JP7784964B2 - Monitoring system, monitoring method and program - Google Patents

Description

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

When monitoring the operational status of large-scale systems such as large-scale plants and facilities, it is common to develop a monitoring program for each subsystem due to the large amount of information handled and the ability to manage and monitor on a subsystem-by-subsystem basis. However, due to differences in development schedules and budgets for individual monitoring programs, functional alignment between monitoring programs is often insufficient. For example, for parameters that cannot be measured by sensors, the monitoring program may estimate their values, but different monitoring programs may use different estimation methods for the same parameter. Furthermore, because each monitoring program is developed assuming the normal operating status of other subsystems, it often does not address how to handle abnormalities in other subsystems. Even if sufficient alignment is achieved during the design of monitoring programs, subsequent changes in functionality or the need for new features can render the original design inappropriate for the current situation. To address these issues, making the data handled by each monitoring program available to other monitoring programs makes it easier to expand functionality to meet emerging needs and to coordinate functions between monitoring programs. Furthermore, integrating the monitoring results of multiple monitoring programs can be useful for determining the operational status of the entire large-scale system.

As a related technique, Patent Document 1 discloses a method for integrating and outputting the diagnostic results and estimated causes of abnormalities from multiple expert systems in an abnormality diagnosis device for a nuclear power plant.

Japanese Patent Application Publication No. 4-346033

There is a need for technology that enables data sharing so that data handled by individually developed monitoring programs can be used by other monitoring programs, or handled comprehensively.

The present disclosure provides a monitoring system, a monitoring method, and a program that can solve the above problems.

The monitoring system according to the present disclosure is a monitoring system for monitoring a system including multiple subsystems, and includes a first monitoring device running a first monitoring program for monitoring a first subsystem, a second monitoring device running a second monitoring program for monitoring a second subsystem, and an integrated platform, wherein the integrated platform includes an acquisition unit that acquires data of the monitoring target or the monitoring result from the first monitoring device, a selection unit that selects a second monitoring program that requires the data of the first monitoring program, an output unit that outputs the data acquired from the first monitoring device to the second monitoring device, a setting reception unit that accepts settings of logic for determining an abnormality in the first subsystem that is not included in the first monitoring program, and a determination unit that determines an abnormality in the first subsystem based on the data and the logic.

A monitoring method according to the present disclosure is a monitoring method for monitoring a system including a plurality of subsystems, and includes the steps of acquiring data of a monitoring target or a monitoring result from a first monitoring device running a first monitoring program for monitoring a first subsystem, selecting a second monitoring program for monitoring a second subsystem that requires the data of the first monitoring program, outputting the data acquired from the first monitoring device to a second monitoring device running a second monitoring program, accepting settings of logic for determining an abnormality in the first subsystem that is not included in the first monitoring program, and determining an abnormality in the first subsystem based on the data and the logic.

A program according to the present disclosure causes a computer to execute the above-described monitoring method.

The integrated platform, monitoring system, monitoring information sharing method, and program disclosed herein enable the sharing of data handled by multiple monitoring programs developed independently.

1 is a block diagram illustrating an example of a monitoring system according to an embodiment. 1 is a block diagram illustrating an example of a monitoring device according to an embodiment. FIG. 10 is a diagram illustrating an example of data settings transmitted from the monitoring device to the integrated platform according to the embodiment. FIG. 10 is a diagram illustrating an example of data settings received by the monitoring device according to the embodiment from the integrated platform. FIG. 1 is a block diagram illustrating an example of an integrated platform according to an embodiment. FIG. 10 is a diagram illustrating an example of data management settings in the integrated platform according to the embodiment. FIG. 10 is a diagram illustrating an example of a determination criterion setting in the integrated platform according to the embodiment. FIG. 10 is a diagram illustrating an example of an integrated anomaly determination criterion in the integrated platform according to the embodiment. FIG. 10 is a diagram illustrating an integrated anomaly determination model in the integrated platform according to the embodiment. FIG. 10 is a block diagram illustrating an example of a monitoring system after a new monitoring program is added according to an embodiment. 10 is a flowchart illustrating an example of an operation of the integrated platform according to the embodiment. FIG. 1 illustrates an example of a hardware configuration of a monitoring system according to an embodiment.

<Embodiment>
The integrated platform of the present disclosure will be described below with reference to the drawings.
(Overall configuration of the monitoring system)
FIG. 1 is a block diagram illustrating an example of a monitoring system according to an embodiment.
The monitoring system 100 includes a facility 1 to be monitored, monitoring devices 10a to 10c, and an integrated platform 20. The facility 1 is a large-scale plant or facility. The facility 1 includes machines M1 to M3, a connection device C1 connecting the machines M1 and M2, a connection device C2 connecting the machines M1 and M3, and so on. For example, the facility 1 may be a nuclear plant, the machine M1 a tank, the machine M2 a nuclear reactor, and the connection device C1 a pump. The machines M1 to M3 and the connection devices C1 to C2 are equipped with sensors. For example, the machine M1 is equipped with sensors S1 and S2, the connection device C1 is equipped with sensors S3 and S4, the machine M2 is equipped with sensors S5 and S6, the machine M2 is equipped with sensors S7, and the machine M3 is equipped with a sensor S8. Note that the configuration of the facility 1, etc. shown in FIG. 1 is merely an example and is not limited thereto. For example, the facility 1 may include two or fewer machines, or four or more machines. The same applies to the number of connection devices and sensors.

