CN117709871A - Multi-sensor-based electricity safety inspection system - Google Patents
Multi-sensor-based electricity safety inspection system Download PDFInfo
- Publication number
- CN117709871A CN117709871A CN202311618439.6A CN202311618439A CN117709871A CN 117709871 A CN117709871 A CN 117709871A CN 202311618439 A CN202311618439 A CN 202311618439A CN 117709871 A CN117709871 A CN 117709871A
- Authority
- CN
- China
- Prior art keywords
- module
- data
- user
- information
- preprocessing
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000007689 inspection Methods 0.000 title claims abstract description 40
- 230000005611 electricity Effects 0.000 title description 16
- 238000007781 pre-processing Methods 0.000 claims abstract description 61
- 230000010354 integration Effects 0.000 claims abstract description 58
- 230000002688 persistence Effects 0.000 claims abstract description 43
- 238000004519 manufacturing process Methods 0.000 claims abstract description 42
- 238000012545 processing Methods 0.000 claims abstract description 36
- 238000013528 artificial neural network Methods 0.000 claims abstract description 17
- 230000000007 visual effect Effects 0.000 claims abstract description 5
- 238000010586 diagram Methods 0.000 claims description 15
- 238000004458 analytical method Methods 0.000 claims description 12
- 238000001514 detection method Methods 0.000 claims description 11
- 230000008859 change Effects 0.000 claims description 7
- 230000004048 modification Effects 0.000 claims description 3
- 238000012986 modification Methods 0.000 claims description 3
- 238000000034 method Methods 0.000 description 21
- 230000008569 process Effects 0.000 description 14
- 230000006870 function Effects 0.000 description 8
- 238000005516 engineering process Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000003062 neural network model Methods 0.000 description 1
- 238000004806 packaging method and process Methods 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
Abstract
An electrical safety inspection system based on multiple sensors, comprising: the inspector view module is used for providing user with electrical appliance options and related user information through a visual interface; the information statistics module is used for counting all working flows at the current moment; the intelligent recommendation module generates a graph neural network path prediction model according to a historical graph path queried by a user, and generates information for recommending a future query path of the user by utilizing the path prediction model according to a current user query path; the flow work module receives and executes a request of a user for a work flow; the rule processing module receives a request of a user for rules; the data integration and preprocessing module is used for receiving the real-time information of the state of the electric appliance, preprocessing the information and then sending the preprocessed information to the data persistence module for storage; the data persistence module stores the received data. The invention displays the relation and flow of the production equipment in the workshop to the user and grasps the production sequence between the production equipment.
Description
Technical Field
The invention relates to the technical field of electric power safety, in particular to an electric power safety inspection system based on multiple sensors.
Background
With the continuous progress of society, an automation system appears in the life of people, the effective operation of the automation system greatly saves the application cost, saves the resources and also provides strong support for the supply of electric power resources. The purpose of the power system automation technology is to ensure the stable and safe operation of the power system, if a data fault occurs, the power system can be adjusted and restored by adopting responsive measures aiming at the reason of the fault, and the degree of automation can be further enhanced by adjusting hardware and software. The sensor is used as a detection device, can detect any information of the external environment, and then converts the perceived information into an electric signal according to a rule, so that the requirements of information transmission, storage, perception and the like are met. Therefore, the sensor technology is applied to intelligent power network power utilization safety, a set of remote power utilization safety inspection system is established, various environment parameters of power equipment scattered at different geographic positions are collected and analyzed, corresponding early warning is given, and power utilization safety management can be more efficiently realized.
Disclosure of Invention
With the continuous development of an intelligent power network, the contradiction between continuous huge power system and efficient investigation of circuit emergency repair, circuit safety inspection, circuit potential safety hazard and the like is becoming prominent, and the invention provides a set of remote power utilization safety inspection system which can collect and analyze various environmental parameters of power equipment scattered at different geographic positions and give corresponding early warning. And (3) carrying out associated storage on various devices in the diversified production environments by utilizing the knowledge graph for a user to check and check the devices, and simultaneously comparing data obtained by different sensors on the remote production environments with related rules to obtain the current electricity consumption condition, thereby realizing remote monitoring of electricity consumption safety.
