality of items of the device status.

For example, as shown in FIG. 4, when the information indicating the apparatus state at the time of a new abnormality is “abnormality type: abnormal sound”, “alarm code: A002”, “current check: OK”, it is shown in Patent Document 1. In the method, if there is no combination of similar device states in the past maintenance history, the countermeasure work cannot be estimated and presented. However, in the method of the present invention, if there is a maintenance history with “abnormality type: abnormal sound” and a maintenance history with “alarm code: A002” and “current check: OK”, the countermeasure work is estimated and presented. Therefore, it is possible to estimate the countermeasure work even when the history information in which the combination of “abnormality type: abnormal sound”, “alarm code: A002”, and “current check: OK” is not accumulated. In this way, even if only a small number of history information is accumulated, it is possible to realize an appropriate countermeasure work in consideration of a plurality of items of the device state.

Note that step S104 (result input by the operator) of the outline operation flow performed by the abnormality diagnosis apparatus 10 corresponds to input by the operator to the abnormality elimination confirmation region 424.

In addition, for step S105 (maintenance history data accumulation processing) of the outline operation flow performed by the abnormality diagnosis apparatus 10, the arithmetic unit 21 accumulates information in the maintenance history data storage area 223. Specifically, the computing unit 21 adds a new record to the maintenance history data storage area 223, stores the new ID in the record to which the history ID 223a is added, and stores the device in the record to which the device status item 223b is added. The information stored in the device state item 225a at the time of new abnormality in the state data storage area 225 is read and stored, and the countermeasure work in which the button of the abnormality elimination confirmation area 424 is clicked is added to the record to which the countermeasure work item 223c is added. By storing the indicated information, the information is accumulated in the maintenance history data storage area 223. By accumulating information in this way, it is possible to estimate the countermeasure work more appropriately.

The abnormality diagnosis system according to the first embodiment has been described above. According to the first embodiment, an appropriate countermeasure work can be estimated and presented using information indicating a smaller device state.

The present invention is not limited to the first embodiment described above. The first embodiment described above can be variously modified within the scope of the technical idea of the present invention. For example, in the above-described embodiment, the configuration is described in detail in order to explain the present invention in an easy-to-understand manner, and is not necessarily limited to the one having all the configurations described.

In addition, each of the above-described configurations, functions, processing units, and the like may be realized by hardware by designing a part or all of them with, for example, an integrated circuit. Further, the control lines and information lines indicate what is considered necessary for the explanation, and not all the control lines and information lines on the product are necessarily shown. Actually, it may be considered that almost all the components are connected to each other.

Also, the technical elements of the above-described embodiments may be applied independently, or may be applied by being divided into a plurality of parts such as program parts and hardware parts.

In the above, this invention was demonstrated centering on embodiment.

DESCRIPTION OF SYMBOLS 1 ... Abnormality diagnosis system, 10 ... Abnormality diagnosis apparatus, 20 ... Diagnosis part, 21 ... Operation part, 22 ... Memory | storage part, 30 ... Input part, 31 ... Output part 32 ... Communication IF unit 211 ... IF unit 300 ... Network 1000 ... Diagnosis target device

Claims

An abnormality diagnosis device presenting countermeasure work for an abnormality occurring in another device,
The storage unit corresponds to the device status information including the status of the other device at the time of occurrence of the abnormality and the device status history information including the history of the device status information, and the countermeasure work performed when the abnormality occurs in the device. The countermeasure work history information attached is stored,
The control unit
Create at least two diagnostic models for calculating the frequency of the countermeasure work for each item of the device status information;
Using the diagnostic model, calculate an index indicating the appropriateness of countermeasure work for each of at least two items of the device status information,
An abnormality diagnosis apparatus that identifies and presents countermeasure work for an abnormality that has occurred in the other apparatus by combining at least two indicators that indicate the appropriateness of the countermeasure work.
The abnormality diagnosis device according to claim 1,
The controller is
Using the device status history information and the countermeasure work history information, for each item of the device status information, create a first diagnostic model representing the frequency of implementation of the countermeasure work in a predetermined device state,
An abnormality diagnosis device that calculates an index indicating appropriateness of countermeasure work for each item of the device state information using the first diagnosis model.
The abnormality diagnosis device according to claim 1,
The controller is
Implemented when the device status history information is close to a predetermined value or more by comparing the distance between the device status information and the information obtained by removing the device status information from the device status history information. A second diagnostic model indicating the frequency of the implemented countermeasure work is created using the countermeasure work history information,
An abnormality diagnosis device that calculates an index indicating appropriateness of countermeasure work for each item of the device state information using the second diagnosis model.
The abnormality diagnosis device according to claim 1,
The controller is
An abnormality diagnosis apparatus that uses a ratio of the number of times the countermeasure work is performed as an index indicating the appropriateness of the countermeasure work.
The abnormality diagnosis device according to claim 1,
The controller is
Occurs in the device using the product of the ratio of the number of countermeasure work executions calculated using the first diagnostic model and the ratio of the number of countermeasure work executions calculated using the second diagnostic model An abnormality diagnosis device that estimates the countermeasure work for abnormalities.
The abnormality diagnosis device according to claim 1,
The controller is
An abnormality diagnosis device using information including any one of an alarm code issued by the device, a test result of the device, a measured value of a device sensor, and a usage time of the device as the device status information.
An abnormality diagnosis method using an abnormality diagnosis device that presents countermeasures for an abnormality occurring in another device,
The abnormality diagnosis device includes a storage unit and a control unit,
In the storage unit, device state information indicating a state of the other device at the time of occurrence of an abnormality, device state history information including a history of the device state information, and countermeasure work performed when an abnormality occurs in the device. The associated countermeasure work history information is stored,
The controller is
Creating at least two diagnostic models for calculating the frequency of the countermeasure work for each item of the device status information;
Using the diagnostic model, each calculating an index indicating the appropriateness of countermeasure work for each of at least two items of the device status information;
And a step of identifying and presenting countermeasure work for an abnormality that has occurred in the other device by combining at least two indicators indicating the appropriateness of the countermeasure work.