Power transmission and distribution device real-time monitoring and intelligent early warning method and system based on multi-source data fusion

Abstract

The invention discloses a power transmission and distribution device real-time monitoring and intelligent early warning method and system based on multi-source data fusion, and relates to the technical field of power system safety monitoring and early warning. S1, collection: collecting operation data of a power transmission and distribution device from a plurality of data sources; s2, fusion: carrying out fusion processing on the collected multi-source data, and extracting key feature information; s3, monitoring: monitoring the running state of the power transmission and distribution device in real time based on the fused data; s4, early warning: generating an intelligent early warning signal according to a monitoring result; and S5, storage: carrying out comprehensive analysis and storage on monitoring and early warning results. According to the power transmission and distribution device real-time monitoring and intelligent early warning method and system based on multi-source data fusion, all-directional monitoring of the power transmission and distribution device is achieved by fusing sensor data, historical operation data, environment data and user feedback data, and the accuracy and reliability of monitoring data are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system safety monitoring and early warning, and particularly to a real-time monitoring and intelligent early warning method and system for power transmission and distribution devices based on multi-source data fusion. Background Art

[0002] With the rapid development of the power system, the safe operation of power transmission and distribution devices is crucial for ensuring the stability of power supply. However, the existing monitoring systems for power transmission and distribution devices have the following problems:

[0003] Single data source: Traditional monitoring systems usually rely on a single data source, such as sensor data or historical operation data, and cannot comprehensively reflect the true operating state of the equipment;

[0004] Limited data processing ability: Lack of effective data fusion technology, it is difficult to extract key feature information from multi-source data, resulting in inaccurate monitoring results;

[0005] Insufficiently intelligent early warning mechanism: Existing early warning systems are mostly based on simple threshold judgment, unable to give early warnings for potential faults or abnormal states, and it is difficult to meet the high requirements of modern power systems for safety and reliability;

[0006] Low system integration: Existing systems often cannot be effectively connected to the data platform of the existing production real-time system, resulting in serious data island phenomena and affecting the overall operation efficiency;

[0007] Lagging equipment maintenance: Traditional maintenance methods are mostly regular maintenance or maintenance after failure, lacking real-time evaluation of the equipment operating state and predictive maintenance, resulting in high maintenance costs and high equipment failure rates.

[0008] Therefore, it is necessary to propose a real-time monitoring and intelligent early warning method and system for power transmission and distribution devices based on multi-source data fusion to solve the above problems. Summary of the Invention

[0009] The purpose of the present invention is to provide a real-time monitoring and intelligent early warning method and system for power transmission and distribution devices based on multi-source data fusion to solve the problems of single data source, limited data processing ability, insufficiently intelligent early warning mechanism, low system integration and lagging equipment maintenance proposed in the above background art.

[0010] To achieve the above purpose, the present invention provides the following technical solutions: A real-time monitoring and intelligent early warning method for power transmission and distribution devices based on multi-source data fusion, including the following operation steps:

[0011] S1. Acquisition: Collect the operation data of the power transmission and distribution device from multiple data sources;

[0012] S2. Fusion: Perform fusion processing on the collected multi-source data to extract key feature information;

[0013] S3. Monitoring: Based on the fused data, the operating status of the power transmission and distribution device is monitored in real time;

[0014] S4. Early warning: According to the monitoring results, an intelligent early warning signal is generated;

[0015] S5. Storage: The monitoring and early warning results are comprehensively analyzed and stored.

[0016] Preferably, the data fusion processing steps include:

[0017] S21. Preprocessing the multi-source data, including data cleaning, normalization, and dimensionality reduction;

[0018] S22. Using a fusion algorithm to assign weights and extract features from the preprocessed data;

[0019] S23. Generating the fused data.

[0020] Preferably, the data source includes user feedback data;

[0021] Receiving the feedback data input by the user;

[0022] Displaying the monitoring and early warning results to the user.

[0023] The present invention also discloses a real-time monitoring and intelligent early warning system for power transmission and distribution devices based on multi-source data fusion. Using the above-mentioned real-time monitoring and intelligent early warning method for power transmission and distribution devices based on multi-source data fusion, it further includes:

[0024] A data acquisition module for collecting the operating data of the power transmission and distribution device from multiple data sources, where the data sources include sensor data, historical operating data, environmental data, and user feedback data;

[0025] A data fusion module for performing fusion processing on the collected multi-source data and extracting key feature information;

[0026] A real-time monitoring module for monitoring the operating status of the power transmission and distribution device in real time based on the fused data;

[0027] An intelligent early warning module for generating an intelligent early warning signal according to the monitoring results, where the early warning signal is based on preset early warning rules and models and can give an early warning of potential faults or abnormal states;

[0028] A central processing unit for coordinating the operation of each module and comprehensively analyzing and storing the monitoring and early warning results.