The invention provides an electricity safety inspection system based on multiple sensors, which comprises: the inspector view module provides electrical equipment options for a user through a visual interface, and provides a relation chart, a production line flow, an electrical equipment inspection list, flow management and rule management query service for the user according to the electrical equipment options selected by the user;
the information statistics module is used for counting all the workflows at the current moment, corresponding inspector numbers and information of whether problems occur in all the workflows; providing a query portal to receive a user query service request sent by an inspector view module;
the intelligent recommendation module generates a graph neural network path prediction model according to a historical graph path queried by a user, and generates information for recommending a future query path of the user by utilizing the path prediction model according to a current user query path;
the flow work module receives and executes the operation and query requests of the user for adding, deleting and modifying the workflow, and returns the operation and/or query results to the user;
the rule processing module receives the operation and query requests of the user for adding, deleting and modifying the rules, and returns operation and/or query results to the user;
the data integration and preprocessing module is used for receiving the state information data of the electric appliance sent by the real-time sensor, preprocessing the state information and then sending the preprocessed state information to the data persistence module for storage;
the data persistence module is used for receiving and storing the data sent by the sensor input module and the data integration and preprocessing module;
and the sensor input module is used for receiving the state data of the electric appliance collected by the various types of sensors.
Further, the inspector view module receives a request option of providing a relation chart from a user, the information statistics module requests all relation pattern data information of the related nodes from the data persistence module, the data persistence module returns all relation pattern data information to the information statistics module, and the information statistics module displays the pattern to the user.
Further, the inspector view module receives a request option for checking the flow of the production line from a user, the information statistics module requests all equipment information of the production line from the data integration and preprocessing module, the data integration and preprocessing module requests the equipment information from the data persistence module, the data persistence module returns the equipment information to the data integration and preprocessing module, the data integration and preprocessing module integrates the equipment information, adds a table header to the equipment information and returns all the processed equipment information to the information statistics module, the information statistics module sends the equipment and the corresponding rule to the rule processing module, the rule processing module returns a matched result to the information statistics module after the equipment information is matched with the corresponding rule, and the information statistics module displays the result to the user.
Further, the inspector view module receives a request option for selecting an electric appliance inspection sheet by a user, and the information statistics module requests the data integration and preprocessing module to print all data required by the electric appliance inspection sheet of the user; the data integration and preprocessing module requests a real-time data part in the required data from the data persistence module; the data persistence module receives the data and the serial numbers of each sensor related to the current scene from the sensor and returns the data to the data integration and preprocessing module; the data integration and preprocessing module formats and matches the real-time data sent by the data persistence module; the data integration and preprocessing module returns the processed real-time data to the information statistics module; the information statistics module sends the preliminarily received real-time data to the rule processing module to request comparison with rules; the rule processing module intelligently matches the received real-time data with the corresponding rule standard interval, performs conflict detection and comparison analysis; the rule processing module returns the detection data result and the analysis result to the information statistics module; and the information statistics module integrates all the data to generate a printing list.
Further, the inspector view module receives options of user flow management, and the inspector view module receives and forwards a request of user flow management to the flow work module; the flow work module initiates a request for recording change information to the data integration and preprocessing module; the data integration and preprocessing module requests the data persistence module to update information of the changed equipment; the data persistence module returns a message of finishing updating the data integration and preprocessing module; the data integration and preprocessing module returns to the flow work module to record the completed message; the workflow work module provides an interface that the user has updated.
Further, the inspector view module receives the option of user rule management, the inspector view module receives and forwards the request of user rule management to the rule processing module, and the rule processing module firstly carries out conflict detection to judge whether the request of rule management is in violation with the current rule; if not, the rule processing module initiates a request for recording change information to the data integration and preprocessing module; the data integration and preprocessing module requests the data persistence module to update information for the modification equipment; the data persistence module returns a message of finishing updating the data integration and preprocessing module; the data integration and preprocessing module returns to the rule processing module to record the completed message; the rule processing module returns information of successful operation to the user to the inspector view module, and the inspector view module displays the information of successful operation to the user.