Facility 1 is divided into multiple subsystems, such as a subsystem consisting of machine M1, a subsystem consisting of machine M2 and connected device C1, and a subsystem consisting of machine M3 and connected device C2, with each subsystem having its own dedicated monitoring program. Monitoring device 10a is connected to sensors S1 and S2. Monitoring program 12a is running in monitoring device 10a, and monitors the operating status of machine M1 by acquiring measurements from sensors S1 and S2. Similarly, monitoring device 10b is connected to sensors S3-6 and runs monitoring program 12b. Monitoring program 12b acquires measurements from sensors S3-6 and monitors the operating status of connected device C1 and machine M2. Monitoring device 10c is connected to sensors S7-8 and runs monitoring program 12c. Monitoring program 12c acquires measurements from sensors S7-8 and monitors the operating status of connected device C2 and machine M3. FIG. 1 illustrates an example in which monitoring programs 12a-12c run on monitoring devices 10a-10c, respectively, but there is no limitation on the devices on which monitoring programs 12a-12c run; for example, monitoring programs 12a-12c may be configured to run on a single monitoring device 10a. Furthermore, the division of subsystems is not limited to the above. For example, each of machine M1, machine M2, machine M3, connected device C1, and connected device C2 may be a subsystem, and a monitoring program 12 may be provided for each subsystem.

The integrated platform 20 is connected to the monitoring devices 10a-10c. The integrated platform 20 acquires from the monitoring device 10a the measurement values of sensors S1-S2, monitoring results (e.g., alerts issued by the monitoring program 12a), virtual sensor values calculated by the monitoring program 12a, and the like. Virtual sensor values are estimated values of physical quantities such as temperature at locations where an actual sensor cannot be installed or physical quantities that cannot be measured by a sensor. Similarly, the integrated platform 20 acquires from the monitoring device 10b the measurement values of sensors S3-S6, alerts issued by the monitoring program 12b, virtual sensor values, and the like, and from the monitoring device 10c the measurement values of sensors S7-S8, alerts issued by the monitoring program 12c, virtual sensor values, and the like. Regarding the acquisition of the measurement values of sensors S1-S8, the integrated platform 20 may be configured to connect to sensors S1-S8 and acquire the measurement values directly from sensors S1-S8. The integrated platform 20 integrates information obtained from the monitoring devices 10a-10c, performs abnormality detection and issues alerts that cannot be performed by the individual monitoring programs 12a-12c. The integrated platform 20 also controls the exchange of data so that sensor measurements and virtual sensor values used by one monitoring device 10 to monitor subsystems can also be used by other monitoring devices 10 and other systems, such as by providing information obtained from monitoring device 10a to monitoring devices 10b and 10c.

(Configuration of monitoring device)
FIG. 2 is a block diagram illustrating an example of a monitoring device according to an embodiment.
The monitoring device 10a includes a data acquisition unit 11a, a monitoring program 12a, an integrated platform collaboration unit 13a, and a storage unit 17a. Of these, the data acquisition unit 11a, the monitoring program 12a, and the storage unit 17a are functions that are originally included in the monitoring device 10a. The integrated platform collaboration unit 13a is a function required for collaboration with the integrated platform 20. When the integrated platform 20 is introduced into an existing monitoring system, the integrated platform collaboration unit 13a is additionally implemented in the monitoring device 10a.

The data acquisition unit 11a acquires the measured values of the sensors S1 and S2.
The monitoring program 12a monitors the machine M1. The monitoring program 12a is an existing program developed for monitoring the subsystem consisting of the machine M1. For example, the monitoring program 12a calculates a virtual sensor value based on the measurement values of the sensors S1 and S2, and determines whether the operating state of the machine M1 is normal or abnormal based on the measurement values of the sensors S1 and S2 and the virtual sensor value. For example, if the measurement value of the sensor S1 exceeds a threshold value, the monitoring program 12a determines that the operating state of the machine M1 is abnormal and issues an alert.

The integrated platform cooperation unit 13a controls the exchange of data with the integrated platform 20. The integrated platform cooperation unit 13a includes a setting reception unit 14a, a transmission unit 15a, and a reception unit 16a.
The setting reception unit 14a receives settings regarding what data is to be transmitted to the integrated platform 20 and what data is to be acquired from the integrated platform 20. Through the setting reception unit 14a, the user can arbitrarily set the content of the data to be transmitted and received.
The transmitter 15a transmits to the integrated platform 20 the measurement values of the sensors S1 to S2 acquired by the monitoring device 10a, the virtual sensor values calculated by the monitoring program 12a, alerts, etc., based on the transmission data settings received by the setting receiver 14a.
The receiving unit 16a acquires data from the integrated platform 20 based on the settings of the received data accepted by the setting accepting unit 14a. For example, when monitoring the machine M1, if the measured values of the sensor S8 belonging to another subsystem or the virtual sensor values calculated by the monitoring program 12c are required, the receiving unit 16a can acquire such information from the integrated platform 20.
The storage unit 17a stores the measurement values acquired by the data acquisition unit 11a and various setting information acquired by the setting reception unit 14a.

While Figure 2 illustrates the configuration of monitoring device 10a, the configurations of monitoring devices 10b and 10c are similar. Furthermore, in this specification, when no distinction is necessary, monitoring devices 10a-10c may be referred to simply as monitoring device 10, and data acquisition units 11a-11c may be referred to simply as data acquisition unit 11. The same applies to the other functional units (monitoring program 12a, integrated platform collaboration unit 13a, setting acceptance unit 14a, transmission unit 15a, reception unit 16a, and storage unit 17a).

Figure 3 shows an example of transmission data settings accepted by the setting acceptance unit 14a. In this example, the measurement value of sensor S1 (data ID = a-001), the measurement value of sensor S2 (data ID = a-002), and the virtual sensor value (data ID = a-003, with sensor ID = 12a-V1 set for the virtual sensor) are set as data to be sent to the integrated platform 20. The transmission unit 15a acquires the measurement values of sensors S1 and S2 acquired by the data acquisition unit 11a and transmits these measurement values to the integrated platform 20. The transmission unit 15a acquires the virtual sensor value (sensor ID = 12a-V1) calculated by the monitoring program 12a from the monitoring program 12a and transmits the virtual sensor value to the integrated platform 20.

