Equipment fault diagnosis and monitoring system based on flexible configuration

Abstract

The invention relates to an equipment fault diagnosis and monitoring system based on flexible configuration, and the system comprises a fault diagnosis algorithm management module which supports a user to upload and manage a fault detection algorithm; the fault diagnosis task module supports a user to customize a fault detection task; the configuration monitoring design module supports a user to configure a factory environment and equipment according to actual conditions, and also supports association of a configuration component and database data; and the configuration monitoring deployment module is used for supporting a user to check a configuration picture through a front-end browser so as to monitor equipment parameters and states. The whole system is realized by adopting a B / S architecture. According to the method, the equipment fault diagnosis and monitoring task can be flexibly generated and deployed through flexible configuration, so that the period of implementing and deploying the equipment fault detection task by enterprise users and developers is shortened, subsequent business upgrading and maintenance are facilitated, and the flexibility and fault tolerance of the system are improved while functions are realized.

Description

Technical Field

[0001] The invention belongs to the field of equipment analysis and monitoring, and in particular relates to an equipment fault diagnosis and monitoring system based on flexible configuration. Background Art

[0002] Existing equipment fault diagnosis systems are generally based on fixed processes and algorithms for fault diagnosis, which also results in very limited devices and scenarios that can be handled after the system is developed. Once the scenario changes, even if it is a minor adjustment, engineers often need to intrusively modify the original system process according to the actual situation, or even redevelop a new fault diagnosis system.

[0003] Similarly, in terms of equipment monitoring, currently commonly used equipment configuration and monitoring software such as wincc are mostly based on the CS architecture, which is difficult to meet the requirements of anytime monitoring of field equipment. The equipment monitoring and configuration system based on the BS architecture solidifies all component logic into the program, which also means that every modification of a component requires intrusive modification of the component program logic. Summary of the invention

[0004] In view of the above-mentioned deficiencies of the existing systems in fault diagnosis and equipment monitoring, the present invention proposes an equipment fault diagnosis and monitoring system based on flexible configuration. Through flexible configuration, equipment fault diagnosis and monitoring tasks are flexibly generated and deployed, thereby reducing the implementation and deployment cycle of equipment fault detection tasks for enterprise users and developers.

[0005] The technical solution adopted by the present invention is:

[0006] A flexible configuration-based equipment fault diagnosis and monitoring system, comprising: providing users with flexible configuration of industrial equipment fault detection and configuration monitoring by constructing a fault diagnosis algorithm management module, a fault diagnosis task module, a configuration monitoring design module, a configuration monitoring deployment module and a database in a front-end interface and a running background;

[0007] The fault diagnosis algorithm management module supports users to upload and manage fault detection algorithms;

[0008] The fault diagnosis task module supports user-defined fault detection tasks;

[0009] The configuration monitoring design module supports users to configure the factory environment and equipment according to actual conditions, and also supports associating configuration components with database data;

[0010] The configuration monitoring deployment module supports users to monitor device parameters and status by viewing the configuration screen through the front-end browser;

[0011] The database is used to store data input by users of the front-end interface and data for running back-end execution tasks and monitoring.

[0012] The system is implemented based on B / S architecture, and the backend is implemented using microservice architecture. The fault diagnosis algorithm management module and the fault diagnosis task module constitute the equipment fault detection service, and the configuration monitoring design module and the configuration monitoring deployment module constitute the equipment configuration monitoring service. The two services are independent of each other and exchange data by connecting to the same database.

[0013] The fault diagnosis algorithm management module is deployed in the backend and collects the custom algorithm files uploaded by users through the frontend interface. The collected content includes: a. algorithm file; b. algorithm class name and format; c. parameter name, type and default value of initialization parameters; d. parameter name and type of input and output parameters.

[0014] The fault diagnosis algorithm management module supports version control of uploaded algorithms: it is capable of modifying the setting information of uploaded algorithms, but does not allow changing the file type of uploaded algorithms.

[0015] The fault diagnosis task module includes two units deployed at the front end and the back end respectively:

[0016] The front-end task construction unit is used by the user to construct a task flow chart on the front-end. After the construction is completed, it is converted into a flow configuration file and sent to the back-end;

[0017] The background task execution unit parses the task flow configuration file, builds the calculation data engine, executes the calculation tasks, and stores the task results.

[0018] The background task execution unit parses the task flow configuration file, including:

[0019] Parse the data source node into SQL query statements for reading data;

[0020] The computing nodes are parsed into a directed acyclic computing graph according to the process configuration. Each node in the graph represents a computing node. The computing operation of each computing node comes from the fault diagnosis algorithm collected by the fault diagnosis algorithm management module.

[0021] Parse the storage node into SQL insert statements to store the calculation results.

[0022] The background task execution unit constructs a data calculation engine and executes the following steps:

[0023] Read data => Pack input => Calculate data => Pack output => Store output.

[0024] Before calculating the data, you need to package the read data according to the input rules set when uploading the algorithm; before storing the results, you need to package the output of the computing node according to the output rules set when uploading the algorithm.

[0025] The configuration monitoring design module is deployed in the front-end interface to support the user's configuration operations to generate configuration configuration files and to edit the configuration configuration files again; the configuration operations include dragging and connecting configuration components, associating components with data in the database, and making set actions based on the associated data.

[0026] The configuration monitoring deployment module includes two units deployed at the front end and the back end respectively:

[0027] The configuration monitoring backend unit is used to parse the configuration file, parse the configuration into the front-end screen, convert the component configuration into the component operation task, establish the communication channel between the front-end configuration screen and the back-end component operation task through WebSocket; and monitor the corresponding data in the database;

[0028] Configuration monitoring front-end unit, used for configuration screen display.

[0029] The advantages and beneficial effects of the present invention are:

[0030] Through flexible configuration, it can flexibly generate and deploy equipment fault diagnosis and monitoring tasks, reduce the implementation and deployment cycle of equipment fault detection tasks for enterprise users and developers, facilitate subsequent business upgrades and maintenance, and improve the flexibility and fault tolerance of the system while realizing functions. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is an equipment fault diagnosis and monitoring system based on flexible configuration.

[0032] Figure 2 It is the process of uploading the equipment fault diagnosis algorithm.

[0033] Figure 3 It is the process of generating and executing equipment fault diagnosis tasks.

[0034] Figure 4 It is the equipment configuration monitoring deployment process. DETAILED DESCRIPTION

[0035] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation method of the present invention is described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the invention, so the present invention is not limited by the specific implementation disclosed below.

[0036] A flexible configuration-based equipment fault diagnosis and monitoring system, which consists of a fault diagnosis algorithm management module, a fault diagnosis task module, a configuration monitoring design module, a configuration monitoring deployment module and a database. The structure of each module is as follows: Figure 1 shown.

[0037] 1. Fault diagnosis algorithm management module

[0038] Users can use this module to upload custom algorithm files or maintain uploaded algorithms.

[0039] like Figure 2 As shown in the figure, it is the process of users uploading custom algorithms. The specific process is as follows:

[0040] Step 1: Upload the algorithm file and set the calling class name. The algorithm file supports both jar package and python file. If the algorithm has initialization parameters, proceed to step 2, otherwise proceed to step 3;

[0041] Step 2: Set the parameter name, parameter type and default value of the initialization parameter. If there are other initialization parameters, go to step 2, otherwise go to step 3;

[0042] Step 3: Set the parameter name and parameter type of the input parameter. If the parameter type is a list, go to step 4, otherwise go to step 5.

[0043] Step 4: Set the length of the input parameter list;

[0044] Step 5: If there are other input parameters, return to step 3, otherwise go to step 6;

[0045] Step 6: Set the parameter name and parameter type of the output parameter. If the parameter type is a list, go to step 7, otherwise go to step 8;

[0046] Step 7: Set the length of the input parameter list;

[0047] Step 8: If there are other input and output parameters, return to step 7, otherwise end the algorithm upload process.

[0048] For uploaded algorithms, users can perform version control on them. They can update the algorithm files and the settings of initialization parameters, input parameters, and output parameters of uploaded algorithms, but are not allowed to change the file type of uploaded algorithms. Each time the algorithm is updated, the version number is automatically increased by one and overwrites the previous version.

[0049] 2. Fault diagnosis task module

[0050] The user builds a task flow chart through the front-end interface. The flow chart includes data source nodes, computing nodes, and storage nodes. After submitting the flow chart, the system automatically converts it into a flow configuration file and transmits the configuration file to the back-end. When setting the task flow, you also need to set the task attributes, that is, real-time tasks or historical tasks. If the task attribute is a real-time task, you need to set the task execution interval. If it is a historical task, you need to select the historical time period in the data source node.

[0051] After receiving the configuration file, the backend parses it and generates a computing engine to perform the computing task. The specific process is as follows: Figure 3 As shown in the figure, the data source node is parsed into an SQL query statement for reading data; the computing node is parsed into a computing directed acyclic graph according to the calculation order, and each node in the graph represents a computing node. The computing operation of each computing node comes from the fault diagnosis algorithm uploaded in advance; the storage node setting is parsed, and the node and its computing results are obtained for storage.

[0052] Then, a data calculation engine is built based on the analysis results. The overall order of the calculation engine is:

[0053] Step 1: Query the database to obtain data according to the SQL query statement parsed by the input node;

[0054] Step 2: Pack the corresponding data according to the algorithm input rules set when uploading the algorithm;

[0055] Step 3: Perform calculations according to the direction of the calculation graph and save the calculation results to the node data structure;

[0056] Step 4: According to the algorithm output format set when uploading the algorithm, parse the corresponding data according to the output format and package it into the data storage format;

[0057] Step 5: Store the results that need to be stored according to the analysis of the storage node.

[0058] If the task type is a historical task, the entire task will be completed after step 5. If it is a real-time task, the parsing results will be saved in the memory, and the calculation engine process from step 1 to step 5 will be executed cyclically according to the set interval event.

[0059] 3. Configuration monitoring design module

[0060] Users can add configuration components representing devices on the front-end page to draw monitoring screens. The drawing content includes: canvas background setting, canvas size setting, component shape selection, component size setting, and component layout drawing. At the same time, components can be associated with data in the database, which can be offline data originally stored in the database or fault diagnosis results calculated by fault diagnosis tasks. In addition, logical animations can be set for components based on the data associated with the components. Animations include flashing, appearing, disappearing, rotating, and color changes to achieve the effect of monitoring data and real-time alarms. The entire design process is relatively free, and there are no fixed design steps. After the design is completed, when the design results are saved, the design file will be automatically generated and transferred to the back end for saving.

[0061] 4. Configuration monitoring deployment module

[0062] Configuration monitoring deployment process Figure 4 As shown in the figure, the deployment process is to parse the saved design files into two parts: front-end display and back-end tasks. The front-end is used to display the monitoring screen and perform set actions according to the associated data. The back-end performs database monitoring tasks. The front-end and back-end communicate in duplex mode through Web Socket to ensure that the back-end monitoring data can be pushed to the front-end response component in real time.

[0063] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any way. Any simple modification, change and equivalent structural change made to the above embodiment based on the technical essence of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A device fault diagnosis and monitoring system based on flexible configuration, characterized in that: include: By building fault diagnosis algorithm management module, fault diagnosis task module, configuration monitoring design module, configuration monitoring deployment module and database in the front-end interface and operation background, users can be provided with flexibly configurable fault detection and configuration monitoring of industrial equipment; The fault diagnosis algorithm management module supports users to upload and manage fault detection algorithms; The fault diagnosis task module supports user-defined fault detection tasks; The configuration monitoring design module supports users to configure the factory environment and equipment according to actual conditions, and also supports associating configuration components with database data; The configuration monitoring deployment module supports users to monitor device parameters and status by viewing the configuration screen through the front-end browser; The database is used to store data input by users of the front-end interface and data for running back-end execution tasks and monitoring.

2. According to the flexible configuration-based equipment fault diagnosis and monitoring system of claim 1, it is characterized in that: The system is implemented based on B / S architecture, and the backend is implemented using microservice architecture. The fault diagnosis algorithm management module and the fault diagnosis task module constitute the equipment fault detection service, and the configuration monitoring design module and the configuration monitoring deployment module constitute the equipment configuration monitoring service. The two services are independent of each other and exchange data by connecting to the same database.

3. According to the flexible configuration-based equipment fault diagnosis and monitoring system of claim 1, it is characterized in that: The fault diagnosis algorithm management module is deployed in the backend and collects the custom algorithm files uploaded by users through the frontend interface. The collected content includes: a. algorithm file; b. algorithm class name and format; c. parameter name, type and default value of initialization parameters; d. parameter name and type of input and output parameters.

4. The equipment fault diagnosis and monitoring system based on flexible configuration according to claim 1 is characterized in that: The fault diagnosis algorithm management module supports version control of uploaded algorithms: it is capable of modifying the setting information of uploaded algorithms, but does not allow changing the file type of uploaded algorithms.

5. The equipment fault diagnosis and monitoring system based on flexible configuration according to claim 1 is characterized in that: The fault diagnosis task module includes two units deployed at the front end and the back end respectively: The front-end task construction unit is used by the user to construct a task flow chart on the front-end. After the construction is completed, it is converted into a flow configuration file and sent to the back-end; The background task execution unit parses the task flow configuration file, builds the calculation data engine, executes the calculation tasks, and stores the task results.

6. The equipment fault diagnosis and monitoring system based on flexible configuration according to claim 5 is characterized in that: The background task execution unit parses the task flow configuration file, including: Parse the data source node into SQL query statements for reading data; The computing nodes are parsed into a directed acyclic computing graph according to the process configuration. Each node in the graph represents a computing node. The computing operation of each computing node comes from the fault diagnosis algorithm collected by the fault diagnosis algorithm management module. Parse the storage node into SQL insert statements to store the calculation results.

7. The equipment fault diagnosis and monitoring system based on flexible configuration according to claim 5 is characterized in that: The background task execution unit constructs a data calculation engine and executes the following steps: Read data => Pack input => Calculate data => Pack output => Store output.

8. The equipment fault diagnosis and monitoring system based on flexible configuration according to claim 7 is characterized in that: Before calculating the data, you need to package the read data according to the input rules set when uploading the algorithm; before storing the results, you need to package the output of the computing node according to the output rules set when uploading the algorithm.

9. The equipment fault diagnosis and monitoring system based on flexible configuration according to claim 1 is characterized in that: The configuration monitoring design module is deployed in the front-end interface to support the user's configuration operations to generate configuration configuration files and to edit the configuration configuration files again; the configuration operations include dragging and connecting configuration components, associating components with data in the database, and making set actions based on the associated data.

10. According to the flexible configuration-based equipment fault diagnosis and monitoring system according to claim 1, it is characterized in that: The configuration monitoring deployment module includes two units deployed at the front end and the back end respectively: The configuration monitoring backend unit is used to parse the configuration file, parse the configuration into the front-end screen, convert the component configuration into the component operation task, establish the communication channel between the front-end configuration screen and the back-end component operation task through WebSocket; and monitor the corresponding data in the database; Configuration monitoring front-end unit, used for configuration screen display.

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