Further, the graph neural network path prediction model is a model based on an R-GCN structure; generating a query history path instance according to a query history generated by the user-selected electrical appliance options; and (3) reserving all query history path constitution diagrams, inputting the query history path constitution diagrams and query nodes input by a user into a graph neural network path prediction model based on an R-GCN structure, and outputting recommended feasible query paths.
Compared with the prior art, the invention has the advantages that:
(1) The sensor can be used for remotely acquiring electricity utilization data of production equipment, so that the cost is reduced, the safety guarantee of operators is improved, and the production scene is remotely monitored.
(2) The knowledge graph can be used for showing the relation of production equipment in all production workshops in the system to a user, and the production sequence between the production equipment is mastered through the flow.
(3) The future inspection flow path recommendation prediction can be obtained through the graph neural network model, so that an inspector can be helped to quickly grasp a key equipment production line and the like, and more accurate and efficient work can be realized.
Drawings
FIG. 1 is a general architecture diagram of the system of the present invention;
FIG. 2 is a diagram of the interaction of the modules in the system of the present invention;
FIG. 3 is a flow chart of an exemplary flow chart for viewing the line flow order and rule presentation of the present invention;
FIG. 4 is a flowchart of an exemplary process for querying an appliance inspection sheet in accordance with the present invention;
FIG. 5 is a flow chart of an exemplary process management flow of the present invention;
FIG. 6 is a flow chart of an exemplary rule management process of the present invention;
FIG. 7 is a schematic diagram of a path prediction recommendation step according to the present invention.
Detailed Description
The invention provides an electricity safety inspection system based on multiple sensors. The following detailed description of specific embodiments of the invention refers to the accompanying drawings.
Referring to fig. 1, the multi-sensor-based electricity safety inspection system mainly comprises an inspector view module, an information statistics module, a flow work module, a rule processing module, a data integration and preprocessing module and a data persistence module. The main functions of each module are as follows:
inspector view module
The module mainly displays pages to security inspectors so as to provide various services for users through visual interfaces. The user can select the corresponding electric appliance on the page, check each electric appliance condition of the current electric appliance, analyze and compare the electric appliance, and take reasonable measures. The module also provides the functions of generating and distributing the inspection sheets of the electric appliances for the user, the user can select one or more types of electric appliances to integrate and print all data of the electric appliances, and the complete data result is displayed for the user to analyze transversely or longitudinally.
Information statistics module
The module counts all the information of all the work flow states, corresponding responsible inspector numbers, whether problems occur in each flow instance and the like at the current moment together so as to be called when a user views or prints an inspection sheet. On the basis of intelligent matching, when one or more keywords are given by a user, related information required by all users can be quickly completed by searching a database, and data required in current information statistics can be screened out.
Intelligent recommendation module
The model is mainly composed of two sub-modules, is a packaging module of a path prediction model based on a graph neural network, and comprises the steps of generating a model according to a historical graph path and making prediction recommendation for a complete path in the future according to the model and a current path key node.
Flow work module
The module mainly comprises four sub-modules, is convenient for processing various existing flows, is also convenient for adding new flows, deleting old flows and the like, meets the requirements of updating projects by combining actual conditions, and is more favorable for the safety record and grasp of workers on each electricity utilization scene due to strict correspondence with reality.
Rule processing module
The module uses xml/json files to uniformly store all rules, can search according to keywords given by users, matches all information wanted by inspectors to integrate, analyzes whether equipment belongs to a normal working interval according to electric and electronic standards, and gives reasonable advice. And meanwhile, the management such as conflict detection, deletion and correction operation and the like can be performed in the rule.
Data integration and preprocessing module
The module integrates data sources related to the electric appliance and submits the data sources to the data persistence module for storage, and the module also performs corresponding preprocessing operation on the data sources with nonstandard formats.
Data persistence module
The module is responsible for the storage and reading functions of a system data source, remotely receives and stores various data about the current use condition of the electric appliance transmitted by the sensor, and the integrated sensor distributes various data indexes read around the electric appliance.