Figure 4 shows an example of received data settings. In this example, the measurement value of sensor S7 (data ID = c-001) and the virtual sensor value (data ID = c-003, with sensor ID = 12c-V1 set for the virtual sensor) are set as data to be received from integrated platform 20. Receiving unit 16a receives the measurement value of sensor S7 and the virtual sensor value (sensor ID = 12c-V1) calculated by monitoring program 12c from integrated platform 20. Receiving unit 16a may request this data from integrated platform 20 and receive the data sent from integrated platform 20 in response to this request, or similar settings may be configured on integrated platform 20 and data sent by integrated platform 20 may be acquired based on these settings.

(Integrated platform configuration)
FIG. 5 is a block diagram illustrating an example of an integrated platform according to an embodiment.
The integrated platform 20 includes a data acquisition unit 21 , a setting reception unit 22 , a data provision unit 23 , a determination unit 24 , a comprehensive abnormality determination unit 25 , a notification unit 26 , and a storage unit 27 .
The data acquisition unit 21 acquires measurement values, virtual sensor values, alerts, etc. of the sensors S1 to S8 from the monitoring device 10. When the integrated platform 20 is connected to the sensors S1 to S8, the data acquisition unit 21 acquires measurement values directly from the sensors S1 to S8. The data acquisition unit 21 may also acquire inspection results such as periodic inspections of the machines M1 to M4 and connected devices C1 to C2 as alerts.
The setting reception unit 22 accepts settings such as settings for data to be managed by the integrated platform 20, settings for judgment conditions when anomaly judgment is performed by the integrated platform 20, and settings for judgment criteria for comprehensive anomaly judgment based on alerts issued by the monitoring device 10.
The data providing unit 23 transmits sensor measurement values, virtual sensor values, alerts, etc. obtained from a monitoring device 10 to other monitoring devices 10b to 10c (monitoring programs 12b to 12c) based on the settings (e.g., Figure 6) received by the setting receiving unit 22.
The determination unit 24 performs an abnormality determination for the equipment 1 based on the setting of the determination conditions (for example, FIG. 7) received by the setting reception unit 22, the sensor measurement values and the virtual sensor values acquired from the monitoring device 10. As will be described later, by using the determination unit 24, it becomes possible to perform an abnormality determination that is not executed by the monitoring programs 12a to 12c.
The comprehensive abnormality judgment unit 25 judges the operating status of the entire system (entire equipment 1) based on the settings of the comprehensive abnormality judgment criteria received by the setting reception unit 22 (e.g., Figure 8) and the alerts obtained from the monitoring programs 12a to 12c.
The notification unit 26 notifies the determination results by the determination unit 24 and the comprehensive abnormality determination unit 25. For example, the notification unit 26 displays the determination results on a display device or notifies another device (e.g., the monitoring device 10) of the determination results.
The storage unit 27 stores information such as the virtual sensor values acquired by the data acquisition unit 21, setting information accepted by the setting acceptance unit 22, and the like.

(Data management settings)
6 shows an example of settings for data managed by the integrated platform 20. The settings in FIG. 6 are examples of settings for data managed by the integrated platform 20 that are set by a user and accepted by the setting acceptance unit 22.
The setting in the first line of Fig. 6 (data ID = a-001) indicates that the measurement value of sensor S1 is acquired, stored, and transmitted to monitoring device 10b. When combined with the setting in the first line of Fig. 3, the data acquisition unit 11 of integrated platform 20 acquires the measurement value of sensor S1 from monitoring device 10a, and the data provision unit 23 transmits this measurement value to monitoring device 10b.
The setting on the second line of FIG. 6 (data ID = a-002) indicates that the measurement value of sensor S2 is acquired and stored. For example, if the data with data ID = a-002 is configured to be provided to the monitoring device 10b, the measurement value of sensor S2 can be transmitted to the monitoring device 10b. This allows the measurement value of sensor S2 to be used by the monitoring program 12b without modifying the equipment 1, even if the measurement value of sensor S2 is subsequently required for the monitoring program 12b. Furthermore, by utilizing the integrated platform collaboration unit 13b for the monitoring program 12b, there is no need to modify the interface that acquires the measurement value of sensor S2. For example, only the abnormality determination logic using the measurement value of sensor S2 needs to be modified, thereby reducing modification costs.

The same applies to the following settings. For example, when line 6 (data ID = c-001) and line 9 (data ID = c-003) are combined with the settings in Figure 4, the integrated platform 20 transmits the measurement value of sensor S7 and the virtual sensor value calculated by monitoring device 10c to monitoring device 10a. Conventionally, virtual sensor values calculated by monitoring device 10c were only available to monitoring device 10c, but by transmitting the virtual sensor values to another monitoring device 10a via the integrated platform 20, they can also be used by monitoring device 10a. For example, even virtual sensor values indicating the same physical quantity may be estimated differently by each monitoring program. However, by obtaining a virtual sensor value for the same physical quantity calculated by another monitoring program 12c and comparing it with the virtual sensor value calculated by the monitoring program itself (monitoring program 12a), it is possible to understand the value calculated using a different estimation method and use this information for monitoring purposes.