[0029] Preferably, the data acquisition module includes:

[0030] A sensor network for real-time collection of physical parameters of power transmission and distribution devices, including voltage, current, temperature, and humidity;

[0031] A data interface unit for accessing historical operation data and user feedback data;

[0032] An environmental monitoring unit for collecting relevant data on the operating environment of power transmission and distribution devices, including meteorological conditions and geographical information;

[0033] A phased array temperature field intelligent agent for displaying the global temperature field and tracking high temperatures, supporting the self-learning function of the device environmental temperature field, and having a 5G network-wide communication function.

[0034] Preferably, the data fusion module adopts at least one of the following fusion algorithms:

[0035] A data fusion algorithm based on statistical analysis;

[0036] A data fusion algorithm based on machine learning;

[0037] A data fusion algorithm based on deep learning;

[0038] The fusion algorithm performs weight assignment and feature extraction on multi-source data to generate fused data.

[0039] Preferably, the real-time monitoring module includes:

[0040] A data processing unit for real-time processing and analysis of the fused data;

[0041] A status evaluation unit for evaluating the real-time operating status of power transmission and distribution devices based on the processed data;

[0042] An anomaly detection unit for detecting anomalies in the operating status and generating corresponding anomaly reports.

[0043] Preferably, the intelligent warning module includes:

[0044] A warning rule library for storing preset warning rules and models;

[0045] A warning generation unit for generating warning signals based on the monitoring results and warning rules;

[0046] A warning notification unit for sending warning signals using the warning system;

[0047] The warning system is installed on a mobile terminal.

[0048] Preferably, the central processing unit includes:

[0049] A data storage unit for storing the collected original data, fused data, and monitoring and warning results;

[0050] An analysis and processing unit that comprehensively analyzes the stored data to generate reports and suggestions;

[0051] A communication interface unit for data communication with a mobile terminal.

[0052] Preferably, the system further includes:

[0053] A device predictive maintenance agent that detects vibration and temperature data and can communicate with a phased array temperature field agent;

[0054] A vision recognition device that supports macro imaging and wireless communication and is suitable for meter reading and monitoring applications in non-explosion-proof areas.

[0055] The technical effects and advantages of the present invention:

[0056] 1. Comprehensive monitoring: By integrating sensor data, historical operation data, environmental data, and user feedback data, it realizes all-round monitoring of the power transmission and distribution device, improving the accuracy and reliability of monitoring data;

[0057] 2. Intelligent early warning: Based on preset early warning rules and models, it can give early warnings of potential faults or abnormal states, reducing the occurrence probability of equipment failures and improving the reliability of the system;

[0058] 3. Efficient data processing: Adopting advanced data fusion algorithms, it assigns weights and extracts features from multi-source data, improving data processing efficiency and analysis accuracy;

[0059] 4. System integration: Supports interface docking with the original production real-time system data platform in the factory, meets the requirements of network security level protection, and realizes data sharing and system collaboration;

[0060] 5. Predictive maintenance: Through the device predictive maintenance agent, it realizes real-time monitoring of equipment vibration and temperature data, communicates with the phased array temperature field agent, and improves the timeliness and effectiveness of equipment maintenance;

[0061] 6. User interaction: Through the user interaction module, it receives feedback data input by the user and displays the monitoring and early warning results to the user, facilitating the user to take measures in a timely manner. Brief Description of the Drawings

[0062] Figure 1 It is a flowchart of the real-time monitoring and intelligent early warning method for power transmission and distribution devices based on multi-source data fusion of the present invention. Detailed Embodiment

[0063] The present invention provides as Figure 1The real-time monitoring and intelligent early warning method for power transmission and distribution devices based on multi-source data fusion shown in the figure includes the following operation steps:

[0064] S1. Collection: Collect the operation data of the power transmission and distribution devices from multiple data sources;

[0065] Among them, the data sources include user feedback data, specifically: Receive the feedback data input by users;

[0066] Display the monitoring and early warning results to the users. Through the user interaction module, receive the feedback data input by the users and display the monitoring and early warning results to the users, so as to facilitate the users to take measures in a timely manner.

[0067] S2. Fusion: Perform fusion processing on the collected multi-source data and extract key feature information;

[0068] The data fusion processing steps include:

[0069] S21. Preprocess the multi-source data, including data cleaning, normalization, and dimensionality reduction;

[0070] S22. Use a fusion algorithm to perform weight assignment and feature extraction on the preprocessed data;

[0071] S23. Generate the fused data;

[0072] S3. Monitoring: Real-time monitor the operation status of the power transmission and distribution devices based on the fused data;

[0073] S4. Early warning: Generate an intelligent early warning signal according to the monitoring results;

[0074] S5. Storage: Comprehensively analyze and store the monitoring and early warning results.

[0075] This method is particularly applicable to GIS power transmission and distribution devices.

[0076] The present invention also discloses a real-time monitoring and intelligent early warning system for power transmission and distribution devices based on multi-source data fusion. Using the above-mentioned real-time monitoring and intelligent early warning method for power transmission and distribution devices based on multi-source data fusion, it further includes:

[0077] A data acquisition module for collecting the operation data of the power transmission and distribution devices from multiple data sources. The data sources include sensor data, historical operation data, environmental data, and user feedback data;

[0078] Specifically, the data acquisition module includes:

[0079] A sensor network for real-time collecting the physical parameters of the power transmission and distribution devices, including voltage, current, temperature, humidity, etc.;

[0080] Voltage, such as but not limited to voltage sensors, etc., can be used; current, such as but not limited to current sensors, etc., can be used; temperature, such as but not limited to infrared temperature sensors, etc., can be used; humidity, such as but not limited to humidity sensors, etc., can be adjusted according to specific usage conditions.

[0081] The data interface unit is used to access historical operation data and user feedback data;

[0082] The environmental monitoring unit is used to collect relevant data on the operation environment of the power transmission and distribution device, including meteorological conditions and geographical information;

[0083] The phased array temperature field intelligent agent is used for global temperature field display and high-temperature tracking, supports the self-learning function of the device environmental temperature field, and has a 5G network-wide communication function.

[0084] Comprehensive monitoring: By integrating sensor data, historical operation data, environmental data, and user feedback data, it realizes the all-round monitoring of the power transmission and distribution device, improving the accuracy and reliability of the monitoring data.

[0085] The data fusion module is used to fuse and process the multi-source data collected, and extract key feature information;

[0086] The data fusion module adopts at least one of the following fusion algorithms:

[0087] The data fusion algorithm based on statistical analysis;

[0088] The data fusion algorithm based on machine learning;

[0089] The data fusion algorithm based on deep learning;

[0090] The fusion algorithm performs weight assignment and feature extraction on the multi-source data to generate the fused data.

[0091] The algorithm based on statistical analysis is suitable for processing structured data and provides an accurate mathematical model; the algorithm based on machine learning has strong flexibility and is applicable to various data types; while the algorithm based on deep learning performs excellently in processing unstructured data, but requires a large amount of data and computing resources.

[0092] The data fusion module adopts the fusion algorithm based on deep learning to perform weight assignment and feature extraction on the multi-source data, and generate the fused data. The specific steps include:

[0093] Data preprocessing: Clean, normalize, and reduce the dimension of the multi-source data to remove noise and redundant information.

[0094] Weight assignment: Assign weights to different data sources according to the reliability and relevance of the data sources.

[0095] Feature extraction: Extract key feature information from the fused data for subsequent monitoring and early warning.

[0096] Efficient data processing: Adopt advanced data fusion algorithms to assign weights and extract features from multi-source data, improving data processing efficiency and analysis accuracy.

[0097] A real-time monitoring module for real-time monitoring of the operating status of power transmission and distribution devices based on the fused data;

[0098] The real-time monitoring module includes:

[0099] A data processing unit for real-time processing and analysis of the fused data;

[0100] A status evaluation unit for evaluating the real-time operating status of power transmission and distribution devices based on the processed data;

[0101] An anomaly detection unit for detecting anomalies in the operating status and generating corresponding anomaly reports.

[0102] An intelligent early warning module for generating intelligent early warning signals based on the monitoring results. The early warning signals are based on preset early warning rules and models and can provide early warnings for potential faults or abnormal states;

[0103] The intelligent early warning module includes:

[0104] An early warning rule library for storing preset early warning rules and models;

[0105] An early warning generation unit for generating early warning signals based on the monitoring results and early warning rules;

[0106] An early warning notification unit for sending out early warning signals using the early warning system;

[0107] The early warning system is installed on a mobile terminal.

[0108] A central processing unit for coordinating the operation of each module and comprehensively analyzing and storing the monitoring and early warning results.

[0109] The central processing unit includes:

[0110] A data storage unit for storing the collected raw data, fused data, and monitoring and early warning results;

[0111] An analysis and processing unit for comprehensively analyzing the stored data and generating reports and suggestions;

[0112] A communication interface unit for data communication with the mobile terminal.

[0113] In addition, the system also includes:

[0114] The device predictive maintenance agent detects vibration and temperature data and is capable of communicating with the phased array temperature field agent;

[0115] For vibration, it can use but is not limited to vibration sensors, etc.;

[0116] For temperature, it can use but is not limited to temperature sensors, etc.

[0117] The vision recognition device supports macro imaging and wireless communication and is suitable for meter reading and monitoring applications in non-explosion-proof areas.

[0118] Moreover, the system supports interface docking with the original production real-time system data platform in the factory, meets the requirements of network security level protection, and realizes data sharing and system collaboration.

Claims

1. A real-time monitoring and intelligent early warning method for power transmission and distribution devices based on multi-source data fusion, characterized in that, It includes the following operation steps: S1. Collection: Collect the operation data of the power transmission and distribution device from multiple data sources; S2. Fusion: Perform fusion processing on the multi-source data collected, and extract key feature information; S3. Monitoring: Based on the fused data, conduct real-time monitoring on the operation status of the power transmission and distribution device; S4. Early warning: Generate an intelligent early warning signal according to the monitoring result; S5. Storage: Conduct comprehensive analysis and storage on the monitoring and early warning results.

2. The real-time monitoring and intelligent early warning method for power transmission and distribution devices based on multi-source data fusion according to claim 1, characterized in that, The data fusion processing step includes: S21. Preprocess the multi-source data, including data cleaning, normalization, and dimensionality reduction; S22. Use a fusion algorithm to perform weight assignment and feature extraction on the preprocessed data; S23. Generate the fused data.

3. The real-time monitoring and intelligent early warning method for power transmission and distribution devices based on multi-source data fusion according to claim 1, characterized in that, The data source includes user feedback data; Receive the feedback data input by the user; Display the monitoring and early warning results to the user.

4. A real-time monitoring and intelligent early warning system for power transmission and distribution devices based on multi-source data fusion, characterized in that, Using the real-time monitoring and intelligent early warning method for power transmission and distribution devices based on multi-source data fusion as described in any one of claims 1 to 3, further includes: A data collection module, used to collect the operation data of the power transmission and distribution device from multiple data sources, and the data sources include sensor data, historical operation data, environmental data, and user feedback data; A data fusion module, used to perform fusion processing on the multi-source data collected, and extract key feature information; A real-time monitoring module, used to conduct real-time monitoring on the operation status of the power transmission and distribution device based on the fused data; An intelligent early warning module, used to generate an intelligent early warning signal according to the monitoring result, and the early warning signal is based on preset early warning rules and models, and can conduct early warning on potential faults or abnormal states in advance; A central processing unit, used to coordinate the operation of each module, and conduct comprehensive analysis and storage on the monitoring and early warning results.

5. The real-time monitoring and intelligent early warning system for power transmission and distribution devices based on multi-source data fusion according to claim 4, characterized in that, The data collection module includes: A sensor network, used to collect the physical parameters of the power transmission and distribution device in real time, including voltage, current, temperature, and humidity; A data interface unit, used to access historical operation data and user feedback data; An environmental monitoring unit, used to collect the relevant data of the operation environment of the power transmission and distribution device, including meteorological conditions and geographical information; A phased array temperature field intelligent agent, used for global temperature field display and high-temperature tracking, supporting the self-learning function of the device environment temperature field, and having a 5G network-wide communication function.

6. The real-time monitoring and intelligent warning system for power transmission and distribution devices based on multi-source data fusion according to claim 4, characterized in that, The data fusion module adopts at least one of the following fusion algorithms: A data fusion algorithm based on statistical analysis; A data fusion algorithm based on machine learning; A data fusion algorithm based on deep learning; The fusion algorithm performs weight assignment and feature extraction on the multi-source data to generate the fused data.

7. The real-time monitoring and intelligent early warning system for power transmission and distribution devices based on multi-source data fusion according to claim 4, characterized in that, The real-time monitoring module includes: A data processing unit, which conducts real-time processing and analysis on the fused data; A status evaluation unit, which evaluates the real-time operation status of the power transmission and distribution device according to the processed data; An anomaly detection unit, which detects anomalies in the operation status and generates corresponding anomaly reports.

8. The real-time monitoring and intelligent warning system for power transmission and distribution devices based on multi-source data fusion according to claim 4, characterized in that, The intelligent early warning module includes: An early warning rule library, which stores preset early warning rules and models; An early warning generation unit, which generates an early warning signal according to the monitoring result and early warning rules; An early warning notification unit, which uses the early warning system to issue an early warning signal; The early warning system is installed on a mobile terminal.

9. The real-time monitoring and intelligent early warning system for power transmission and distribution devices based on multi-source data fusion according to claim 8, characterized in that, The central processing unit includes: A data storage unit that stores the collected raw data, the fused data, and the monitoring and early warning results; An analysis and processing unit that comprehensively analyzes the stored data and generates reports and suggestions; A communication interface unit for data communication with a mobile terminal.

10. The real-time monitoring and intelligent early warning system for power transmission and distribution devices based on multi-source data fusion according to claim 5, characterized in that The system further includes: A device predictive maintenance agent that detects vibration and temperature data and is capable of communicating with a phased array temperature field agent; A vision recognition device that supports macro imaging and wireless communication and is applicable to meter reading and monitoring applications in non-explosion-proof areas.

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