Sensor input module
The module is responsible for controlling the data input of the various types of sensors. Because the sensor types are various, the transmitted data types are different, so that different control modules are needed to process the transmitted data of different types.
Referring to fig. 2, the basic elements in the inspector view are basically displayed by various data information collected by the information statistics module, and the relevant operations are accurately performed by users through various process examples, devices and the like. Meanwhile, the information statistics module processes intelligent matching analysis based on the current working state and rules of each flow instance, and generates and distributes a printing sheet of a production line required by a user. The user can scientifically manage each flow and rule according to the change of the equipment update increase and decrease and the production requirement of the actual situation. Meanwhile, the system can also construct a historical path diagram generating model according to the collected information to recommend future paths.
In the process of working in the flow example, no matter what scene, what equipment and when data are obtained, comparison and analysis are needed with rules corresponding to the electric appliances, so that a series of analysis results can be obtained for inspection by inspectors to judge how and whether the current electric safety situation is operated next time.
The data sources needed in the system are all derived from a data integration and preprocessing module, and the data integration and preprocessing module is responsible for integrating real-time data obtained in the data persistence module with system fixed data for the rule module, the flow work module and the information statistics module to read, compare and analyze. Meanwhile, the data integration module also collects the result parts analyzed by each instance in the flow work module for the follow-up complete production improvement suggestion reference and the adjustment of the large framework.
The interface structure of each module is described below.
The information statistics module is provided with an information collection interface. Information collection interface: and collecting and integrating all data required to be distributed to the user, and returning all information to be printed.
The intelligent recommendation module has: a historical path collection interface and a future path recommendation interface. Historical path collection interface: and receiving paths in all the flow examples queried by the users, generating a graph and constructing a model. Future path recommendation interface: the key nodes of the path which the user wants to generate are received and all possible paths are returned.
The flow work module comprises a flow management interface and a flow viewing interface. The flow management interface: and receiving and executing the adding, deleting and checking operation information of all users for the flow. Flow viewing interface: and receiving a request of a user for viewing a certain flow instance, collecting all data of the instance in real time, and returning the data to the user to display the instance.
The rule processing module has: rule management interface, rule matching interface. Rule management interface: and receiving the operation information of adding, deleting and checking the rules of all users, performing conflict detection, performing the operation required by the users after confirming the conflict, and returning to the user results. Intelligent matching interface: after receiving the real-time data, comparing and analyzing each item of data with the standard matching of the corresponding rule, and returning analysis data results and the like.
The data integration and preprocessing module comprises: the system comprises a real-time sensor data processing interface and a working data collecting interface. Real-time sensor data processing interface: and integrating the primary data transmitted by the data persistence with the fixed data, and converting the primary data and the fixed data into a unified format. Work data collection interface: partial flow instance work data is collected for analysis of long-term work, efficient operation recommendations.
The data persistence module has a data access interface. Data access interface: the real-time data of different types transmitted by various sensors are received from different types of interfaces, new inherent data transmitted when the user modifies the flow and rules, and result data of some analysis which need to be saved.
FIG. 3 is a flow chart showing an exemplary flow chart for checking the flow order and rules of a production line according to the present invention. Before the user formally uses the checking system, the user can roughly know the sequence and relation of the production line and the equipment to be checked according to the sequence diagram, and after the function is used, the user can be used as a reference criterion of the system for checking and managing the operation of each flow equipment. When a user wants to view the production relationship of the equipment, selecting a relationship diagram view function on an inspector interface, and initiating a request for viewing a knowledge graph; and calling an information statistics module to request all map data information from a data persistence module, returning all information to the information statistics module by the data persistence module, and displaying the map to a user by the information statistics module.