In this way, by sharing the monitored data (measurement values of sensors S1-S8, virtual sensor values) used by each monitoring program 12 and making it available to other monitoring programs, it is possible to improve irrational and inefficient monitoring caused by insufficient coordination between the functions of each monitoring program. The settings illustrated in FIG. 6 may be configured by the user, or the integrated platform 20 may collect the transmission data settings (FIG. 3) and reception data settings (FIG. 4) configured by the monitoring device 10 and aggregate them to generate the configuration data illustrated in FIG. 6. While FIG. 6 illustrates a case in which the sensor measurement values and virtual sensor values are managed by the integrated platform 20, for example, settings may be configured to send alerts issued by monitoring program 12a to monitoring programs 12b-12c, allowing monitoring programs 12b-12c to utilize the alerts issued by monitoring program 12a.

(Setting judgment conditions)
FIG. 7 shows an example of a setting of a judgment condition for an anomaly judgment performed in the integrated platform 20. The setting example shown in FIG. 7 is an example of a setting of a judgment condition set by a user and accepted by the setting acceptance unit 22. By making the setting example shown in FIG. 6 , it is possible to acquire sensor measurement values and virtual sensor values that could not be acquired previously on the monitoring program 12 side and perform new anomaly judgment. In this case, however, anomaly judgment logic must be added to the monitoring program 12. The setting in FIG. 7 is intended to enable new anomaly judgment to be performed by setting anomaly judgment logic in the integrated platform 20 without modifying the monitoring program 12. As a result, the anomaly judgment function can be added to the monitoring program 12 side simply by implementing the integrated platform cooperation unit 13 and configuring the transmission of sensor measurement values, etc. to the integrated platform 20.
The judgment condition in the first line of FIG. 7 indicates that if the measurement value of sensor S2 exceeds the threshold X1, a message stating "Abnormality sign detected on machine M1" is sent to the monitoring device 10b. According to this setting, the judgment unit 24 monitors the measurement value of sensor S2 acquired from the monitoring device 10a and determines whether the measurement value exceeds the threshold X1. If the measurement value of sensor S2 exceeds the threshold X1, the notification unit 26 sends the message to the monitoring device 10b set as the notification destination. This allows the monitoring program 12b to use the abnormality judgment results based on the measurement value of sensor S2 of another subsystem without modifying the equipment 1 or the monitoring program 12b. The sensor used for abnormality judgment and the value of threshold X1 can be arbitrarily set according to the purpose of the monitoring program 12b. Therefore, even if a new sensor is installed in the equipment 1, for example, abnormality judgment and abnormality sign detection based on the measurement value of the new sensor can be realized at low cost. In this way, by introducing the integrated platform 20, monitoring functions that are not provided in the monitoring program 12b (such as functions that were not necessary at the time of development but became necessary due to changes in operations or the environment, or monitoring functions based on sensor values that were deemed unnecessary at the time of development but were later found to need to be monitored) can be easily added simply by making the necessary settings.

The judgment condition on the second line of Figure 7 indicates that if the virtual sensor value (sensor ID = 12a-V1) of monitoring program 12a exceeds threshold X2, the measurement value of sensor S3 exceeds threshold X3, and the measurement value of sensor S8 exceeds threshold X4, a "system abnormality" message is sent to monitoring devices 10a-10c. According to this setting, the judgment unit 24 makes the above judgment based on the measurement values and virtual sensor values obtained from monitoring devices 10a-10c. If the judgment condition is met, the notification unit 26 sends the above message to the monitoring devices 10a-10c set as the notification destination. Although monitoring programs 12a-12c can only judge abnormalities in the subsystems they are responsible for, setting the judgment condition on the second line of Figure 7 makes it possible to quickly detect abnormalities that occur across subsystems or throughout facility 1, which cannot be detected by individual monitoring programs 12, without modifying facility 1 or monitoring programs 12a-12c. Furthermore, while virtual sensor values were previously only available within the monitoring program that calculated them, by collecting and sharing virtual sensor values on the integrated platform 20, comprehensive judgments can be made from the virtual sensor values calculated by multiple monitoring programs 12a-12c, which can be useful in monitoring the operating status of the entire system.

The judgment condition on the third line of Figure 7 indicates that if the difference between the virtual sensor value (data ID = b-005) of monitoring program 12b and the virtual sensor value (data ID = c-003) of monitoring program 12c exceeds threshold X5, a "temperature abnormality" message is sent to monitoring device 10c. Here, the two virtual sensor values are both estimated values of the cooling water temperature, calculated using different formulas based on different physical models. Furthermore, when equipment 1 is operating normally, these two virtual sensor values indicate the same temperature. If the operating state of equipment 1 deviates from the normal state, a divergence occurs between the two estimated temperature values. According to this setting, the judgment unit 24 calculates the difference between the two virtual sensor values and makes an abnormality judgment based on that difference. Thus, although the virtual sensor values may have been estimated differently depending on the development timing, developer, and development budget of monitoring program 12, abnormality monitoring can be performed by noting the differences in the behavior of the virtual sensor values based on the different estimation methods.

Furthermore, even if the relationship between monitored data acquired by different subsystems changes between normal and abnormal conditions (for example, as in the example above, two values are close to each other under normal conditions but diverge under abnormal conditions), and is not limited to virtual sensor values obtained by estimating the same physical quantity using different methods, an abnormality can be determined by setting that relationship as a judgment condition, similar to the judgment condition on the third line.

In the explanation of Figure 7 above, an example was described in which new anomaly detection can be performed on the integrated platform 20 simply by setting the detection conditions, etc., without modifying the monitoring program 12. However, this is not the only way to add a newly required anomaly detection function to the integrated platform 20. For example, anomaly detection logic (referred to as monitoring program 12a') that becomes necessary later in the monitoring program 12a may be added to the integrated platform 20. In this case, the monitoring program 12a' is an example of a determination unit 24. When adding an anomaly detection function that was not originally envisioned in the design, the only option is generally to modify the monitoring program 12a. However, this method involves making changes to a system that is operating stably, and therefore is risky. In contrast, by introducing the integrated platform 20, the monitoring program 12a' can be added to the integrated platform 20, allowing new anomaly monitoring functions to be added with low risk and without modifying the monitoring program 12a.

