JP2023153229A - Monitoring assistance system, monitoring assistance device, and monitoring assistance method - Google Patents

Abstract

To reduce a work load of monitoring and to improve work efficiency.SOLUTION: A monitoring assistance system includes: a group information storage unit configured to store group identification information for identifying a group to which a user belongs and restriction information related to analysis processing for analyzing acquired data of a monitoring target, in association with each other; an analysis processing unit configured to execute the analysis processing, based on a learning model generated using normal data of the monitoring target as learning data, in response to an analysis request from a user terminal used by the user; and a restriction processing unit configured to restrict use of the user including execution of the analysis processing, based on the restriction information stored in the group information storage unit and corresponding to the group to which the user belongs.SELECTED DRAWING: Figure 2

Description

The present disclosure relates to a monitoring support system, a monitoring support device, and a monitoring support method.

In recent years, monitoring systems that monitor monitoring targets such as plant equipment have been known (for example, see Patent Document 1). In such a monitoring system, a signal graph or an event history of the monitored object is displayed on the monitoring screen, and monitoring tasks such as detecting anomalies in the monitored object are performed based on the past experience of the monitoring staff.

JP 2021-149358 Publication

However, in the above-mentioned conventional technology, abnormality detection depends on the ability of the monitor, and abnormality detection etc. may depend on the individual's individual skills, which may reduce work efficiency.

The present disclosure has been made to solve the above problems, and the purpose is to provide a monitoring support system, a monitoring support device, and a monitoring support method that can reduce the work load of monitoring and improve work efficiency. There is a particular thing.

In order to solve the above problem, one aspect of the present disclosure provides a file name of a file that stores acquired data of a monitoring target, which is equipment of a plant registered by a user, and the acquired data stored in the file. , an analysis data storage unit that stores group identification information that identifies a group to which the user belongs, user identification information that identifies the user, and monitoring target identification information that identifies the monitoring target; , a group information storage unit that stores the group identification information and restriction information regarding analysis processing for analyzing the acquired data in association with each other; and the user uses the acquired data stored in the analysis data storage unit. an analysis processing unit that executes the analysis process based on a learning model generated using the normal data of the monitoring target as learning data in response to an analysis request from a user terminal, the group identification information, and the user; an analysis result storage unit that stores identification information, the monitoring target identification information, and the analysis result of the analysis process in association with each other, and the restriction information stored in the group information storage unit, the restriction information being stored in the group information storage unit, and the restriction information to which the user belongs. and a restriction processing unit that restricts the use of the user, including execution of the analysis process, based on the restriction information corresponding to the group.

Further, one aspect of the present disclosure provides a file name of a file that stores acquired data of a monitoring target that is equipment of a plant registered by a user, the acquired data stored in the file, and the information to which the user belongs. an analysis data storage unit that stores group identification information for identifying a group to be monitored, user identification information for identifying the user, and monitoring target identification information for identifying the monitoring target; , a group information storage unit that stores restriction information related to analysis processing for analyzing the acquired data in association with each other; and analysis of the acquired data stored in the analysis data storage unit from a user terminal used by the user. an analysis processing unit that executes the analysis process based on a learning model generated using the normal data of the monitoring target as learning data in response to a request, the group identification information, the user identification information, and the monitoring an analysis result storage unit that stores target identification information and analysis results of the analysis process in association with each other; and the restriction information stored in the group information storage unit, which corresponds to the group to which the user belongs. The monitoring support device includes a restriction processing unit that restricts the use of the user, including execution of the analysis process, based on the restriction information.

Further, one aspect of the present disclosure provides a file name of a file that stores acquired data of a monitoring target that is equipment of a plant registered by a user, the acquired data stored in the file, and the information to which the user belongs. an analysis data storage unit that stores group identification information for identifying a group to be monitored, user identification information for identifying the user, and monitoring target identification information for identifying the monitoring target; A monitoring support method for a monitoring support device comprising: a group information storage unit that stores group identification information in association with restriction information regarding analysis processing for analyzing the acquired data; an analysis processing unit; and a restriction processing unit. , the analysis processing unit generates the acquired data stored in the analysis data storage unit using the normal data of the monitoring target as learning data in response to an analysis request from a user terminal used by the user. executing the analysis process based on the learning model; and the analysis processing unit associating the group identification information, the user identification information, the monitoring target identification information, and the analysis result of the analysis process. the restriction processing unit stores the restriction information in the analysis result storage unit based on the restriction information stored in the group information storage unit and that corresponds to the group to which the user belongs; and a step of restricting use by the user including execution of the analysis process.

According to the present disclosure, it is possible to reduce the workload of monitoring and improve business efficiency.

1 is a diagram showing an example of the main hardware configuration of a monitoring support system according to the present embodiment. FIG. 1 is a block diagram showing an example of a functional configuration of a monitoring support system according to the present embodiment. It is a figure showing the example of data of the group information storage part in this embodiment. It is a figure showing the example of data of the user information storage part in this embodiment. It is a figure showing the example of data of the monitoring setting storage part in this embodiment. It is a figure which shows the example of data of the analysis data storage part in this embodiment. It is a figure showing an example of report information in this embodiment. FIG. 3 is a diagram illustrating an example of an analysis processing operation of waveform comparison of the monitoring support system according to the present embodiment. FIG. 3 is a diagram showing an example of a menu screen of the monitoring support system according to the present embodiment. It is a figure which shows an example of the analysis and report screen in waveform comparison of the monitoring support system by this embodiment. FIG. 3 is a diagram showing an example of a data input screen for waveform comparison of the monitoring support system according to the present embodiment. FIG. 3 is a diagram showing an example of an analysis start screen of the monitoring support system according to the present embodiment. It is a figure which shows an example of the analysis and report screen after the analysis process of waveform comparison of the monitoring support system by this embodiment. 7 is a flowchart illustrating an example of a waveform comparison analysis process of the portal server according to the present embodiment. 12 is a flowchart illustrating an example of a learning process for abnormality sign analysis of the portal server according to the present embodiment. FIG. 3 is a diagram illustrating an example of a processing operation of abnormality sign analysis of the monitoring support system according to the present embodiment. It is a figure which shows an example of the analysis and report screen in abnormality sign analysis of the monitoring support system by this embodiment. 7 is a flowchart illustrating an example of an abnormality sign analysis process of the portal server according to the present embodiment. It is a figure which shows an example of the display process of the analysis report, and a deletion process of a monitoring support system by this embodiment. FIG. 3 is a diagram showing a comparative example of analysis data of an analysis report of the monitoring support system according to the present embodiment. It is a figure which shows the modification of the data of a user information storage part in this embodiment.

Hereinafter, a monitoring support system, a monitoring support device, and a monitoring support method according to an embodiment of the present disclosure will be described with reference to the drawings.
FIG. 1 is a diagram showing an example of the main hardware configuration of a monitoring support system 1 according to this embodiment.

As shown in FIG. 1, the monitoring support system 1 includes a portal server 10 and user terminals 20 (20-1, 20-2, . . . ).
The monitoring support system 1 is a system that uses the portal server 10 to support monitoring operations that monitor monitoring targets such as plant equipment, and uses a service that analyzes acquired data (analytical data) obtained from the monitored targets. provided to the person.

In addition, in FIG. 1, each of the user terminals 20-1, 20-2, ... has the same configuration, and when indicating any user terminal provided in the monitoring support system 1, or especially If no distinction is made, the user terminal 20 will be described.

Further, the monitoring support system 1 can be used by a plurality of companies (for example, company C1, company C2, . . . ). For example, the user terminal 20-1 is a terminal device used by a user of company C1, and the user terminal 20-2 is a terminal device used by a user of company C2.

The user terminal 20 is a terminal device used by a user who uses the monitoring support system 1. The user terminal 20 is, for example, a personal computer, a tablet terminal, or the like. The user terminal 20 is connectable to the portal server 10 via the network NW1, and transmits learning data and analysis data in the analysis process. Further, the user terminal 20 receives report information based on the analysis result of the analysis process executed by the portal server 10, and displays (outputs) the report information.

The user terminal 20 includes an NW (network) adapter H21, a memory H22, a processor H23, an input device H24, and a display H25.
The NW adapter H11 is, for example, a communication device such as a LAN (Local Area Network) card that can be connected to the network NW1. NW adapter H11 performs data communication with portal server 10 via network NW1.

The memory H22 is, for example, a storage device such as a RAM (Random Access Memory), a flash memory, or an HDD (Hard Disk Drive), and stores various information and programs used by the user terminal 20.

The processor H23 is, for example, a processing circuit including a CPU (Central Processing Unit). The processor H23 executes various processes of the user terminal 20 by executing programs stored in the memory H22.

The input device H24 is, for example, a keyboard, a pointing device, a touch sensor, or the like. The input device H24 accepts input of various information by the user when using the monitoring support system 1.

The display H25 is, for example, a display device such as a liquid crystal display. The display H25 displays various information when using the monitoring support system 1. The display H25 displays, for example, a menu screen sent from the portal server 10, various screens for analysis processing, analysis results, report information, and the like.

The portal server 10 is, for example, a server device that includes a computer system therein, and is an example of a monitoring support device that provides services related to monitoring of monitoring targets such as plant equipment. Portal server 10 is connectable to user terminal 20 via network NW1.
The portal server 10 includes a NW adapter H11, a memory H12, and a processor H13.

The NW adapter H11 is, for example, a communication device such as a LAN card that can be connected to the network NW1.
The memory H12 is a storage device such as a RAM, flash memory, or HDD, and stores various information and programs used by the portal server 10.

The processor H13 is, for example, a processing circuit including a CPU. The processor H13 executes various processes of the portal server 10 by executing programs stored in the memory H12.