FIG. 4 is a flowchart of an exemplary process for checking an appliance for inquiry according to the present invention. The user selects a checking sheet printing function on an inspector interface, and initiates a request for printing a current checking sheet; the information statistics module requests all data needed by the printing inspection list to the data integration and preprocessing module; the data integration and preprocessing module requests a real-time data part in the required data from the data persistence module; the data persistence module receives the data, the serial numbers and the like of each sensor related to the current scene from the sensor and returns the data to the data integration and preprocessing module; the data integration and preprocessing module formats, matches information and the like on the data sent by the data persistence module, and unifies and sorts the data with inconsistent forms; the data integration and preprocessing module returns the processed real-time data to the information statistics module; the information statistics module sends the preliminarily received real-time data to the rule processing module to request comparison with rules; the rule processing module intelligently matches the received real-time data with the corresponding rule standard interval and the like, and performs conflict detection and comparison analysis; the rule processing module returns the tidied data result and the analysis result to the information statistics module; and the information statistics module integrates all the data to generate a printing list and distributes the printing list to a user for the user to check.
Fig. 5 is a flow chart of an exemplary flow management process of the present invention. A user selects the functions of adding, deleting and modifying the flow in a user interface, and initiates a management request for the flow; the flow work module calls the sub-module for flow management, and responds to a series of operations for a user request; the flow work module initiates a request for recording change information to the data integration and preprocessing module; the data integration and preprocessing module requests the data persistence module to update information on the changed equipment in time; the data persistence module returns a message of finishing updating the data integration and preprocessing module; the data integration and preprocessing module returns to the flow work module to record the completed message; the workflow work module provides an interface that the user has updated.
FIG. 6 is a flow chart of an exemplary rule management process of the present invention. A user selects the functions of adding, deleting and modifying the rules in a user interface and initiates a management request for the rules; the rule processing module calls the sub-module of rule management and responds to a series of operations for the user request; conflict detection is carried out to see whether a place with violation of the current rule exists or not before formal modification; the rule processing module initiates a request for recording change information to the data integration and preprocessing module; the data integration and preprocessing module requests the data persistence module to update information on the changed equipment in time; the data persistence module returns a message of finishing updating the data integration and preprocessing module; the data integration and preprocessing module returns to the rule processing module to record the completed message; the rule processing module returns a prompt for successful operation to the user.
The neural network path prediction model of the invention is based on an R-GCN structure. The inspection flow recommending method based on the graph neural network aims at automatically generating meaningful inspection equipment flow example paths for inspection personnel. Through a message propagation mechanism of the graph neural network, the intelligent recommendation process node path is realized. The core idea of the method is to form a historical query graph of a flow path by storing each time a worker checks an instance of the flow. By adopting the RGCN basic diagram neural network mode, the method can generate future inspection flow example path suggestions, and provides convenience for workers to better master the electricity safety condition of the production line.
Fig. 7 is a schematic diagram of a path prediction recommendation step. Generating a query history path instance according to a query history generated by the user-selected electrical appliance options; and (3) reserving all query history path constitution diagrams, inputting the query history path constitution diagrams and query nodes input by a user into a graph neural network path prediction model based on an R-GCN structure, and outputting recommended feasible query paths.
The method can improve the efficiency of the inspection flow and provide more comprehensive safety grasp and decision support for staff. Through the intelligent recommended inspection flow example path, workers can more accurately predict future inspection demands and timely take corresponding measures to ensure the electricity safety of the production line. This has positive implications for maintenance of equipment, reduction of faults and improvement of production efficiency. Therefore, the inspection flow recommending method based on the graph neural network brings greater convenience and reliability for inspection work.
The invention has the following technical effects:
the invention realizes the intelligent display of the electricity safety relationship based on the knowledge graph, which is characterized in that: the production equipment usage map databases on the production lines in all production scenes are stored in the form of multiple relation networks, visual management of the relation of the production equipment by operators is achieved, the overall control of the production environment is improved, and macroscopic regulation and control in the actual production process are achieved.
The invention realizes an inspection flow recommending method based on a graph neural network, which is characterized in that: through a message propagation mechanism of the graph neural network, the inspection flow node paths are intelligently recommended, and meaningful inspection equipment flow instance paths are generated for inspection personnel. The method has the core ideas that each time the staff checks the process, a history inquiry chart of the process is formed. By adopting the RGCN basic diagram neural network mode, the system can generate future inspection flow example path suggestions, and help workers to better know the electricity safety condition of the production line. The technical breakthrough not only improves the inspection efficiency, but also provides convenient and reliable support for the electricity safety of the production line.