(Setting comprehensive criteria for determining abnormalities based on alerts)
FIG. 8 is a diagram illustrating an example of comprehensive anomaly determination criteria in the integrated platform according to the embodiment. The example settings shown in FIG. 8 are set by a user and accepted by the setting acceptance unit 22. On the horizontal axis of the table in FIG. 8 , the monitoring program 12a issues alerts 1 and 2, the monitoring program 12b issues alerts 3 and 4, and the monitoring program 12c issues alerts 5 and 6. A "1" for alerts 1 to 6 indicates that the alert has been issued, and a "0" indicates that the alert has not been issued. Regarding the levels on the vertical axis of the table in FIG. 8 , level 0 indicates that the entire system of equipment 1 is in a normal state, level 1 indicates that there is no abnormality but that the state is different from normal, level 2 indicates that there is no impact on the operation of equipment 1 but that some abnormality is suspected, level 3 indicates that an abnormality has occurred that affects the operation of equipment 1, and level 4 indicates that an abnormality has occurred that requires the shutdown of equipment 1.

The setting on the first line in FIG. 8 specifies that if alert 1 is issued from the monitoring program 12a and no other alerts are issued, the operating state is determined to be level 0.
The setting on the second line of Figure 8 specifies that if alert 1 is issued from the monitoring program 12a, alert 3 is issued from the monitoring program 12b, and no other alerts are issued, the operating state is determined to be level 1.
For example, the determination method in the seventh line (bottom line) of Fig. 8 specifies that if alerts 1 and 2 are issued from the monitoring program 12a, alerts 3 and 4 are issued from the monitoring program 12b, and alerts 5 and 6 are issued from the monitoring program 12c, it is determined that the operating state is level 4.
The comprehensive abnormality determination unit 25 determines the operating state of the equipment 1 based on the alerts acquired by the data acquisition unit 21 and the settings exemplified in Fig. 8. Then, the notification unit 26 displays the determination result (for example, when alert 1 and alert 3 are issued, a message such as "equipment 1 is not abnormal, but its operating state is different from normal") on the display device or transmits it to the monitoring devices 10a to 10c.
The monitoring programs 12a to 12c issue alerts for any abnormalities that occur within the range of the subsystems that they are responsible for. According to the setting example shown in Fig. 8, the alerts issued for each subsystem can be integrated to determine the operating status of the entire facility 1.

The setting example in Figure 8 is an example in which a knowledgeable engineer or the like sets the operating state of the equipment 1 for each combination of alerts, but a comprehensive judgment based on the combination of alerts may also be made based on past performance.
FIG. 9 illustrates an example of historical data for constructing a comprehensive anomaly judgment model. For example, historical data indicating that event A occurred when alerts 1 and 3 were issued, event B occurred when alerts 1 and 5 were issued, and so on is recorded and accumulated in the storage unit 27. The comprehensive anomaly judgment unit 25 is also provided with a learning function. The comprehensive anomaly judgment unit 25 learns from the historical data the relationship between the issuance of alerts 1 to 6 and the events occurring in the equipment 1, and constructs an anomaly judgment model. The comprehensive anomaly judgment unit 25 then evaluates the operating status of the equipment 1 based on the constructed anomaly judgment model and the values of alerts 1 to 6 acquired by the data acquisition unit 11. The notification unit 26 displays the evaluation results (e.g., when alerts 1 to 3 are issued, a message such as "There is a possibility that event C will occur in equipment 1" or the probability of event C occurring) on a display device or transmits them to the monitoring devices 10a to 10c.
This makes it possible to determine an abnormal state occurring in the facility 1 based on the past record of alerts issued by the monitoring programs 12a to 12c. Note that, regardless of the methods shown in Figures 8 and 9, when inspection results such as periodic inspections of the machines M1 to M4 and connected devices C1 to C2 are used as alerts, the operating state of the facility 1 can be determined taking into account the maintenance history of the machines M1 to M4, etc. Furthermore, the comprehensive abnormality determination unit 25 may perform both the determination described in Figure 8 and the determination described in Figure 9.

(Work costs when adding a new monitoring program)
Next, we will explain the work required to add a newly developed monitoring program 12d to the monitoring system 100. FIG. 10 shows the monitoring system 100 after adding a monitoring device 10d running the monitoring program 12d. The monitoring program 12d is a program that monitors a subsystem consisting of a machine M4. The machine M4 is equipped with a sensor S9. The monitoring program 12d is configured to acquire measurement values from sensors S8 to S9 and virtual sensor values (data ID = 12a-V1) calculated by the monitoring program 12a to monitor the operating status of the machine M4. In this case, the monitoring device 10d is connected to the sensor S9 and the integrated platform 20. Then, the setting reception unit 14d of the monitoring device 10d is configured to receive the measurement values from sensor S8 and the virtual sensor values (data ID = 12a-V1) from the integrated platform 20. Furthermore, the integrated platform 20 is configured to transmit the measurement values from sensor S8 and the virtual sensor values (data ID = 12a-V1) to the monitoring device 10d. As a result, the monitoring program 12d does not need to develop and implement logic for calculating the virtual sensor value. Furthermore, even if the sensor S8 is located in a remote location, the measurement value of the sensor S8 can be acquired simply by connecting the monitoring device 10d to the integrated platform 20 via a network, without the need to connect the monitoring device 10d to the sensor S8. Furthermore, the setting acceptance unit 14d of the monitoring device 10d configures the sensor S9 to transmit the measurement value of the sensor S9 to the integrated platform 20, and the integrated platform 20 sets the destination of the measurement value of the sensor S9. This allows the measurement value of the sensor S9 to be used by other monitoring programs 12a to 12c. Note that instead of connecting the sensor S9 to the monitoring device 10d, the sensor S9 may be connected to the integrated platform 20, and the monitoring device 10d may acquire the measurement value of the sensor S9 from the integrated platform 20.

By introducing the integrated platform 20 in this way and configuring it to centrally manage all measurement values and virtual sensor values, not only does it allow existing monitoring programs to share information with each other, but it also makes it easier to obtain the data necessary for monitoring in a new monitoring program 12d when that monitoring program is added. It also provides flexibility in cases where new sensor measurement values or virtual sensor values are needed due to changes in the specifications of existing monitoring programs 12a to 12c. Furthermore, assuming the introduction of the integrated platform 20, even when developing a new monitoring system for a large-scale system, it is possible to design a system that anticipates data sharing between multiple monitoring programs using the integrated platform 20. This makes it easier to design a monitoring system that can simultaneously monitor each subsystem and the entire system, rather than monitoring each subsystem separately.

(operation)
Next, the operation of the integrated platform 20 will be described with reference to FIG.
FIG. 11 is a flowchart illustrating an example of the operation of the integrated platform according to the embodiment.
The user sets data management settings (e.g., FIG. 6 ), judgment conditions (e.g., FIG. 7 ), and comprehensive anomaly judgment criteria (e.g., FIG. 8 ) in the integrated platform 20. The setting reception unit 22 acquires this setting information (step S101) and records it in the storage unit 27. Next, the data acquisition unit 21 acquires data such as sensor measurement values, virtual sensor values, and alerts from the monitoring devices 10 a to 10 c (step S102). The data acquisition unit 21 records the acquired data in the storage unit 27.
Next, the data providing unit 23 determines whether to provide the data acquired in step S102 to any of the monitoring programs 12a to 12c (step S103). For example, the data providing unit 23 determines to provide data if a destination is set in the data management settings (e.g., FIG. 6), and determines not to provide data if a destination is not set. If it determines not to provide data (step S103; No), the process proceeds to step S106. If it determines to provide data (step S103; Yes), the data providing unit 23 selects the type of data to be provided and information on the destination from the data management settings (step S104). For example, the data providing unit 23 selects "measurement value of sensor S1" as the data type and "monitoring device 10b" as the destination from the settings in the first row of FIG. 6. Next, the data providing unit 23 transmits the data (step S105). In the above example, the data providing unit 23 acquires the measurement value of the sensor S1 from the storage unit 27 out of the data acquired in step S102, and transmits the acquired value to the monitoring device 10b.

Next, the determination unit 24 determines whether to perform an abnormality determination based on the data acquired in step S102 (step S106). For example, if a determination condition setting (e.g., Figure 7) has been set, the determination unit 24 determines to perform an abnormality determination, and if a determination condition has not been set, the determination unit 24 determines not to perform an abnormality determination. If it has determined not to perform an abnormality determination (step S106; No), the process proceeds to step S109. If it has determined to perform an abnormality determination (step S106; Yes), the determination unit 24 acquires data necessary for the abnormality determination from the storage unit 27 and performs an abnormality determination based on the determination conditions (step S107). For example, the determination unit 24 determines whether the measurement value of sensor S2 exceeds X1 based on the determination conditions in the first row of Figure 7. The determination unit 24 outputs the determination result to the notification unit 26. The notification unit 26 transmits the abnormality determination result (step S108). For example, if the measurement value of sensor S2 exceeds X1, the notification unit 26 identifies the message "Abnormality sign detected on machine M1" and the notification destination "monitoring device 10b" from the judgment condition settings (Figure 7), and sends the message to monitoring device 10b.

Next, the comprehensive abnormality judgment unit 25 determines whether to perform a comprehensive abnormality judgment based on the alert acquired in step S102 (step S109). For example, if comprehensive abnormality judgment criteria have been set (e.g., FIG. 8) and an alert has been acquired in step S102, the comprehensive abnormality judgment unit 25 determines to perform an abnormality judgment; otherwise, it determines not to perform an abnormality judgment. If it determines not to perform a comprehensive abnormality judgment (step S109; No), the processing proceeds to step S112. If it determines to perform a comprehensive abnormality judgment (step S109; Yes), the comprehensive abnormality judgment unit 25 acquires the alerts necessary for the comprehensive abnormality judgment from the memory unit 27 and performs a comprehensive abnormality judgment based on the abnormality judgment criteria set (FIG. 8) (step S110). For example, if alert 1 and alert 3 are acquired in step S102, the comprehensive abnormality judgment unit 25 determines that a level 1 abnormality has occurred in facility 1 based on the abnormality judgment criteria in the second row of FIG. 8. Furthermore, for example, if some abnormality related to Alert 1 is detected during a regular inspection of machine M1, even if only Alert 3 is acquired in step S102, the comprehensive abnormality judgment unit 25 may consider that Alert 1 has been issued and judge that a Level 1 abnormality has occurred in facility 1. The comprehensive abnormality judgment unit 25 outputs the judgment result to the notification unit 26. The notification unit 26 outputs the result of the comprehensive abnormality judgment (step S111). For example, the notification unit 26 outputs a message such as "A Level 1 abnormality has occurred" to a display device. This allows the user to understand the operating status of facility 1, which cannot be monitored by individual monitoring programs 12a-12c.

The setting reception unit 22 then determines whether or not the settings have been changed (step S112). If the settings have been changed (step S112; Yes), the processing from step S101 onwards is executed. If the settings have not been changed (step S112; No), the integrated platform 20 then determines whether or not to end monitoring (step S113). If monitoring is to be ended (step S113; Yes), the processing of Figure 11 is terminated. If monitoring is not to be ended (step S113; No), the processing from step S102 onwards is repeatedly executed.

(effect)
Although large-scale systems are interconnected systems, traditionally, each subsystem is often separated and monitored individually. This can result in irrational and inefficient monitoring, such as overlooking events occurring in other subsystems that are related to events occurring in one subsystem, or failing to grasp the overall picture of events occurring across subsystems. In contrast, the integrated platform 20 of this embodiment allows multiple independent monitoring programs to work together and share the parameters and alerts monitored by each monitoring program. This allows a monitoring program to add parameters that it previously could not monitor (e.g., monitoring parameters of other subsystems) to its monitoring targets, enabling it to recognize events occurring in other subsystems that are related to events occurring in its own subsystem. Furthermore, unlike the conventional method, events occurring across subsystems can be monitored by bringing together parameters monitored by different monitoring programs and performing anomaly detection based on those parameters. Furthermore, by integrating alerts issued by multiple monitoring programs, the operating status of the entire system can be evaluated.

FIG. 12 illustrates an example of a hardware configuration of a monitoring system according to an embodiment.
The computer 900 includes a CPU 901 , a main memory device 902 , an auxiliary memory device 903 , an input/output interface 904 , and a communication interface 905 .
The monitoring device 10 and integrated platform 20 described above are implemented in a computer 900. The above-described functions are stored in the auxiliary storage device 903 in the form of a program. The CPU 901 reads the program from the auxiliary storage device 903, loads it into the main storage device 902, and executes the above-described processing in accordance with the program. The CPU 901 also allocates a storage area in the main storage device 902 in accordance with the program. The CPU 901 also allocates a storage area in the auxiliary storage device 903 for storing data being processed in accordance with the program.

In addition, a program for realizing all or part of the functions of the monitoring device 10 and the integrated platform 20 may be recorded on a computer-readable recording medium, and the program recorded on the recording medium may be loaded into a computer system and executed to perform processing by each functional unit. The term "computer system" here includes hardware such as the OS and peripheral devices. Furthermore, if a WWW system is used, the term "computer system" also includes the homepage provision environment (or display environment). Furthermore, "computer-readable recording medium" refers to portable media such as CDs, DVDs, and USBs, as well as storage devices such as hard disks built into the computer system. Furthermore, if the program is distributed to the computer 900 via a communication line, the computer 900 that receives the program may load the program into the main storage device 902 and execute the above-mentioned processing. Furthermore, the program may be for realizing part of the above-mentioned functions, or may be capable of realizing the above-mentioned functions in combination with a program already recorded on the computer system.

As described above, several embodiments of the present disclosure have been described. However, all of these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments may be embodied in a variety of other forms, and various omissions, substitutions, and modifications may be made without departing from the spirit of the invention. These embodiments and their variations are included within the scope of the invention and its equivalents as set forth in the claims, as well as within the scope and spirit of the invention.

<Additional Notes>
The integration platform, monitoring system, monitoring information integration method, and program described in the embodiments can be understood, for example, as follows.

(1) The integrated platform 20 according to the first aspect includes an acquisition unit (data acquisition unit 21) that acquires data on the monitored object (sensor measurement values, virtual sensor values) or monitoring results (alerts) from a monitoring program for monitoring a plurality of systems (subsystems constituting a large-scale system) prepared for each of the systems, a selection unit (data providing unit 23, S104 in FIG. 11) that selects a second monitoring program that requires the data from the first monitoring program, and an output unit (data providing unit 23, S105 in FIG. 11) that outputs the data acquired from the first monitoring program to the second monitoring program.
This allows the data to be monitored to be shared, and by monitoring parameters (data to be monitored) that could not be monitored before, it is possible to eliminate the drawbacks of monitoring separately by subsystem, such as insufficient coordination of monitoring programs, and to achieve the necessary collaboration between monitoring programs.

(2) The integrated platform 20 according to the second aspect is the integrated platform of (1), wherein the acquisition unit acquires a virtual sensor value, which is a physical quantity of the monitored object estimated by the first monitoring program, and the output unit outputs the virtual sensor value acquired from the first monitoring program to the second monitoring program.
Conventionally, virtual sensor values are calculated and used within each monitoring program and are not provided to the outside, but by using the integrated platform 20 as an intermediary in the exchange of virtual sensor values between monitoring programs, it becomes possible for a virtual sensor value estimated by one monitoring program to be provided to another monitoring program. This enables other monitoring programs to monitor parameters that cannot be measured by sensors.

(3) The integrated platform 20 according to the third aspect is an integrated platform of (1) to (2), wherein the acquisition unit acquires measurement values of a sensor that is monitored by a first monitoring program, and the output unit outputs the measurement values acquired from the first monitoring program to a second monitoring program.
This makes it easy to include the measurement values of sensors that were not subject to monitoring when the monitoring program was first developed as subjects to be monitored.

(4) The integrated platform 20 according to the fourth aspect is an integrated platform of (1) to (3), and further includes a comprehensive abnormality judgment unit 25 that generates a comprehensive alert indicating the operating status of the entire plurality of systems based on the alerts output by the plurality of monitoring programs, and a notification unit 26 that outputs the comprehensive alert generated by the comprehensive abnormality judgment unit.
This allows the operating status of the entire system to be evaluated, which cannot be evaluated by individual monitoring programs.

(5) The integrated platform 20 according to the fifth aspect is an integrated platform of any of (1) to (4), and further includes a determination unit 24 that performs an abnormality determination based on the data of the monitored object obtained from the monitoring program, and a notification unit 26 that outputs the result of the abnormality determination.
This allows for easy anomaly detection without modifying individual monitoring programs, and allows for anomaly monitoring of all parameters regardless of subsystem boundaries.

(6) The integrated platform 20 according to a sixth aspect is the integrated platform of any one of (1) to (5), wherein the determination unit determines the data acquired from the different monitoring programs as normal if a predetermined relationship is established between the data acquired from the different monitoring programs, and determines the data as abnormal if a predetermined relationship is not established.
This makes it possible to make an abnormality judgment based on a relationship between two parameters monitored by different subsystems, for example, where the values of the two parameters are approximately the same under normal conditions and diverge under abnormal conditions.

(7) A monitoring system according to a seventh aspect includes a monitoring program for monitoring each of a plurality of systems, and an integrated platform of (1) to (6).
This allows data handled by multiple monitoring programs developed individually to be shared, used by other monitoring programs, or handled in an integrated manner.

(8) A monitoring information sharing method according to an eighth aspect includes the steps of acquiring data on monitoring targets or monitoring results from monitoring programs prepared for each of a plurality of systems, the steps of selecting a second monitoring program that requires the data from a first monitoring program, and the steps of outputting the data acquired from the first monitoring program to the second monitoring program.

(9) A program according to a ninth aspect causes a computer to execute the steps of acquiring data on the monitoring target or the monitoring results from a monitoring program prepared for each of a plurality of systems for monitoring the systems, selecting a second monitoring program that requires the data from a first monitoring program, and outputting the data acquired from the first monitoring program to the second monitoring program.

1... Equipment 10, 10a, 10b, 10c, 10d... Monitoring device 11, 11a, 11b, 11c... Data acquisition unit 12, 12a, 12b, 12c, 12d... Monitoring program 13, 13a, 13b, 13c... Integrated platform collaboration unit 14, 14a, 14b, 14c... Setting acceptance unit 15, 15a, 15b, 15c... Transmission unit 16, 16a, 16b, 16c... Reception unit 17, 17a, 17b , 17c...Memory unit 20...Integrated platform 21...Data acquisition unit 22...Setting reception unit 23...Data provision unit 24...Determination unit 25...Comprehensive abnormality determination unit 26...Notification unit 27...Memory unit 100...Monitoring systems M1, M2, M3...Machines C1, C2...Connected devices S1, S2, S3, S4, S5, S6, S7, S8, S9...Sensor 900...Computer 901...CPU
902: Main storage device 903: Auxiliary storage device 904: Input/output interface 905: Communication interface

Claims (9)

1. A monitoring system for monitoring a system including a plurality of subsystems, comprising:
a first monitoring device running a first monitoring program for monitoring the first subsystem ;
a second monitoring device running a second monitoring program for monitoring the second subsystem;
An integrated platform and
and
The integrated platform comprises:
an acquisition unit that acquires data on a monitoring target or a monitoring result from the first monitoring device ;
a selection unit that selects a second monitoring program that requires the data of the first monitoring program;
an output unit that outputs the data acquired from the first monitoring device to the second monitoring device ;
a setting receiving unit that receives a setting of logic for determining an abnormality in the first subsystem that is not included in the first monitoring program;
a determination unit that determines whether or not there is an abnormality in the first subsystem based on the data and the logic;
A monitoring system having: the acquisition unit acquires a virtual sensor value that is a physical quantity of the monitoring target estimated by the first monitoring program;
the output unit outputs the virtual sensor value acquired from the first monitoring program to the second monitoring program;
The monitoring system of claim 1 . the acquisition unit acquires a measurement value of a sensor that is a monitoring target of the first monitoring program,
the output unit outputs the measurement value acquired from the first monitoring program to the second monitoring program;
3. The monitoring system according to claim 1 or 2. The integrated platform comprises:
a comprehensive abnormality determination unit that generates a comprehensive alert indicating the operating status of the entire plurality of systems based on the alerts output by the plurality of monitoring programs;
a notification unit that outputs the comprehensive alert generated by the comprehensive abnormality determination unit;
3. The monitoring system according to claim 1 or claim 2, further comprising: The integrated platform comprises:
a notification unit that outputs the determination result of the determination unit to the second monitoring device;
3. The monitoring system according to claim 1 or claim 2, further comprising: the determination unit determines that the data acquired from the different monitoring programs is normal when a predetermined relationship is established between the data acquired from the different monitoring programs, and determines that the data is abnormal when a predetermined relationship is not established between the data acquired from the different monitoring programs.
3. The monitoring system according to claim 1 or 2 . The acquisition unit
The first monitoring program acquires from the first monitoring device a first virtual sensor value, which is a physical quantity of the monitoring target calculated by a calculation formula based on a first physical model;
a second monitoring program acquires from a second monitoring device a second virtual sensor value, the second virtual sensor value being the physical quantity calculated by a calculation formula based on a second physical model different from the first physical model;
the determination unit determines whether the first subsystem is abnormal based on a difference between the first virtual sensor value and the second virtual sensor value.
3. The monitoring system according to claim 1 or 2. 1. A monitoring method for monitoring a system including a plurality of subsystems, comprising:
acquiring data on a monitoring target or a monitoring result from a first monitoring device running a first monitoring program for monitoring the first subsystem ;
selecting a second monitoring program for monitoring a second subsystem that requires the data of a first monitoring program;
outputting the data acquired from the first monitoring device to a second monitoring device on which the second monitoring program is running ;
receiving a setting of logic for determining an abnormality in the first subsystem that is not included in the first monitoring program;
determining an abnormality in the first subsystem based on the data and the logic;
A monitoring method comprising: On the computer,
A program for executing the monitoring method according to claim 8 .