Next, with reference to FIG. 2, the functional configuration of the monitoring support system 1 according to this embodiment will be described.
FIG. 2 is a block diagram showing an example of the functional configuration of the monitoring support system 1 according to this embodiment.

As shown in FIG. 2, the monitoring support system 1 includes a portal server 10 and a user terminal 20. Note that in the example shown in FIG. 2, one user terminal 20 is shown for convenience of explanation, but even if multiple user terminals 20 are connected to the portal server 10 via the network NW1. good.

The user terminal 20 includes a NW communication section 21, an input section 22, a display section 23, a terminal storage section 24, and a terminal control section 25.
The NW communication unit 21 is a functional unit realized by the NW adapter H21, and connects to the network NW1 to perform data communication with, for example, the portal server 10.

The input unit 22 is a functional unit realized by the input device H24, and uses information such as login information to the portal server 10, designation of learning data and analysis data to be registered in the portal server 10, input of analysis processing, etc. accepted from the person. The input unit 22 outputs various input information received from the user to the terminal control unit 25.

The display unit 23 is a functional unit realized by the display H25, and displays, for example, a menu screen transmitted from the portal server 10, various screens of analysis processing, analysis results, report information, and the like.

The display unit 23 displays, for example, a list of analysis information (a list of reports) with which analysis results corresponding to each of a plurality of monitoring targets can be compared. Here, the plurality of monitoring targets include, for example, a plurality of different types of equipment monitored by a monitor (user of the monitoring support system 1) in a plant such as a building, factory, hospital, or power plant, The display unit 23 displays this analysis information in a list.

The terminal storage unit 24 includes a memory H22, and stores various information used by the user terminal 20. The terminal storage unit 24 stores, for example, acquired data (learning data and analysis data) of the monitoring target before registration, analysis results received from the portal server 10, and the like.

The terminal control unit 25 is a functional unit that is realized by causing the processor H23 to execute a program stored in the memory H22. The terminal control unit 25 executes various processes by the user terminal 20. For example, the terminal control unit 25 connects to the portal server 10 via the NW communication unit 21 and displays the menu screen received from the portal server 10 on the display unit 23.

In addition, the terminal control unit 25 displays the analysis processing screen received from the portal server 10 on the display unit 23, and also displays the learning data and analysis data of the monitoring target received from the user via the input unit 22 through the NW communication. 21 to the portal server 10.

Additionally, the terminal control unit 25 displays a list of analysis information for a plurality of monitoring targets on the display unit 23, which is a result screen of the analysis process received from the portal server 10, and also displays information received from the user via the input unit 22. Selection information of analysis information is transmitted to the portal server 10 via the NW communication unit 21. Furthermore, the terminal control unit 25 displays report information received from the portal server 10 on the display unit 23 according to the selection information.

The portal server 10 includes a NW communication section 11, a server storage section 12, and a server control section 13.
The NW communication unit 11 is a functional unit realized by the NW adapter H11, connects to the network NW1, and performs data communication with the user terminal 20.

The server storage unit 12 includes a memory H12, and stores various information used by the portal server 10. The server storage unit 12 includes a group information storage unit 121, a user information storage unit 122, a learning data storage unit 123, a monitoring setting storage unit 124, an analysis data storage unit 125, a learning model storage unit 126, and an analysis data storage unit 125. It includes a result storage section 127 and a report information storage section 128.

The group information storage unit 121 stores information regarding groups to which users belong, such as companies, organizations, and organizations. Note that in the monitoring support system 1 according to the present embodiment, services provided by the portal server 10 (for example, analysis services for monitoring targets, etc.) can be used by contracting for services in groups such as companies. The group information storage unit 121 stores information regarding groups that have subscribed to the service. The group information storage unit 121 stores, for example, a group ID that identifies a group to which a user belongs, and restriction information regarding analysis processing for analyzing acquired data to be monitored, in association with each other. Here, an example of data in the group information storage section 121 will be described with reference to FIG. 3.

FIG. 3 is a diagram showing an example of data in the group information storage unit 121 in this embodiment.
As shown in FIG. 3, the group information storage unit 121 corresponds to a group ID, a management password, a group name, the number of contract signals, the number of accounts, the number of possible analyzes, the number of times analysis is executed, and the expiration date. Attach and memorize.

In FIG. 3, the group ID is group identification information that identifies the group that has subscribed to the service. Further, the management password is, for example, a password used by a group representative when performing management processing such as user registration. Further, the group name indicates a group name such as a contracted company name, organization name, group name, etc.

Further, the number of contracted signals indicates the number of signals that can be used during analysis processing. The number of contract signals is an example of the upper limit number of signals for acquired data (analysis data) to be monitored, which is set for each group. Further, the number of accounts is the number of user accounts that can be registered within a group, and is an example of the upper limit number of users set for each group. Furthermore, the number of times that analysis is possible indicates the number of times that analysis processing can be used, and the number of times that analysis execution is performed indicates the number of times that analysis processing has been executed. The possible number of times of analysis is an example of a limit on the number of times analysis processing can be executed, which is set for each group.

Further, the expiration date indicates the expiration date for using the service of the portal server 10, and is an example of the usage expiration date for analysis processing set for each group. Here, the number of contract signals, the number of accounts, the number of times analysis is possible, the number of times analysis is executed, and the expiration date are examples of restriction information regarding analysis processing. In addition to the possible number of times of analysis and the number of times of execution of analysis, the group information storage unit 121 may store an upper limit number of times of analysis processing set for each group, such as the number of times of contract execution. Further, the group information storage unit 121 may store setting information such as change information based on contract conditions (for example, usage fees, etc.), setting information of settable options, and the like.

For example, in the example shown in FIG. 3, the management password of the group whose group ID is "G001" is "ABCDXXX", indicating that the group name is "○○ Corporation". In addition, the number of contract signals for this group is "50", indicating that the number of accounts is "50", and the number of possible analyzes is "20", and the number of analysis executions is "10". Yes, indicating that the expiration date is “2022/3/31” (March 31, 2022).

Returning to the explanation of FIG. 2 again, the user information storage unit 122 stores user information regarding users who use the portal server 10. The user information storage unit 122 stores user information for each group. Here, with reference to FIG. 4, an example of data in the user information storage section 122 will be described.

FIG. 4 is a diagram showing an example of data in the user information storage unit 122 in this embodiment.
As shown in FIG. 4, the user information storage unit 122 stores group IDs, user IDs, passwords, and names in association with each other.

In FIG. 4, the group ID indicates the group to which the user belongs, and the user ID indicates user identification information that identifies the user. Further, the password indicates a password for the user to connect to the portal server 10 and use the service. The user ID and password are login information. Further, the name indicates the user's name or name.

For example, the example shown in FIG. 4 shows that users with user IDs "U10001" and "U10002" are registered in a group with group ID "G001". Further, the user whose user ID is "U10001" has a password of "XXXXXX" and a name of "○○ Taro." Further, the user whose user ID is "U10002" has a password of "YYYYYY" and a name indicating that he/she is in the "XX development department." Note that the name may be a department name, such as "XX Development Department."

It also shows that the user with the user ID "U20001" is registered in the group with the group ID "G002". Further, the user whose user ID is "U20001" has a password of "EFGHIJ" and a name of "XX Ichiro."
In this way, the user information storage unit 122 stores user information for each group. Note that user information can be registered, changed, and deleted by the administrator of each group.

Returning to the explanation of FIG. 2 again, the learning data storage unit 123 stores learning data registered by the user, which is learning data for generating a learning model. The learning data storage unit 123 stores, for example, normal data of the monitoring target as learning data for each monitoring target. The learning data storage unit 123 stores, for example, group IDs, user IDs, monitoring target IDs, signal names, and learning data in association with each other, similar to the analysis data storage unit 125 described later.

The monitoring setting storage unit 124 stores setting information of monitoring targets. The monitoring setting storage unit 124 stores, for example, a monitoring object ID for identifying a monitoring object, a group ID, a user ID, and setting information regarding the monitoring object in association with each other. Here, an example of data in the monitoring setting storage section 124 will be described with reference to FIG. 5.

FIG. 5 is a diagram showing an example of data in the monitoring setting storage unit 124 in this embodiment.
As shown in FIG. 5, the monitoring setting storage unit 124 stores monitoring target IDs, group IDs, user IDs, and setting information in association with each other. Here, the monitoring target ID is an example of monitoring target identification information that identifies a monitoring target.

For example, in the example shown in FIG. 5, the monitoring target ID "M001" indicates that the group ID is "G001" and is registered by the user whose user ID is "U10001." It also indicates that this setting information is "XXX, YYY, . . .". Note that the setting information may include setting information of the learning model to be used, the type of analysis processing (waveform comparison analysis or abnormality sign analysis), etc. to be described later.

Returning to the explanation of FIG. 2 again, the analysis data storage unit 125 stores analysis data of the monitoring target registered by the user. Here, the analysis data is acquired data acquired during monitoring of a monitoring target such as plant equipment, and includes measurement data of various sensors. The analysis data is stored, for example, in a CSV format file. Here, with reference to FIG. 6, an example of data in the analysis data storage section 125 will be described.

FIG. 6 is a diagram showing an example of data in the analysis data storage unit 125 in this embodiment.
As shown in FIG. 6, the analysis data storage unit 125 stores group IDs, date and time information, user IDs, monitoring target IDs, signal names, titles, file names, and data in association with each other. .

In FIG. 6, the user ID indicates the user who registered the analysis data. The signal name is the signal name of the analysis data. Further, the title is the title name of the analysis data set by the user when registering the analysis data. Further, the file name indicates the file name of the analysis data, and the data indicates the contents of the analysis data file.

For example, in the example shown in FIG. 6, the log information corresponding to the group ID "G001" has the date and time information "2022/2/22 11:00:00" (February 22, 2022 11:00:00). ), indicating that the user ID is "U10001". Further, this analysis data indicates that the monitoring target ID is "M001", the signal name is "AI0001", the log title is "XX01 data", and the file name is "XXX01.csv".
Note that the learning data storage section 123 described above may store learning data as shown in FIG. 6, similarly to the analysis data storage section 125.

Returning to the explanation of FIG. 2 again, the learning model storage unit 126 stores learning models used for analysis processing. The learning model storage unit 126 stores, for example, a group ID, a user ID, and a learning model in association with each other.

The analysis result storage unit 127 stores analysis results of analysis processing to be described later. The analysis result storage unit 127 stores, for example, group IDs, user IDs, monitoring target IDs, and analysis results in association with each other.

The report information storage unit 128 stores report information generated based on the analysis results. The report information storage unit 128 stores, for example, group IDs, user IDs, monitoring target IDs, and report information in association with each other. Here, an example of report information will be described with reference to FIG. 7.

FIG. 7 is a diagram showing an example of report information in this embodiment.
Report RP1 shown in FIG. 7 is report information including analysis data information DI, analysis result RES1, and learning data DT1 and analysis data DT2 for comparison.

In FIG. 7, the analysis data information DI is information such as the period of learning data, the period of analysis data, the number of signals, and the main signals, and is information regarding input for analysis. Further, the analysis result RES1 is, for example, a graph of daily changes in abnormality detection time (information on all signals is accumulated and displayed).

Further, the learning data DT1 indicates the waveform of the learning data of each signal, and the analysis data DT2 indicates the waveform of the analysis data and the analysis result of each signal.

Returning to the explanation of FIG. 2 again, the server control unit 13 is a functional unit that is realized by causing the processor H13 to execute a program stored in the memory H12. The server control unit 13 includes a web processing unit 131, a data registration processing unit 132, a monitoring registration processing unit 133, a learning processing unit 134, an analysis processing unit 135, and a report processing unit 136.

The web processing unit 131 executes web processing for a portal site that provides services of the portal server 10. The web processing unit 131 transmits various web display data in HTML (Hyper Text Markup Language) format to the connection request received from the user terminal 20 via the NW communication unit 11. The information is transmitted to the user terminal 20 to cause the display unit 23 of the user terminal 20 to display a web screen based on various web display data.

The web processing unit 131 executes, for example, a user login process. The web processing unit 131 determines whether the user ID and password received from the user terminal 20 via the NW communication unit 11 match the user ID and password stored in the user information storage unit 122. judge. The web processing unit 131 allows the portal server 10 to provide the service when the received user ID and password match the user ID and password stored in the user information storage unit 122.

In addition, the web processing unit 131, for example, creates a list of analysis information that can be compared with the analysis results analyzed by the analysis processing unit 135, which will be described later, and that corresponds to each of a plurality of monitoring targets, and provides the information to the user terminal. 20 to output. That is, the Web processing unit 131 transmits the list of analysis information to the user terminal 20 via the NW communication unit 11, and causes the user terminal 20 to display the list of analysis information. Here, the Web processing unit 131 is an example of an output processing unit that processes output to the user terminal 20.

For example, when a new monitoring target is added to the monitoring setting storage unit 124, the web processing unit 131 adds the monitoring target added to the monitoring setting storage unit 124 to the list of analysis information and displays the information on the user terminal. 20 to output.

In addition, for example, when the analysis processing unit 135 (described later) completes analysis of a newly added monitoring target, the web processing unit 131 stores the analysis information of the newly added monitoring target in a list of analysis information. , and causes the user terminal 20 to output notification information indicating that a new monitoring target has been added to the analysis information list.

Further, the web processing unit 131 causes the user terminal 20 to output a list of analysis information corresponding to the user ID or a list of analysis information corresponding to the group ID in accordance with a specification from the user terminal 20. Good too. That is, the web processing unit 131 switches between a list of analysis information for each user and a list of analysis information analyzed by a plurality of users in the group, and causes the user terminal 20 to display the list.

Further, in accordance with the search information received from the user terminal 20, the web processing unit 131 extracts analysis information corresponding to the search information from the list of analysis information, and displays the extracted analysis information list as the search result. is output to the user terminal 20 as follows.

Further, the Web processing unit 131 causes the user terminal 20 to output report information generated by a report processing unit 136, which will be described later. For example, when the user terminal 20 selects a specific monitoring target from the list of analysis information, the web processing unit 131 causes the user terminal 20 to output report information of the selected specific monitoring target. That is, the Web processing unit 131 acquires report information of the selected specific monitoring target from the report information storage unit 128, and sends the report information as shown in FIG. 7 to the user terminal via the NW communication unit 11. 20 and displayed on the user terminal 20.

Further, the web processing unit 131 restricts the user's use, including the execution of analysis processing, based on the restriction information stored in the group information storage unit 121 and corresponding to the group to which the user belongs. . The Web processing unit 131 here is an example of a restriction processing unit that restricts the use of the portal server 10.

For example, the web processing unit 131 prohibits users belonging to the group from executing the analysis process when the number of executions of the analysis process in the group reaches the execution limit number of times. That is, the Web processing unit 131 determines whether the number of executions of the analysis process in the group has reached the execution limit based on the number of possible analyzes and the number of executions of the analysis in the group information storage unit 121. If the web processing unit 131 determines that the number of executions of the analysis process in the group has reached the execution limit, it prohibits the user IDs of the users belonging to the group from executing the analysis process.

Furthermore, when the number of signals of acquired data used for analysis processing reaches the upper limit number of signals, the Web processing unit 131 restricts use by users belonging to the group. That is, the Web processing unit 131 determines whether the number of signals has reached the upper limit number of signals based on the number of contracted signals in the group information storage unit 121. When the Web processing unit 131 determines that the number of signals has reached the upper limit number of signals, the Web processing unit 131 restricts, for example, the use of the portal server 10 with respect to the user ID of the user belonging to the group. In this case, the web processing unit 131, for example, stops execution of the analysis process or prohibits the registration process of data such as analysis data.

Further, the web processing unit 131 limits registration of users belonging to the group when the number of users belonging to the group stored in the user information storage unit 122 reaches the upper limit number of users. That is, the web processing unit 131 determines whether the number of users belonging to the group has reached the upper limit number of users based on the number of accounts in the group information storage unit 121. For example, the web processing unit 131 prohibits registration of new users when the number of users belonging to the group reaches the upper limit number of users.

Further, the Web processing unit 131 restricts the use of users belonging to the group when the usage period of the analysis process reaches its usage limit. That is, the Web processing unit 131 determines whether the usage period of the analysis process has reached the usage period based on the expiration date of the group information storage unit 121. When the Web processing unit 131 determines that the usage period of the analysis process has reached its usage limit, the web processing unit 131 restricts the use of the portal server 10, for example, to the user ID of the user belonging to the group.

Further, the Web processing unit 131 cancels the usage restriction when an additional usage fee is paid by the group (for example, a contract company of the portal server 10).

The data registration processing unit 132 registers learning data and analysis data received from the user terminal 20. The data registration processing unit 132 stores the learning data received from the user terminal 20 in the learning data storage unit 123 by associating the learning data with the group ID, user ID, and monitoring target ID, as shown in FIG. 6, for example. Make me remember. Further, the data registration processing unit 132 associates the analysis data received from the user terminal 20 with the group ID, user ID, and monitoring target ID, as shown in FIG. 125.

In response to a monitoring target addition request received from the user terminal 20, the monitoring registration processing unit 133 adds monitoring target setting information corresponding to the addition request to the monitoring setting storage unit 124. The additional request here is, for example, a request to analyze a monitoring target (request to execute analysis processing), a request to generate a learning model, and the like. For example, as shown in FIG. 5, the monitoring registration processing unit 133 causes the monitoring target setting information to be stored in the monitoring setting storage unit 124.

The learning processing unit 134 generates a learning model based on the learning data. The learning processing unit 134 uses, for example, normal data of the monitoring target received from the user terminal 20 as learning data, and generates a learning model based on the learning data. The learning processing unit 134 generates a learning model based on the learning data stored in the learning data storage unit 123.

Further, the learning processing unit 134 stores the generated learning model in the learning model storage unit 126. The learning processing unit 134 associates the group ID, user ID, and learning model with each other, and stores them in the learning model storage unit 126, for example.

The analysis processing unit 135 analyzes the acquired data of the monitoring target based on a learning model generated using preregistered normal data of the monitoring target as learning data. The analysis processing unit 135 can perform two types of analysis processing: waveform comparison analysis and abnormality sign analysis. Waveform comparison analysis is a process of comparing and analyzing waveforms between learning data, which is normal data to be monitored, and analysis data. Further, abnormality sign analysis is a process of analyzing analysis data using a learning model registered in advance, and is a process of analyzing abnormality signs.

In the waveform comparison analysis, the analysis processing unit 135 analyzes the normal data and the monitoring target analysis data received from the user terminal 20 based on a learning model for comparison determination generated from the normal data received from the user terminal 20. Compare and analyze the data. As a technique for comparing and analyzing normal data and analytical data, for example, the technique described in International Publication No. 2016/117086 can be applied.

Furthermore, in the abnormality sign analysis, the analysis processing unit 135 analyzes the analysis data of the monitoring target received from the user terminal 20 based on the learning model registered in advance in the learning model storage unit 126. The analysis processing unit 135 analyzes abnormality signs in the analysis data stored in the analysis data storage unit 125 based on a learning model registered in advance. For example, the analysis processing unit 135 predicts a discrepancy between normal data and analysis data based on a learning model, and determines a sign of the discrepancy. As a technique for analyzing abnormal signs, for example, the technique described in International Publication No. 2018/207350 can be applied.

Furthermore, the analysis processing unit 135 causes the analysis result storage unit 127 to store the analysis result of the analysis process. For example, the analysis processing unit 135 stores the group ID, user ID, monitoring target ID, and analysis result in the analysis result storage unit 127 in association with each other.

The report processing unit 136 generates report information as shown in FIG. 7, for example, based on the analysis result by the analysis processing unit 135. The report processing unit 136 acquires the analysis results stored in the analysis result storage unit 127, and generates report information based on the acquired analysis results. For example, when the analysis processing unit 135 executes abnormality sign analysis, the report processing unit 136 generates report information that emphasizes signs of deviation.

Additionally, the report processing unit 136 causes the report information storage unit 128 to store the generated report information. The report processing unit 136 associates the group ID, user ID, monitoring target ID, and report information with each other, and stores them in the report information storage unit 128, for example.

Next, the operation of the monitoring support system 1 according to this embodiment will be explained with reference to the drawings.
FIG. 8 is a diagram showing an example of the waveform comparison analysis processing operation of the monitoring support system 1 according to the present embodiment.

As shown in FIG. 8, in the waveform comparison analysis process of the monitoring support system 1, the user terminal 20 first transmits a connection request to the portal server 10 (step S101). The terminal control unit 25 of the user terminal 20 transmits a connection request to the URL (Uniform Resource Locator) of the portal server 10 via the NW communication unit 21 according to the user's operation via the input unit 22. .

Next, the portal server 10 transmits a login screen (HTML data of the login screen) to the user terminal 20 in response to a connection request from the user terminal 20 (step S102). The web processing unit 131 of the portal server 10 uses the NW communication unit 11 to display a login screen (HTML data of the login screen) for entering a user ID and password on the user terminal 20. The information is sent to the user terminal 20.

Next, the user terminal 20 displays a login screen (step S103). The terminal control unit 25 causes the display unit 23 to display the login screen received via the NW communication unit 21.

Next, the user terminal 20 transmits login information (user ID, password) to the portal server 10 (step S104). The terminal control unit 25 receives a user ID and password from the user via the input unit 22, and transmits login information including the user ID and password to the portal server 10 via the NW communication unit 21.

Next, the portal server 10 executes login processing (step S105). The web processing unit 131 executes a login process based on the user ID and password received from the user terminal 20 via the NW communication unit 11. As a login process, the web processing unit 131 determines whether the received user ID and password match the user ID and password stored in the user information storage unit 122.

If the received user ID and password match the user ID and password stored in the user information storage unit 122, the web processing unit 131 determines that the user is a legitimate user, and stores the user ID. Allow us to provide services to you. Further, if the received user ID and password do not match the user ID and password stored in the user information storage unit 122, the web processing unit 131 determines that the user is not a legitimate user, and Provision of services by ID is not permitted. Note that in the following description, it is assumed that the user of the user terminal 20 is a legitimate user.

Next, the portal server 10 transmits the menu screen to the user terminal 20 (step S106). The web processing unit 131 transmits a menu screen of a service provided by the portal server 10 to the user terminal 20 via the NW communication unit 11.

Next, the user terminal 20 displays a menu screen (step S107). The terminal control unit 25 causes the display unit 23 to display, for example, a menu screen as shown in FIG. 9 received via the NW communication unit 21.

FIG. 9 is a diagram showing an example of a menu screen of the monitoring support system 1 according to this embodiment.
A screen G1 shown in FIG. 9 shows a menu screen of the portal server 10. In screen G1, button BT1 is a button for selecting "abnormality sign analysis" (analysis processing).

Returning to the description of FIG. 8, next, the user terminal 20 transmits designation information for analysis processing to the portal server 10 (step S108). Here, assuming that the button BT1 has been selected by the user via the input unit 22, the terminal control unit 25 transmits specification information for analysis processing to the portal server 10 via the NW communication unit 21.

Next, the portal server 10 transmits the analysis and report screen to the user terminal 20 (step S109). The web processing unit 131 transmits an analysis and report screen to the user terminal 20 via the NW communication unit 11 in accordance with the analysis process specification information received from the user terminal 20 .

Next, the user terminal 20 displays an analysis and report screen (step S110). The terminal control unit 25 causes the display unit 23 to display, for example, an analysis and report screen as shown in FIG. 10 received via the NW communication unit 21.

FIG. 10 is a diagram showing an example of an analysis and report screen for waveform comparison of the monitoring support system 1 according to the present embodiment.
Screen G2 shown in FIG. 10 shows an analysis and report screen for waveform comparison. In the screen G2, an analysis information list LS1 shows a list of analysis information for waveform comparison. Furthermore, the analysis information list LS2 shows a list of analysis information for abnormality sign analysis. Further, button BT2 indicates a selection button for waveform comparison analysis, and button BT3 indicates a switching button for analysis processing.

Returning to the explanation of FIG. 8 again, next, the user terminal 20 transmits the waveform comparison designation information to the portal server 10 (step S111). Here, it is assumed that waveform comparison analysis has been specified and the switching button (button BT3) has been pressed on the analysis and report screen (screen G2) shown in FIG. The unit 25 transmits the waveform comparison designation information to the portal server 10 via the NW communication unit 21.

Next, the portal server 10 transmits a data input screen for waveform comparison to the user terminal 20 (step S112). The web processing unit 131 transmits a data input screen for waveform comparison to the user terminal 20 via the NW communication unit 11 in accordance with the waveform comparison designation information received from the user terminal 20 .

Next, the user terminal 20 displays a data input screen for waveform comparison (step S113). The terminal control unit 25 causes the display unit 23 to display, for example, a waveform comparison data input screen as shown in FIG. 11 received via the NW communication unit 21.

FIG. 11 is a diagram showing an example of a data input screen for waveform comparison of the monitoring support system 1 according to the present embodiment.
Screen G3 shown in FIG. 11 shows a data input screen for waveform comparison. In the screen G3, an input window WD1 indicates an input window for an analysis title, and an input window WD2 indicates a registration window for learning data. Input window WD3 indicates an analysis data registration window, and input window WD4 indicates a condition setting input window. Further, button BT4 indicates a button to start analysis processing of waveform comparison.

Returning to the explanation of FIG. 8 again, next, the user terminal 20 transmits input data for waveform comparison (learning data and analysis data) to the portal server 10 (step S114). Here, the title, learning data, and analysis data are input via the input unit 22 on the waveform comparison data input screen (screen G3) shown in FIG. Assuming that has been pressed, the terminal control unit 25 transmits input data for waveform comparison (learning data and analysis data) to the portal server 10 via the NW communication unit 21.

Next, the portal server 10 executes registration processing (step S115). The web processing unit 131 registers data in the data registration processing unit 132 and the monitoring registration processing unit 133 according to the waveform comparison input data (learning data and analysis data) received from the user terminal 20 via the NW communication unit 11. Execute the process.

The data registration processing unit 132 stores the received learning data in the learning data storage unit 123 in association with the group ID, user ID, and monitoring target ID, as shown in FIG. 6, for example. Further, the data registration processing unit 132 stores the received analysis data in the analysis data storage unit 125 in association with the group ID, user ID, and monitoring target ID, as shown in FIG. 6, for example.
Further, the monitoring registration processing unit 133 stores setting information of the monitoring target in the monitoring setting storage unit 124, for example, as shown in FIG.

Next, the portal server 10 transmits an analysis start screen (number of possible analyses, etc.) to the user terminal 20 (step S116). The Web processing unit 131 transmits an analysis start screen (number of possible analyses, etc.) to the user terminal 20 via the NW communication unit 11 in response to the start of the analysis process.

Next, the user terminal 20 displays an analysis start screen (step S117). The terminal control unit 25 causes the display unit 23 to display, for example, an analysis start screen as shown in FIG. 12 received via the NW communication unit 21.

FIG. 12 is a diagram showing an example of an analysis start screen of the monitoring support system according to the present embodiment.
Screen G4 shown in FIG. 12 shows an analysis start screen of the portal server 10. On the screen G4, a message indicating that the analysis has started is displayed, as well as the analyzed content, the expiration date, the number of times the analysis has been performed, and the number of possible analyzes.

The portal server 10 also executes waveform comparison processing (waveform comparison analysis processing) (step S118). The analysis processing unit 135 of the portal server 10 executes analysis processing of waveform comparison. Further, the report processing unit 136 generates report information based on the analysis result of the waveform comparison analysis process. Note that details of the waveform comparison analysis process and the report information generation process will be described later with reference to FIG.

Next, the portal server 10 transmits the analysis and report screen with the report added to the user terminal 20 (step S119). Upon completion of the analysis process, the web processing unit 131 transmits the analysis and report screen to which the report has been added to the user terminal 20 via the NW communication unit 11.

Next, the user terminal 20 displays an analysis and report screen with the report added (step S120). The terminal control unit 25 causes the display unit 23 to display, for example, an analysis and report screen as shown in FIG. 13 received via the NW communication unit 21.

FIG. 13 is a diagram showing an example of an analysis and report screen after the waveform comparison analysis process of the monitoring support system 1 according to the present embodiment.
Screen G5 shown in FIG. 13 shows the analysis and report screen after the waveform comparison analysis process. In the screen G5, an analysis information list LS1 shows a list of analysis information for waveform comparison. Furthermore, the analysis information list LS2 shows a list of analysis information for abnormality sign analysis. Further, report RP1 shows analysis information of the monitoring target added in the current waveform comparison analysis process. Further, notification AL1 indicates that analysis information of a new monitoring target has been added to the list. Note that more detailed report information of report RP1 is the information of report RP1 shown in FIG. The added report RP1 is added to the analysis information list LS1, which is a list of analysis information for waveform comparison in FIG. 13.

In this way, when the analysis processing unit 135 completes the analysis (waveform comparison analysis) of the newly added monitoring target, the web processing unit 131 uses the analysis information of the newly added monitoring target to It is added to the top of the analysis information list and causes the user terminal 20 to output notification information indicating that a new monitoring target has been added to the analysis information list.

Furthermore, in the screen G5, an input window WD5 indicates a search keyword input window. When a user inputs a search keyword (search information) into this input window WD5, the web processing unit 131 displays a list of analysis information according to the search keyword (search information) received from the user terminal 20. Analysis information corresponding to the search information is extracted from among them, and a list of the extracted analysis information is output to the user terminal 20 as a search result.

Next, details of the waveform comparison analysis process will be described with reference to FIG. 14.
FIG. 14 is a flowchart illustrating an example of the waveform comparison analysis process of the portal server 10 in this embodiment. The process shown in FIG. 14 corresponds to the processes in step S116, step S118, and step S119 in FIG. 8 described above.

As shown in FIG. 14, the web processing unit 131 of the portal server 10 first determines whether the number of possible analyzes is 0 (step S201). The Web processing unit 131 refers to the number of times the analysis can be performed and the number of times the analysis can be executed for the group to which the user belongs from the group information storage unit 121, and determines whether the limit number of times of execution has been reached. If the number of possible analyzes is 0 (the limited number of executions has been reached) (step S201: YES), the web processing unit 131 advances the process to step S209. Further, if the number of possible analyzes is not 0 (the limited number of executions has not been reached) (step S201: NO), the web processing unit 131 advances the process to step S202.

In step S202, the web processing unit 131 determines whether the number of signals is within a limit. The Web processing unit 131 refers to the number of contracted signals of the group to which the user belongs from the group information storage unit 121, and determines whether the number of signals has reached the upper limit. If the number of signals is within the limit (within the contract number of signals) (step S202: YES), the web processing unit 131 advances the process to step S203. Further, if the number of signals is not within the limit (outside the contracted number of signals) (step S202: NO), the web processing unit 131 advances the process to step S209.

In step S203, the web processing unit 131 updates the possible number of times of analysis and the number of times of execution of analysis. The web processing unit 131 subtracts one time from the possible number of analyzes and adds one time to the number of times the analysis can be executed, and stores the result in the group information storage unit 121.

Next, the web processing unit 131 displays an analysis start screen on the display unit 23 of the user terminal 20 (step S204). The web processing unit 131 transmits an analysis start screen as shown in FIG. 12 to the user terminal 20 via the NW communication unit 11.

Next, the learning processing unit 134 generates a learning model from the registered normal data (step S205). The learning processing unit 134 generates a learning model from the learning data (normal data received from the user terminal 20) stored in the learning data storage unit 123. The learning processing unit 134 stores the learning model in the learning model storage unit 126.

Next, the analysis processing unit 135 uses the learning model to perform a comparative analysis between the normal data and the analysis data (step S206). The analysis processing unit 135 performs comparative analysis between normal data and analytical data using, for example, the techniques described in International Publication No. 2016/117086 and International Publication No. 2018/207350. The analysis processing unit 135 causes the analysis result storage unit 127 to store the analysis result.

Next, the report processing unit 136 generates a report based on the comparative analysis results (step S207). The report processing unit 136 generates, for example, information on report RP1 shown in FIG. 7 and information on report RP1 shown in FIG. 13. The report processing unit 136 causes the report information storage unit 128 to store the generated report.

Next, the Web processing unit 131 generates an analysis and report screen to which the generated report is added, and displays it on the display unit 23 of the user terminal 20 (step S208). The web processing unit 131 causes the user terminal 20 to display an analysis and report screen such as screen G5 in FIG. 13, for example. After the process in step S208, the web processing unit 131 ends the waveform comparison analysis process.

Further, in step S209, the web processing unit 131 displays an error message on the display unit 23 of the user terminal 20. In this case, the web processing unit 131 restricts the user's use of the portal server 10 and prohibits the execution of waveform comparison analysis processing. After the process in step S209, the web processing unit 131 ends the waveform comparison analysis process.

Next, an abnormality sign analysis process of the portal server 10 in this embodiment will be described with reference to the drawings.
FIG. 15 is a flowchart illustrating an example of a learning process for abnormality sign analysis of the portal server 10 in this embodiment.

As shown in FIG. 15, in the learning process for anomaly sign analysis, the portal server 10 first executes a monitoring target registration process (step S301). The monitoring registration processing unit 133 of the portal server 10 adds setting information of the monitoring target to the monitoring setting storage unit 124. For example, as shown in FIG. 5, the monitoring registration processing unit 133 causes the monitoring target setting information to be stored in the monitoring setting storage unit 124.

Next, the portal server 10 registers learning data to be monitored (step S302). The data registration processing unit 132 of the portal server 10 stores, for example, learning data (normal data) received from the user terminal 20 in the learning data storage unit 123.

Next, the portal server 10 generates a learning model to be monitored from the learning data (step S303). The learning processing unit 134 of the portal server 10, for example, acquires the specified learning data from the learning data storage unit 123 as learning data, and creates a learning model (for example, a learning model for detecting abnormality signs) from the learning data. ) is generated. The learning processing unit 134 stores the generated learning model in the learning model storage unit 126. After the process of step S303, the portal server 10 ends the learning model generation process.
In this way, in the abnormality sign analysis, it is assumed that the learning model is stored (registered) in the learning model storage unit 126 in advance.

Next, with reference to FIG. 16, the processing operation of the abnormality sign analysis of the monitoring support system 1 according to this embodiment will be described.
FIG. 16 is a diagram illustrating an example of the processing operation of the abnormality sign analysis of the monitoring support system 1 according to the present embodiment.

In FIG. 16, the processing from step S401 to step S410 is the same as the processing from step S101 to step S110 shown in FIG. 8 described above, so the description thereof will be omitted here.
Note that, in step S410, the terminal control unit 25 causes the display unit 23 to display, for example, an analysis and report screen as shown in FIG. 17 received via the NW communication unit 21.

FIG. 17 is a diagram showing an example of an analysis and report screen in abnormality symptom analysis of the monitoring support system 1 according to the present embodiment.
Screen G6 shown in FIG. 17 shows an analysis and report screen in abnormality sign analysis. In the screen G6, an analysis information list LS1 shows a list of analysis information for waveform comparison. Furthermore, the analysis information list LS2 shows a list of analysis information for abnormality sign analysis. Further, button BT5 indicates a selection button for abnormality sign analysis, and button BT3 indicates a switching button for analysis processing.

Returning to the explanation of FIG. 16 again, next, the user terminal 20 transmits designation information for abnormality sign analysis to the portal server 10 (step S411). Here, it is assumed that abnormality symptom analysis has been specified and the switching button (button BT3) has been pressed on the analysis and report screen (screen G6) shown in FIG. 25 transmits designation information for abnormality sign analysis to the portal server 10 via the NW communication unit 21.

Next, the portal server 10 transmits a data input screen for abnormality sign analysis to the user terminal 20 (step S412). The web processing unit 131 transmits a data input screen for abnormality sign analysis to the user terminal 20 via the NW communication unit 11 in accordance with the abnormality sign analysis specification information received from the user terminal 20 .

Next, the user terminal 20 displays a data input screen for abnormality sign analysis (step S413). The terminal control unit 25 causes the display unit 23 to display a data input screen for abnormality sign analysis received via the NW communication unit 21.

Next, the user terminal 20 transmits input data (model designation information and analysis data) for abnormality sign analysis to the portal server 10 (step S414). Here, for example, a title, model specification information, and analysis data are inputted via the input unit 22 on a data input screen for abnormality sign analysis, and the terminal control unit 25 inputs the input data for abnormality sign analysis (model specification information and analysis data) to the portal server 10 via the NW communication unit 21.

Next, the portal server 10 transmits an analysis start screen (number of possible analyses, etc.) to the user terminal 20 (step S415). The Web processing unit 131 transmits an analysis start screen (number of possible analyses, etc.) to the user terminal 20 via the NW communication unit 11 in response to the start of the analysis process. Note that the data registration processing unit 132 stores the received analysis data in the analysis data storage unit 125 by associating the group ID, user ID, and monitoring target ID, as shown in FIG. 6, for example. . Further, the monitoring registration processing unit 133 stores setting information of the monitoring target in the monitoring setting storage unit 124, for example, as shown in FIG.

Next, the user terminal 20 displays an analysis start screen (step S416). The terminal control unit 25 causes the display unit 23 to display, for example, an analysis start screen as shown in FIG. 12 received via the NW communication unit 21.

Next, the portal server 10 executes abnormality sign analysis processing (step S417). The analysis processing unit 135 of the portal server 10 executes abnormality sign analysis processing. Furthermore, the report processing unit 136 generates report information based on the analysis results of the abnormality sign analysis process. Note that details of the analysis process of abnormality sign analysis and the report information generation process will be described later with reference to FIG. 18.

Next, the portal server 10 transmits the analysis and report screen with the added report to the user terminal 20 (step S418). Upon completion of the analysis process, the web processing unit 131 transmits the analysis and report screen to which the report has been added to the user terminal 20 via the NW communication unit 11.

Next, the user terminal 20 displays an analysis and report screen with the added report (step S419). The terminal control unit 25 causes the display unit 23 to display the analysis and report screen received via the NW communication unit 21. Note that the analysis and report screen is the same as that shown in FIG. 13 described above, so a description thereof will be omitted here. Furthermore, in the case of abnormality sign analysis, the added report is added to the analysis information list LS2, which is a list of analysis information for abnormality sign analysis in FIG. 17, for example.

Further, when the analysis processing unit 135 completes the analysis (abnormality sign analysis) of the newly added monitoring target, the web processing unit 131 converts the analysis information of the newly added monitoring target into the analysis information. It is added to the top of the list, and causes the user terminal 20 to output notification information indicating that a new monitoring target has been added to the list of analysis information.

Next, details of the abnormality sign analysis process will be described with reference to FIG. 18.
FIG. 18 is a flowchart illustrating an example of an abnormality sign analysis process of the portal server 10 in this embodiment. The processing shown in FIG. 18 corresponds to the processing in step S415, step S417, and step S418 in FIG. 16 described above.

In FIG. 18, the processing from step S501 to step S504 is the same as the processing from step S201 to step S204 shown in FIG. 14 described above, so the description thereof will be omitted here.

In step S505, the analysis processing unit 135 analyzes signs of abnormality in the analysis data using the learning model of the specified monitoring target. The analysis processing unit 135 analyzes abnormality signs in the analysis data using, for example, the technique described in International Publication No. 2018/207350. The analysis processing unit 135 causes the analysis result storage unit 127 to store the analysis result.

Next, the report processing unit 136 generates a report based on the abnormality sign analysis results (step S506). The report processing unit 136 generates information such as the report RP1 shown in FIG. 7 and the report RP1 shown in FIG. 13, for example. The report processing unit 136 causes the report information storage unit 128 to store the generated report.

The subsequent processes in step S507 and step S508 are similar to the processes in step S208 and step S209 shown in FIG. 14 described above, so the description thereof will be omitted here.

Next, with reference to FIG. 19, the analysis report display processing and deletion processing of the monitoring support system 1 according to this embodiment will be described.
FIG. 19 is a diagram illustrating an example of analysis report display processing and deletion processing of the monitoring support system 1 according to the present embodiment.

As shown in FIG. 19, in the analysis report display process, first, as shown in step S601, while the user terminal 20 is displaying the analysis and report screen, the user specifies a specific report. be done.

The user terminal 20 transmits report specification information to the portal server 10 (step S602). Here, assuming that a specific report has been specified by the user via the input unit 22, the terminal control unit 25 sends report specification information specifying the specific report to the portal via the NW communication unit 21. Send to server 10.

Next, the portal server 10 transmits an analysis report (step S603). In accordance with the report specification information received from the user terminal 20, the web processing unit 131 of the portal server 10 obtains an analysis report corresponding to the report specification information from the report information storage unit 128. Here, the analysis report is report information such as report RP1 shown in FIG. 7, for example. The web processing unit 131 transmits the analysis report (for example, report RP1) acquired from the report information storage unit 128 to the user terminal 20.

Next, the user terminal 20 displays the analysis report (step S604). The terminal control unit 25 of the user terminal 20 displays, for example, an analysis report (for example, report RP1) as shown in FIG. 7 on the display unit 23.
In this way, when the user terminal 20 selects a specific monitoring target from the list of analysis information, the web processing unit 131 sends report information indicating the difference between normal data and analysis data to the user terminal 20. Output to .

Here, with reference to FIG. 20, a comparison between normal data in the analysis report and analysis data will be described.
FIG. 20 is a diagram showing a comparative example of analysis data of an analysis report of the monitoring support system 1 according to the present embodiment. Further, FIG. 20 is an enlarged view of the learning data DT1 and the analysis data DT2 of the report RP1 shown in FIG. 7 described above.

In FIG. 20, waveform W1 shows the waveform of learning data (normal data), and waveform W2 shows the waveform of analysis data. Furthermore, the broken line portion of the waveform W2 indicates the abnormality sign portion AB1.

As shown in FIG. 20, the report processing unit 136 generates report information in which signs of deviation (abnormality sign portions) are highlighted with broken lines. In the example shown in Fig. 20, signs of deviation (abnormality sign areas) are emphasized using broken lines, but signs of deviation can be highlighted using other techniques, such as changing thick lines, changing line colors, or changing line types. (Abnormality sign part) may be emphasized.

Returning to the explanation of FIG. 19, in the report deletion process, first, as shown in step S611, while the user terminal 20 is displaying the analysis and report screen, the user specifies a specific report. , a delete operation is input.

In this case, the user terminal 20 transmits a request to delete the specified report to the portal server 10 (step S612). Here, assuming that a specific report has been designated by the user via the input unit 22, the terminal control unit 25 transmits a specific report deletion request to the portal server 10 via the NW communication unit 21. .

Next, the portal server 10 deletes the specified report (step S613). The web processing unit 131 of the portal server 10 deletes the registration of the monitoring target corresponding to the specified report from the monitoring setting storage unit 124, and also deletes the specified report from the analysis information list (report list). . Note that the web processing unit 131 may delete the analysis results and report information corresponding to the specified report from the analysis result storage unit 127 and the report information storage unit 128.

Next, the portal server 10 transmits the analysis and report screen with the report deleted to the user terminal 20 (step S614). The web processing unit 131 of the portal server 10 transmits an analysis and report screen in which the specified report is deleted from the list of analysis information (list of reports) to the user terminal 20 via the NW communication unit 11.

Next, the user terminal 20 displays an analysis and report screen (step S615). The terminal control unit 25 of the user terminal 20 displays on the display unit 23 the analysis and report screen from which the specified report has been deleted.

Next, with reference to FIG. 21, a modified example of data in the user information storage unit 122 in this embodiment will be described.
FIG. 21 is a diagram showing a modified example of data in the user information storage unit 122 in this embodiment.

As shown in FIG. 21, the user information storage unit 122 may store the number of times analysis is possible and the number of times analysis is performed for each user. In this case, the web processing unit 131 determines that the number of executions of the analysis process for the user has reached the limit number of executions, based on the number of possible analyzes and the number of executions of analysis set for each user stored in the user information storage unit 122. Determine whether it has been reached. When the number of executions of the analysis process by the user reaches the execution limit number of times, the web processing unit 131 prohibits the user from executing the analysis process.

As described above, the monitoring support system 1 according to the present embodiment includes the analysis processing section 135 and the web processing section 131 (output processing section). The analysis processing unit 135 analyzes the acquired data of the monitoring target based on a learning model generated using normal data of the monitoring target registered in advance (for example, various monitored equipment of a plant, etc.) as learning data. . The web processing unit 131 (output processing unit) generates a list of analysis information (for example, a list of reports) that is the analysis result analyzed by the analysis processing unit 135 and allows comparison of the analysis results corresponding to each of a plurality of monitoring targets. and output it to the user terminal 20 used by the user.

Thereby, the monitoring support system 1 according to the present embodiment can confirm analysis information while comparing a plurality of monitoring targets, and can collectively monitor a plurality of monitoring targets. Therefore, the monitoring support system 1 according to the present embodiment can reduce the work load of monitoring and improve work efficiency.

Further, the monitoring support system 1 according to the present embodiment includes a learning processing section 134, an analysis processing section 135, and a web processing section 131 (output processing section). The learning processing unit 134 uses, as learning data, the normal data of the monitoring target received from the user terminal 20 used by the user, and generates a learning model for comparison and determination based on the learning data. The analysis processing unit 135 compares the normal data with the analysis data of the monitoring target received from the user terminal 20 used by the user, based on the learning model, and analyzes the analysis data. The web processing unit 131 (output processing unit) converts the analysis results analyzed by the analysis processing unit 135 and corresponds to each of the plurality of monitoring targets into a list of comparative analysis information, and outputs the analysis results to the user terminal 20. Output to .

Thereby, the monitoring support system 1 according to the present embodiment can accurately compare normal data and analytical data without requiring special expertise. Therefore, the monitoring support system 1 according to the present embodiment can reduce the work load of monitoring and improve work efficiency.

Further, the monitoring support system 1 according to the present embodiment includes a monitoring setting storage section 124 and a monitoring registration processing section 133. The monitoring setting storage unit 124 stores a monitoring object ID (monitoring object identification information) that identifies a monitoring object and setting information regarding the monitoring object in association with each other. The monitoring registration processing unit 133 responds to a monitoring target addition request received from the user terminal 20 (for example, a monitoring target analysis request (analysis processing execution request), a learning model generation request, etc.). Setting information of the corresponding monitoring target is added to the monitoring setting storage unit 124. The web processing unit 131 adds the monitoring target added to the monitoring setting storage unit 124 to the list of analysis information, and causes the user terminal 20 to output the list.

As a result, the monitoring support system 1 according to the present embodiment can easily add monitoring targets, thereby reducing the monitoring work load and further improving work efficiency.

Further, in the present embodiment, when the analysis processing unit 135 completes the analysis of the newly added monitoring target, the web processing unit 131 converts the analysis information of the newly added monitoring target into the analysis information. It is added to the top of the list, and causes the user terminal 20 to output notification information indicating that a new monitoring target has been added to the list of analysis information.

As a result, the monitoring support system 1 according to the present embodiment is notified that the analysis process has been completed, and the analysis information of the newly added monitoring target is added to the top of the list of analysis information. You can quickly and efficiently check the analysis information added to the monitoring target.

In the present embodiment, the monitoring setting storage unit 124 also stores a group ID (group identification information) that identifies a group to which a user belongs, a user ID (user identification information) that identifies a user, and a monitoring target. The ID and setting information are stored in association with each other. The web processing unit 131 causes the user terminal 20 to output a list of analysis information corresponding to the user ID or a list of analysis information corresponding to the group ID.

As a result, in the monitoring support system 1 according to the present embodiment, monitoring targets are managed for each group ID, so that, for example, know-how within a group such as a company will not be leaked to other groups. Further, since the monitoring support system 1 according to the present embodiment is operated by the portal server 10, a group such as a company does not need to prepare its own equipment and can receive services. That is, the monitoring support system 1 according to the present embodiment does not require a group such as a company to own the system itself, and can suppress capital investment costs.
Therefore, the monitoring support system 1 according to the present embodiment can easily and safely introduce a system related to monitoring of a plant to be monitored.

Further, in this embodiment, the web processing unit 131 extracts analysis information corresponding to the search information from the list of analysis information according to the search information received from the user terminal 20, and extracts analysis information corresponding to the search information from the list of analysis information. The list is output to the user terminal 20 as a search result.

As a result, the monitoring support system 1 according to the present embodiment can appropriately search for analysis information using search information, thereby further improving the efficiency of monitoring operations.

Further, the monitoring support system 1 according to the present embodiment includes a data registration processing section 132. The data registration processing unit 132 stores the acquired data of the monitoring target received from the user terminal 20 in the analysis data storage unit 125 as analysis data. The analysis processing unit 135 analyzes abnormality signs in the analysis data stored in the analysis data storage unit 125 based on the learning model.

As a result, the monitoring support system 1 according to the present embodiment can easily detect signs of abnormality, thereby further improving the efficiency of monitoring operations.

Furthermore, in the present embodiment, when a specific monitoring target is selected by the user terminal 20 from the list of analysis information, the web processing unit 131 uses report information indicating the difference between normal data and analysis data. output to the user terminal 20.

Thereby, the monitoring support system 1 according to the present embodiment can monitor the occurrence of abnormality by comparing normal data and analysis data, and can further improve the efficiency of monitoring work.

Furthermore, the monitoring support system 1 according to this embodiment includes a report processing unit 136 that generates report information. The analysis processing unit 135 predicts a discrepancy between normal data and analysis data, and determines a sign of the discrepancy. The report processing unit 136 generates report information that emphasizes signs of deviation.

As a result, the monitoring support system 1 according to the present embodiment can appropriately determine the signs of deviation, and in order to emphasize the signs of abnormality, the monitor (worker) can appropriately learn the signs of abnormality. be able to. Therefore, the monitoring support system 1 according to the present embodiment can improve the level of the monitoring staff (workers) and improve the quality of monitoring work.

Furthermore, the monitoring support system 1 according to the present embodiment includes a learning processing unit 134 that generates a learning model based on learning data. The analysis processing unit 135 analyzes the acquired data of the monitoring target based on the learning model generated by the learning processing unit 134.

As a result, the monitoring support system 1 according to the present embodiment can easily generate a learning model, and therefore can easily introduce abnormality detection of a monitoring target using a learning model.

Furthermore, in the present embodiment, the analysis processing unit 135 uses the learning model specified by the user terminal 20 from among the learning model generated by the learning processing unit 134 and the learning model prepared in advance. Analyze the acquired data of the monitored target.

Thereby, the monitoring support system 1 according to the present embodiment can easily change the learning model and try it out, so it can flexibly respond to various types of monitoring targets.

Further, the monitoring support system 1 according to the present embodiment includes a group information storage section 121, an analysis processing section 135, and a web processing section 131 (restriction processing section). The group information storage unit 121 stores a group ID (group identification information) that identifies a group to which a user belongs, and restriction information regarding analysis processing for analyzing acquired data to be monitored, in association with each other. The analysis processing unit 135 executes analysis processing based on a learning model generated using normal data to be monitored as learning data in response to an analysis request from the user terminal 20 used by the user. The web processing unit 131 (restriction processing unit) controls the user's usage, including the execution of analysis processing, based on the restriction information stored in the group information storage unit 121 and corresponding to the group to which the user belongs. limit.

As a result, since the monitoring support system 1 according to the present embodiment is managed by the group information storage unit 121 for each group such as a company, it is possible to easily monitor a monitoring target with high precision using a learning model. Moreover, it can be introduced safely. Therefore, the monitoring support system 1 according to the present embodiment can reduce the work load of monitoring and improve work efficiency.

Further, the monitoring support system 1 according to the present embodiment can appropriately restrict use by users using restriction information. Therefore, the monitoring support system 1 according to the present embodiment can appropriately distribute the resources of the portal server 10, and can reduce the system load caused by uneven use by some users. Therefore, the monitoring support system 1 according to the present embodiment can comfortably analyze the monitoring target and improve business efficiency.

Further, in this embodiment, the limit information includes a limit number of executions of analysis processing set for each group. The web processing unit 131 prohibits users belonging to the group from executing the analysis process when the number of executions of the analysis process in the group reaches the execution limit number of times.

Thereby, the monitoring support system 1 according to the present embodiment can appropriately restrict usage by users for each group based on the number of executions of the analysis process, and can reduce the system load.

Further, in this embodiment, the limit information includes an upper limit number of signals for acquisition data set for each group. The Web processing unit 131 limits use by users belonging to the group when the number of signals of acquired data used for analysis processing reaches the upper limit number of signals (for example, the number of contracted signals).

Thereby, the monitoring support system 1 according to the present embodiment can appropriately limit usage by users for each group based on the upper limit signal number of acquired data, and can reduce system load.

Further, the monitoring support system 1 according to the present embodiment includes a user information storage unit 122 that stores at least a group ID (group identification information) and a user ID (user identification information) for identifying a user in association with each other. Be prepared. The limit information includes the upper limit number of users set for each group. The web processing unit 131 limits the registration of users belonging to the group when the number of users belonging to the group stored in the user information storage unit 122 reaches the upper limit number of users (number of accounts). .

Thereby, the monitoring support system 1 according to the present embodiment can appropriately limit the use of users for each group based on the upper limit number of users, and can reduce the system load.

Furthermore, in the present embodiment, the limit information includes a limit number of executions of analysis processing set for each user. The web processing unit 131 prohibits the user from executing the analysis process when the number of times the user has executed the analysis process reaches the execution limit number of times.

As a result, the monitoring support system 1 according to the present embodiment can appropriately limit the usage of each user based on the number of executions of the analysis process for each user, and can reduce the system load.

Furthermore, in this embodiment, the restriction information includes a usage period for analysis processing set for each group. The web processing unit 131 restricts the use of users belonging to the group when the usage period of analysis processing reaches its usage limit.

Thereby, the monitoring support system 1 according to the present embodiment can appropriately restrict usage by users for each group based on the usage period for each group, and can reduce the system load.

Further, in this embodiment, the web processing unit 131 cancels the usage restriction when an additional usage fee is paid by the group.
Thereby, the monitoring support system 1 according to the present embodiment can appropriately release usage restrictions for the user and improve convenience.

Further, the portal server 10 (monitoring support device) according to this embodiment includes an analysis processing section 135 and a web processing section 131 (output processing section). The analysis processing unit 135 analyzes the acquired data of the monitoring target based on a learning model generated using preregistered normal data of the monitoring target as learning data. The web processing unit 131 makes a list of analysis information that can be compared with the analysis results analyzed by the analysis processing unit 135 and corresponds to each of the plurality of monitoring targets, and displays the analysis results on the user terminal 20 used by the user. Output to .

Thereby, the portal server 10 (monitoring support device) according to this embodiment can achieve the same effects as the above-mentioned monitoring support system 1, reduce the workload of monitoring, and improve business efficiency.

Further, the monitoring support method according to the present embodiment is a monitoring support method for the portal server 10 including an analysis processing section 135 and a web processing section 131, and includes an analysis processing step and an output processing step. In the analysis processing step, the analysis processing unit 135 analyzes the acquired data of the monitoring target based on a learning model generated using preregistered normal data of the monitoring target as learning data. In the output processing step, the web processing unit 131 creates a list of analysis information that can be compared with the analysis results analyzed by the analysis processing unit 135 and corresponds to each of the plurality of monitoring targets, and makes the list of analysis information available for comparison to the user. output to the user terminal 20.

Thereby, the monitoring support method according to this embodiment can achieve the same effects as the above-mentioned monitoring support system 1, reduce the work load of monitoring, and improve work efficiency.

Further, the portal server 10 (monitoring support device) according to this embodiment includes a learning processing section 134, an analysis processing section 135, and a web processing section 131 (output processing section). The learning processing unit 134 uses, as learning data, the normal data of the monitoring target received from the user terminal 20 used by the user, and generates a learning model for comparison and determination based on the learning data. The analysis processing unit 135 compares the normal data with the analysis data of the monitoring target received from the user terminal 20 used by the user, based on the learning model, and analyzes the analysis data. The web processing unit 131 (output processing unit) converts the analysis results analyzed by the analysis processing unit 135 and corresponds to each of the plurality of monitoring targets into a list of comparative analysis information, and outputs the analysis results to the user terminal 20. Output to .

Thereby, the portal server 10 (monitoring support device) according to this embodiment can achieve the same effects as the above-mentioned monitoring support system 1, reduce the workload of monitoring, and improve business efficiency.

Further, the monitoring support method according to the present embodiment is a monitoring support method for the portal server 10 including a learning processing section 134, an analysis processing section 135, and a web processing section 131, and includes a learning processing step and an analysis processing step. , and an output processing step. In the learning processing step, the learning processing unit 134 uses normal data of the monitoring target received from the user terminal 20 used by the user as learning data, and generates a learning model for comparison and determination based on the learning data. In the analysis processing step, the analysis processing unit 135 analyzes the analysis data by comparing the normal data and the analysis data of the monitoring target received from the user terminal 20 used by the user based on the learning model. In the output processing step, the web processing unit 131 creates a list of analysis information that can be compared with the analysis results analyzed by the analysis processing unit 135 and corresponds to each of the plurality of monitoring targets, and outputs the analysis results to the user terminal 20. Output to .

Thereby, the monitoring support method according to this embodiment can achieve the same effects as the above-mentioned monitoring support system 1, reduce the work load of monitoring, and improve work efficiency.

Further, the portal server 10 (monitoring support device) according to the present embodiment includes a group information storage section 121, an analysis processing section 135, and a web processing section 131. The group information storage unit 121 stores a group ID for identifying a group to which a user belongs, and restriction information regarding an analysis process for analyzing acquired data to be monitored, in association with each other. The analysis processing unit 135 executes analysis processing based on a learning model generated using normal data to be monitored as learning data in response to an analysis request from the user terminal 20 used by the user. The web processing unit 131 restricts the user's use, including the execution of analysis processing, based on the restriction information stored in the group information storage unit 121 and corresponding to the group to which the user belongs.

As a result, the portal server 10 (monitoring support device) according to the present embodiment has the same effect as the above-mentioned monitoring support system 1, and can appropriately restrict the use of the user by the restriction information. analysis can be performed comfortably and work efficiency can be improved.

In addition, the monitoring support method according to the present embodiment includes a group information storage unit 121 that stores group IDs and restriction information related to analysis processing for analyzing acquired data of a monitoring target in association with each other, an analysis processing unit 135, and a web processing unit. The method includes an analysis processing step and a restriction processing step. In the analysis processing step, the analysis processing unit 135 executes analysis processing based on a learning model generated using normal data to be monitored as learning data in response to an analysis request from the user terminal 20 used by the user. do. In the restriction processing step, the web processing unit 131 controls the user's usage, including execution of analysis processing, based on the restriction information stored in the group information storage unit 121 and corresponding to the group to which the user belongs. limit.

As a result, the monitoring support method according to the present embodiment has the same effect as the above-mentioned monitoring support system 1, and the use of the user can be appropriately restricted by the restriction information, so that analysis of the monitored target can be performed comfortably. This can improve work efficiency.

Note that the present disclosure is not limited to the above-described embodiments, and can be modified without departing from the spirit of the present disclosure.
For example, in the above embodiment, an example has been described in which the portal server 10 is configured with one server device, but the portal server 10 is not limited to this, and may be configured with a plurality of server devices, for example. .

Further, in the above embodiment, part or all of the server storage unit 12 may be provided outside the portal server 10. Further, part of the functions of the server control unit 13 may be provided outside the portal server 10.

Furthermore, in the above embodiment, an example was described in which the web processing unit 131 executes processing for adding and deleting analysis information of a monitoring target to a list of analysis information of monitoring targets, and search processing using search information. For example, other operation processing such as rearrangement processing of analysis information to be monitored may be executed.

Furthermore, in the embodiments described above, the plurality of monitoring targets may include equipment operated by different managers or maintenance companies. Further, the plurality of monitoring targets may include mutually different in-building facilities (e.g., elevators, air conditioners, surveillance cameras). Furthermore, the multiple monitoring targets include different types of power generation facilities (for example, thermal power, wind power, hydropower, nuclear power, etc.), and the monitoring support system 1 may display the analysis information of these in a list. .

Furthermore, in the above embodiment, the plurality of monitoring targets include service demand information and equipment used for service supply, and the monitoring support system 1 may display this analysis information in a list. . Further, the plurality of monitoring targets may include power generation equipment and power transmission equipment. Further, the monitoring support system 1 may manage a supply chain (for example, fuel procurement, power generation, power transmission, etc.) using a plurality of monitoring targets.

Note that each component included in the monitoring support system 1 described above has a computer system therein. Then, a program for realizing the functions of each component of the monitoring support system 1 described above is recorded on a computer-readable recording medium, and the program recorded on this recording medium is read into the computer system and executed. Accordingly, processing in each configuration included in the monitoring support system 1 described above may be performed. Here, "reading a program recorded on a recording medium into a computer system and executing it" includes installing the program on the computer system. The "computer system" herein includes an OS and hardware such as peripheral devices.

Furthermore, a "computer system" may include a plurality of computer devices connected via a network including communication lines such as the Internet, WAN, LAN, and dedicated lines. Furthermore, the term "computer-readable recording medium" refers to portable media such as flexible disks, magneto-optical disks, ROMs, and CD-ROMs, and storage devices such as hard disks built into computer systems. In this way, the recording medium storing the program may be a non-transitory recording medium such as a CD-ROM.

The recording medium also includes a recording medium provided internally or externally that can be accessed from the distribution server for distributing the program. Note that the program may be divided into a plurality of programs, each downloaded at different timings, and then combined into each component of the monitoring support system 1, or the distribution servers that distribute each of the divided programs may be different. Furthermore, a "computer-readable recording medium" refers to a storage medium that retains a program for a certain period of time, such as volatile memory (RAM) inside a computer system that serves as a server or client when a program is transmitted via a network. This includes those who are present. Moreover, the above-mentioned program may be for realizing a part of the above-mentioned functions. Furthermore, it may be a so-called difference file (difference program) that can realize the above-mentioned functions in combination with a program already recorded in the computer system.

1... Monitoring support system, 10... Portal server, 11, 21... NW communication section, 12... Server storage section, 13... Server control section, 20, 20-1, 20-2... User terminal, 22... Input section, 23... Display section, 24... Terminal storage section, 25... Terminal control section, 121... Group information storage section, 122... User information storage section, 123... Learning data storage section, 124... Monitoring setting storage section, 125... Analysis data Storage section, 126... Learning model storage section, 127... Analysis result storage section, 128... Report information storage section, 131... Web processing section, 132... Data registration processing section, 133... Monitoring registration processing section, 134... Learning processing section, 135... Analysis processing unit, 136... Report processing unit, C1, C2... Company, H11, H21... NW adapter, H12, H22... Memory, H13, H23... Processor, H24... Input device, H25... Display, NW1... Network

Claims (9)

A file name of a file that stores acquired data of a monitoring target that is plant equipment registered by a user, the acquired data stored in the file, and group identification information that identifies the group to which the user belongs. , an analysis data storage unit that stores user identification information for identifying the user and monitoring target identification information for identifying the monitoring target in association with each other;
a group information storage unit that stores the group identification information and restriction information regarding analysis processing for analyzing the acquired data in association with each other;
The acquired data stored in the analysis data storage unit is analyzed based on a learning model generated using the normal data of the monitoring target as learning data in response to an analysis request from a user terminal used by the user. an analysis processing unit that executes analysis processing;
an analysis result storage unit that stores the group identification information, the user identification information, the monitoring target identification information, and the analysis result of the analysis process in association with each other;
Restriction processing that restricts the use of the user, including execution of the analysis process, based on the restriction information stored in the group information storage unit and that corresponds to the group to which the user belongs. A monitoring support system equipped with a department and a department. The limit information includes a limit number of executions of the analysis process set for each group,
The restriction processing unit prohibits the user belonging to the group from executing the analysis process when the number of executions of the analysis process in the group reaches the execution limit number of times. The monitoring support system described in . The limit information includes an upper limit number of signals for the acquired data set for each group,
According to claim 1 or claim 2, the restriction processing unit restricts the use of the user belonging to the group when the number of signals of the acquired data used for the analysis process reaches the upper limit number of signals. Monitoring support system as described. a user information storage unit that stores at least the group identification information and user identification information for identifying the user;
The limit information includes an upper limit number of users set for each group,
The restriction processing unit restricts registration of the users belonging to the group when the number of the users belonging to the group stored in the user information storage unit reaches the upper limit number of users. The monitoring support system according to any one of claims 1 to 3. The limit information includes a limit number of executions of the analysis process set for each user,
The restriction processing unit prohibits the user from executing the analysis process when the number of executions of the analysis process by the user reaches the execution limit number of times. The monitoring support system according to any one of the above. The restriction information includes a usage deadline for the analysis processing set for each group,
The restriction processing unit restricts the use of the user belonging to the group when the usage period of the analysis process reaches the usage time limit. Surveillance support system. The monitoring support system according to any one of claims 1 to 6, wherein the restriction processing unit releases the usage restriction when an additional usage fee is paid by the group. A file name of a file that stores acquired data of a monitoring target that is plant equipment registered by a user, the acquired data stored in the file, and group identification information that identifies the group to which the user belongs. , an analysis data storage unit that stores user identification information for identifying the user and monitoring target identification information for identifying the monitoring target in association with each other;
a group information storage unit that stores the group identification information and restriction information regarding analysis processing for analyzing the acquired data in association with each other;
The acquired data stored in the analysis data storage unit is analyzed based on a learning model generated using the normal data of the monitoring target as learning data in response to an analysis request from a user terminal used by the user. an analysis processing unit that executes analysis processing;
an analysis result storage unit that stores the group identification information, the user identification information, the monitoring target identification information, and the analysis result of the analysis process in association with each other;
Restriction processing that restricts use of the user, including execution of the analysis process, based on the restriction information stored in the group information storage unit and that corresponds to the group to which the user belongs. A monitoring support device comprising a part and a part. A file name of a file that stores acquired data of a monitoring target that is plant equipment registered by a user, the acquired data stored in the file, and group identification information that identifies the group to which the user belongs. , an analysis data storage unit that stores user identification information that identifies the user and monitoring object identification information that identifies the monitoring object in association with each other, group identification information that identifies the group, and the acquired data; A monitoring support method for a monitoring support device comprising: a group information storage unit that associates and stores restriction information regarding analysis processing to be analyzed; an analysis processing unit; and a restriction processing unit.
The analysis processing unit analyzes the acquired data stored in the analysis data storage unit in response to an analysis request from a user terminal used by the user, and performs learning that is generated using normal data of the monitoring target as learning data. performing the analysis process based on the model;
a step in which the analysis processing unit stores the group identification information, the user identification information, the monitoring target identification information, and the analysis result of the analysis process in an analysis result storage unit in association with each other;
The restriction processing unit is configured to perform processing of the user, including execution of the analysis process, based on the restriction information stored in the group information storage unit and corresponding to the group to which the user belongs. A monitoring aid method comprising steps for restricting use.

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