The invention realizes an intelligent system for electricity safety inspection based on a process, which is characterized in that: the system realizes the electricity safety condition of the remote monitoring equipment through various sensors, receives data transmitted back from the sensors on site, displays the data to a user in a flow mode, and clearly displays the production sequence and the front-back relation of each equipment on the production line. The production equipment in an abnormal state is obtained after comparison with the rules and is fed back to the user in the form of an inspection sheet, the user can timely adjust the equipment by combining the production sequence and the alarm information after grasping the relation of the production equipment through the knowledge graph, and the safety of production personnel is ensured while the normal operation of the production line is ensured.
Claims (7)
1. An electrical safety inspection system based on multiple sensors, comprising:
the inspector view module provides electrical equipment options for a user through a visual interface, and provides a relation chart, a production line flow, an electrical equipment inspection list, flow management and rule management query service for the user according to the electrical equipment options selected by the user;
the information statistics module is used for counting all the workflows at the current moment, corresponding inspector numbers and information of whether problems occur in all the workflows; providing a query portal to receive a user query service request sent by an inspector view module;
the intelligent recommendation module generates a graph neural network path prediction model according to a historical graph path queried by a user, and generates information for recommending a future query path of the user by utilizing the path prediction model according to a current user query path;
the flow work module receives and executes the operation and query requests of the user for adding, deleting and modifying the workflow, and returns the operation and/or query results to the user;
the rule processing module receives the operation and query requests of the user for adding, deleting and modifying the rules, and returns operation and/or query results to the user;
the data integration and preprocessing module is used for receiving the state information data of the electric appliance sent by the real-time sensor, preprocessing the state information and then sending the preprocessed state information to the data persistence module for storage;
the data persistence module is used for receiving and storing the data sent by the sensor input module and the data integration and preprocessing module;
and the sensor input module is used for receiving the state data of the electric appliance collected by the various types of sensors.
2. The system of claim 1, wherein the inspector view module receives a request option from a user to provide a relationship graph,
the information statistics module requests all relation graph data information of the related nodes from the data persistence module, the data persistence module returns all relation graph data information to the information statistics module, and the information statistics module displays the graph to a user.
3. The system of claim 1, wherein the inspector view module receives a request option from a user to view a production line flow,
the information statistics module requests all equipment information of the production line from the data integration and preprocessing module, the data integration and preprocessing module requests the equipment information from the data persistence module, the data persistence module returns the equipment information to the data integration and preprocessing module, the data integration and preprocessing module integrates the equipment information, adds a table header to the equipment information and returns all the processed equipment information to the information statistics module, the information statistics module sends equipment and corresponding rules to the rule processing module, the rule processing module returns a matched result to the information statistics module after the equipment information is matched with the corresponding rules, and the information statistics module displays the result to a user.
4. The system of claim 1, wherein the inspector view module receives a request option from a user to select an appliance inspection sheet,
the information statistics module requests the data integration and preprocessing module to print all data which are needed by the user electrical appliance inspection; the data integration and preprocessing module requests a real-time data part in the required data from the data persistence module; the data persistence module receives the data and the serial numbers of each sensor related to the current scene from the sensor and returns the data to the data integration and preprocessing module; the data integration and preprocessing module formats and matches the real-time data sent by the data persistence module; the data integration and preprocessing module returns the processed real-time data to the information statistics module; the information statistics module sends the preliminarily received real-time data to the rule processing module to request comparison with rules; the rule processing module intelligently matches the received real-time data with the corresponding rule standard interval, performs conflict detection and comparison analysis; the rule processing module returns the detection data result and the analysis result to the information statistics module; and the information statistics module integrates all the data to generate a printing list.
5. The system of claim 1, wherein the inspector view module receives an option for user flow management,
the inspector view module receives and forwards a user flow management request to the flow work module; the flow work module initiates a request for recording change information to the data integration and preprocessing module; the data integration and preprocessing module requests the data persistence module to update information of the changed equipment; the data persistence module returns a message of finishing updating the data integration and preprocessing module; the data integration and preprocessing module returns to the flow work module to record the completed message; the workflow work module provides an interface that the user has updated.
6. The system of claim 1, wherein the inspector view module receives an option for user rule management,
the inspector view module receives and forwards the request of user rule management to the rule processing module, and the rule processing module firstly carries out conflict detection to judge whether the request of rule management is violated with the current rule or not; if not, the rule processing module initiates a request for recording change information to the data integration and preprocessing module; the data integration and preprocessing module requests the data persistence module to update information for the modification equipment; the data persistence module returns a message of finishing updating the data integration and preprocessing module; the data integration and preprocessing module returns to the rule processing module to record the completed message; the rule processing module returns information of successful operation to the user to the inspector view module, and the inspector view module displays the information of successful operation to the user.
7. The system of claim 1, wherein the graph neural network path prediction model is a model based on an R-GCN structure;
generating a query history path instance according to a query history generated by the user-selected electrical appliance options; and (3) reserving all query history path constitution diagrams, inputting the query history path constitution diagrams and query nodes input by a user into a graph neural network path prediction model based on an R-GCN structure, and outputting recommended feasible query paths.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311618439.6A CN117709871A (en) | 2023-11-30 | 2023-11-30 | Multi-sensor-based electricity safety inspection system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311618439.6A CN117709871A (en) | 2023-11-30 | 2023-11-30 | Multi-sensor-based electricity safety inspection system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117709871A true CN117709871A (en) | 2024-03-15 |
Family
ID=90156177
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311618439.6A Pending CN117709871A (en) | 2023-11-30 | 2023-11-30 | Multi-sensor-based electricity safety inspection system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117709871A (en) |
-
2023
- 2023-11-30 CN CN202311618439.6A patent/CN117709871A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP2697699B1 (en) | Dynamic assessment system for high-voltage electrical components | |
| CN113689013A (en) | Intelligent monitoring and operation and maintenance system for transformer | |
| CN108388950A (en) | Intelligent transformer O＆M method and system based on big data | |
| US7246014B2 (en) | Human machine interface for an energy analytics system | |
| CN107958337A (en) | A kind of information resources visualize mobile management system | |
| CN112910089A (en) | Transformer substation secondary equipment fault logic visualization method and system | |
| CN110728443A (en) | Motor full life cycle management and control system | |
| CN107066500B (en) | Power grid mass data quality verification method based on PMS model | |
| CN111591778A (en) | Remote monitoring management system and method for stacker-reclaimer based on Internet technology | |
| KR20110048771A (en) | The engineering platform system of the electric power- telemetrics and its using method | |
| JP2008202898A (en) | Failure diagnosis system of apparatus | |
| CN113541315A (en) | Power transformation information comprehensive processing system | |
| CN112186901B (en) | Panoramic sensing monitoring method and system for transformer substation | |
| JP7442001B1 (en) | Comprehensive failure diagnosis method for hydroelectric power generation units | |
| CN115313625A (en) | Transformer substation monitoring method and system | |
| CN113312200A (en) | Event processing method and device, computer equipment and storage medium | |
| CN112615436A (en) | Health diagnosis and monitoring system and method for integrated automation device of transformer substation | |
| CN116738163A (en) | Energy consumption monitoring management system and method based on rule engine | |
| CN112052965A (en) | Visual electric power equipment online management system and management method | |
| CN116991678A (en) | Intelligent operation and maintenance system of data center | |
| CN116955434A (en) | Full life cycle management and multidimensional energy efficiency analysis system for industrial equipment | |
| CN117709871A (en) | Multi-sensor-based electricity safety inspection system | |
| CN116522746A (en) | Power distribution hosting method for high-energy-consumption enterprises | |
| CN109494882B (en) | Method and system for diagnosing state of substation switch equipment | |
| CN114780625A (en) | Data management and comprehensive analysis system for civil aircraft |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |