Beidou power transmission line on-line monitoring system and monitoring method

Abstract

The invention belongs to the technical field of power transmission line supervision, and particularly relates to a Beidou power transmission line on-line monitoring system and method, and the system comprises a Beidou high-precision positioning collection module, a multi-parameter environment sensing module, a data preprocessing fusion module, an intelligent fault diagnosis module, a Beidou short message communication module and a ground monitoring center. According to the invention, the Beidou high-precision positioning acquisition module acquires position information of power transmission line towers and wires in real time, the multi-parameter environment sensing module senses environment parameters around a power transmission line, and the data preprocessing and fusion module preprocesses and fuses the acquired data. The operation state of the power transmission line is analyzed and diagnosed in real time based on the comprehensive monitoring data, and the fault diagnosis result and the comprehensive monitoring data are transmitted to a ground monitoring center in real time, so that the state and position of the power transmission line are accurately monitored, and the accuracy and timeliness of fault positioning are effectively improved. And a powerful guarantee is provided for safe and stable operation of the power transmission line.

Description

Technical Field

[0001] This invention relates to the field of power transmission line monitoring technology, specifically a BeiDou power transmission line online monitoring system and monitoring method. Background Technology

[0002] Transmission lines are a key component of the power system used to transmit and distribute electrical energy. They are typically composed of conductors, insulators, towers, grounding devices, etc. Their core function is to transmit the electrical energy generated by power plants over long distances to load centers, and then distribute it to end users through the distribution network. A method and system for online monitoring of transmission lines is disclosed in Chinese invention patent with publication number CN116363585A. The invention uses binocular ranging technology to perform three-dimensional reconstruction, uses three-dimensional target detection technology to calculate the location and category of dangerous targets, and uses a three-dimensional coordinate database to obtain the warning level, thereby monitoring the safety of transmission lines. This allows inspection personnel to obtain alarm reminders in real time and grasp the on-site situation, greatly improving monitoring efficiency. However, in practical applications, the above-mentioned invention mainly focuses on detecting dangerous targets through monitoring devices. It cannot accurately monitor the status and location of transmission lines and realize fault identification and location. Furthermore, it cannot reasonably assess the operational risks of transmission lines and accurately judge the management safety of corresponding areas, which is not conducive to ensuring the safety and stability of transmission lines. To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0003] The purpose of this invention is to provide a Beidou online monitoring system and method for power transmission lines, which solves the problems of existing technologies being unable to accurately monitor the status and location of power transmission lines and to identify and locate faults, and being unable to reasonably assess the operational risks of power transmission lines and accurately determine the management safety of corresponding areas, which is not conducive to ensuring the safety and stability of power transmission lines.

[0004] To achieve the above objectives, the present invention provides the following technical solution: A BeiDou power transmission line online monitoring system includes a BeiDou high-precision positioning acquisition module, a multi-parameter environmental perception module, a data preprocessing and fusion module, an intelligent fault diagnosis module, a BeiDou short message communication module, and a ground monitoring center. The BeiDou high-precision positioning acquisition module collects the position information of the transmission line towers and conductors in real time, and uses the high-precision positioning technology of BeiDou satellites to obtain accurate latitude and longitude coordinates and altitude data. The multi-parameter environmental perception module is used to sense the environmental parameters around the transmission line and collect various environmental data around the transmission line; the data preprocessing and fusion module preprocesses and fuses the data collected by the Beidou high-precision positioning acquisition module and the multi-parameter environmental perception module to generate comprehensive monitoring data and send it to the intelligent fault diagnosis module; the intelligent fault diagnosis module uses intelligent algorithms to analyze and diagnose the operating status of the transmission line in real time based on the comprehensive monitoring data to determine whether there is a fault in the transmission line; The BeiDou short message communication module utilizes the short message communication function of the BeiDou satellite to transmit fault diagnosis results and comprehensive monitoring data to the ground monitoring center in real time. The ground monitoring center receives the data sent by the BeiDou short message communication module, decapsulates and parses it, stores the parsed data in the database of the ground monitoring center, and visualizes the monitoring data and fault diagnosis results to the operation and maintenance personnel through a visual interface. In addition, the BeiDou short message communication module is also used to receive instructions sent by the ground monitoring center, and parses and executes the instructions.

[0005] Furthermore, the multi-parameter environmental sensing module integrates various types of sensors, including temperature sensors, humidity sensors, wind speed and direction sensors, rainfall sensors, and insulator pollution sensors. Each sensor collects the corresponding environmental parameters in real time and converts analog signals into digital signals. The multi-parameter environmental sensing module performs preliminary processing on the collected digital signals, including filtering and amplification, and encapsulates and stores the processed data in a unified data format.

[0006] Furthermore, the data preprocessing and fusion module obtains raw data from the BeiDou high-precision positioning acquisition module and the multi-parameter environmental perception module. Specifically, for the positioning data, the Kalman filter algorithm is used to smooth the data and remove measurement noise. For the environmental parameter data, data normalization is performed to convert data of different dimensions into a unified standard range. Finally, the data fusion algorithm is used to fuse the positioning data and environmental parameter data to generate comprehensive monitoring data.

[0007] Furthermore, the specific operation process of the intelligent fault diagnosis module includes: Comprehensive monitoring data is obtained from the data preprocessing and fusion module. Feature extraction is performed on the data to extract fault-related feature parameters, including tower tilt angle, conductor galloping amplitude, and insulator contamination level. A machine learning-based fault diagnosis algorithm is used to analyze and judge the extracted feature parameters. The feature parameters of the current monitoring data are compared with the pre-established fault model, and the similarity is used to determine whether there is a fault in the transmission line. If a fault is determined, the type and location of the fault are further determined.

[0008] Furthermore, the ground monitoring center has a communication connection to a line risk assessment module. This module is used to set the detection period, assess and analyze the risk of the transmission lines during the detection period, and mark the corresponding transmission lines as low-risk lines or lines with potential hazards through analysis. The marking information of the corresponding transmission lines is then sent to the ground monitoring center.

[0009] Furthermore, the specific analysis process of the line risk assessment module is as follows: All faults that occurred on the corresponding transmission line during the detection period were obtained and classified. The occurrence frequency of each type of fault was marked as the category feature value. Each type of fault was pre-set with a set of preset weight values. The category feature value of the corresponding type of fault was multiplied with the corresponding preset weight value, and the product was marked as the category risk factor. The category risk factors of all types of faults that occurred on the corresponding transmission line during the detection period were summed to obtain the total fault risk value. The total duration of the corresponding transmission line in a fault state during the detection period is collected and marked as the total fault duration performance value. The number of times the duration of a single fault state of the corresponding transmission line exceeds the preset duration threshold during the detection period is marked as the fault risk performance value. The line risk assessment coefficient is calculated by weighting and summing the total value of potential faults, the total fault duration, and the fault risk holding value. The line risk assessment coefficient is then compared with a preset line risk assessment coefficient threshold. If the line risk assessment coefficient exceeds the preset threshold, the corresponding transmission line is marked as a line with potential risks; if the line risk assessment coefficient does not exceed the preset threshold, the corresponding transmission line is marked as a low-risk line.

[0010] Furthermore, the line risk assessment module communicates with the regional multi-dimensional analysis module. The line risk assessment module sends the line risk assessment coefficient and marking information of the transmission line to the regional multi-dimensional analysis module. The regional multi-dimensional analysis module marks the number of lines with hidden dangers in the management area as hidden danger detection values. It compares the hidden danger detection values ​​with the preset hidden danger detection threshold. If the hidden danger detection value exceeds the preset hidden danger detection threshold, the management area is marked as a key area. If the detected value of potential hazards does not exceed the preset threshold for potential hazards, the total number of transmission lines in the management area will be marked as the line statistics value, and the average value of the line risk assessment coefficients of all transmission lines in the management area will be calculated to obtain the risk assessment characteristic value. The detected value of potential hazards, the line statistics value and the risk assessment characteristic value will be weighted and summed to obtain the comprehensive evaluation value of the lines in the area. The comprehensive evaluation value of the regional line is compared with the preset comprehensive evaluation threshold of the regional line. If the comprehensive evaluation value of the regional line exceeds the preset comprehensive evaluation threshold of the regional line, the management area is marked as a key area; if the comprehensive evaluation value of the regional line does not exceed the preset comprehensive evaluation threshold of the regional line, the management area is marked as a non-key area; and the marking information of the management area is sent to the ground monitoring center.

[0011] Furthermore, the regional multi-dimensional analysis module is used to conduct management security assessment of the managed area. Through assessment and analysis, the management assessment characteristic values ​​within the monitoring period are obtained. If the managed area is a key area, a preset management assessment characteristic threshold FX1 is assigned to it; if the managed area is a non-key area, a preset management assessment characteristic threshold FX2 is assigned to it, and FX2 > FX1 > 0. The system compares the management evaluation feature value with the corresponding preset management evaluation feature threshold. If the management evaluation feature value exceeds the corresponding preset management evaluation feature threshold, a management evaluation non-qualified signal is generated. If the management evaluation feature value does not exceed the corresponding preset management evaluation feature threshold, a management evaluation qualified signal is generated, and the management evaluation non-qualified signal or management evaluation qualified signal is sent to the ground monitoring center.

[0012] Furthermore, the method for obtaining the characteristic values ​​of the management evaluation is as follows: The average response time for transmission line faults in the management area during the monitoring period is obtained and marked as the time characteristic value. The number of times the response time for transmission line faults in the management area exceeds the preset response time threshold during the monitoring period is marked as the response anomaly measurement value. The time during which no supervisory personnel are present in the management area during the monitoring period is marked as the unattended time measurement value. The management evaluation characteristic value is obtained by weighted summation of the time characteristic value, the response anomaly measurement value, and the unattended time measurement value.

[0013] Furthermore, this invention also proposes an online monitoring method for BeiDou power transmission lines, comprising the following steps: Step 1: Real-time acquisition of location information for transmission line towers and conductors; Step 2: Collect various environmental data around the transmission line; Step 3: Preprocess and fuse the collected data to generate comprehensive monitoring data; Step 4: Based on comprehensive monitoring data, use intelligent algorithms to analyze and diagnose the operating status of the transmission lines in real time to determine whether there are any faults in the transmission lines; Step 5: Utilize the short message communication function of the BeiDou satellite to transmit the fault diagnosis results and comprehensive monitoring data to the ground monitoring center in real time.

[0014] Compared with the prior art, the beneficial effects of the present invention are: 1. In this invention, the location information of transmission line towers and conductors is collected in real time by the Beidou high-precision positioning acquisition module, and the environmental parameters around the transmission line are sensed by the multi-parameter environmental perception module. The collected data is preprocessed and fused to diagnose the operating status of the transmission line. The fault diagnosis results and comprehensive monitoring data are transmitted to the ground monitoring center in real time, so as to realize the accurate monitoring of the status and location of the transmission line, improve the accuracy and timeliness of fault location, and provide strong guarantee for the safe and stable operation of the transmission line. 2. In this invention, the risk assessment module is used to assess and analyze the risk of transmission lines during the detection period, thereby strengthening the monitoring and management of lines with potential hazards in a timely manner. This helps to ensure the safety and stability of power transmission. Furthermore, by reasonably analyzing and accurately outputting the management difficulty and risks of the management area, it is beneficial to formulate reasonable subsequent supervision plans, further ensuring the safety and stability of transmission lines. The invention also demonstrates a high level of intelligence. Attached Figure Description

[0015] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings; Figure 1 This is a system block diagram of Embodiment 1 of the present invention; Figure 2 This is a system block diagram of Embodiments 2 and 3 of the present invention; Figure 3 This is a flowchart of the method in Embodiment 4 of the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Example 1: As Figure 1 As shown, the present invention proposes a Beidou transmission line online monitoring system, which includes a Beidou high-precision positioning and acquisition module, a multi-parameter environmental perception module, a data preprocessing and fusion module, an intelligent fault diagnosis module, a Beidou short message communication module, and a ground monitoring center. The BeiDou high-precision positioning acquisition module (with a built-in BeiDou high-precision positioning chip, which calculates the three-dimensional coordinates of towers and conductors by receiving signals transmitted by BeiDou satellites) collects the position information of transmission line towers and conductors in real time. Utilizing the high-precision positioning technology of BeiDou satellites, it obtains accurate latitude and longitude coordinates and altitude data. The high-precision positioning data can accurately reflect the positional changes of towers and conductors, providing a reliable basis for timely detection of anomalies such as tower tilting and conductor galloping, and effectively improving the accuracy of monitoring.

[0018] The multi-parameter environmental sensing module is used to sense the environmental parameters around the transmission line and collect various environmental data around the transmission line, including temperature, humidity, wind speed, wind direction, rainfall, and insulator pollution level. It can comprehensively grasp the operating environment of the transmission line, provide richer information for fault diagnosis, help to discover potential safety hazards in advance, and improve the reliability of the line. It should be noted that the multi-parameter environmental sensing module integrates various types of sensors, such as temperature sensors, humidity sensors, wind speed and direction sensors, rainfall sensors, and insulator pollution sensors. Each sensor collects the corresponding environmental parameters in real time and converts the analog signals into digital signals. The multi-parameter environmental sensing module performs preliminary processing on the collected digital signals, such as filtering and amplification, to improve the data quality. It also encapsulates and stores the processed data in a unified data format.

[0019] The data preprocessing and fusion module preprocesses and fuses the data collected by the Beidou high-precision positioning acquisition module and the multi-parameter environmental perception module to generate comprehensive monitoring data and send it to the intelligent fault diagnosis module. Through data preprocessing and fusion, noise data can be effectively removed, the quality and consistency of the data can be improved, and subsequent fault diagnosis can be more accurate and reliable, reducing the occurrence of misjudgment and missed judgment. Specifically, the data preprocessing and fusion module first obtains raw data from the BeiDou high-precision positioning acquisition module and the multi-parameter environmental perception module. For the positioning data, a Kalman filter algorithm is used to smooth the data, remove measurement noise, and improve the accuracy of the positioning data. For the environmental parameter data, data normalization is performed to convert data of different dimensions into a unified standard range. Then, a data fusion algorithm (such as the weighted average method) is used to fuse the positioning data and environmental parameter data to generate comprehensive monitoring data.

[0020] The intelligent fault diagnosis module, based on comprehensive monitoring data, uses intelligent algorithms to perform real-time analysis and diagnosis of the operating status of transmission lines, determining whether faults exist. It can diagnose transmission line faults accurately and in real time, providing timely fault information to maintenance personnel, facilitating rapid repair and handling, and reducing power outage time and economic losses. Specifically, the operation process of the intelligent fault diagnosis module includes: Comprehensive monitoring data is obtained from the data preprocessing and fusion module. First, feature extraction is performed on the data to extract fault-related feature parameters, such as tower tilt angle, conductor galloping amplitude, and insulator contamination level. Then, a machine learning-based fault diagnosis algorithm (such as support vector machine algorithm) is used to analyze and judge the extracted feature parameters. The feature parameters of the current monitoring data are compared with the pre-established fault model, and the similarity is used to determine whether there is a fault in the transmission line. If a fault is determined, the type and location of the fault are further determined.

[0021] The BeiDou short message communication module utilizes the short message communication function of the BeiDou satellite to transmit fault diagnosis results and comprehensive monitoring data to the ground monitoring center in real time. (That is, it periodically reads fault diagnosis results and comprehensive monitoring data, encapsulates the data according to the BeiDou short message communication protocol, and then sends the encapsulated data to the BeiDou satellite through the BeiDou terminal equipment, and then the BeiDou satellite forwards the data to the ground monitoring center.) This solves the data transmission problem in areas without public network coverage, ensures the real-time and reliable transmission of monitoring data, and improves the applicability and reliability of the system.

[0022] The ground monitoring center receives data sent by the BeiDou short message communication module, decapsulates and parses it, and stores the parsed data in its database. The monitoring data and fault diagnosis results are then visualized and presented to maintenance personnel through a graphical interface in the form of charts and reports. This allows maintenance personnel to understand the real-time operating status of the transmission lines and make decisions based on the displayed information, such as scheduling maintenance tasks and adjusting operating parameters. Furthermore, the BeiDou short message communication module also receives and parses commands from the ground monitoring center, such as data query commands and equipment control commands, and executes these commands.

[0023] Example 2: Figure 2 As shown, the difference between this embodiment and Embodiment 1 lies in the communication connection between the ground monitoring center and the line risk assessment module. This module is used to set the detection period, preferably fifteen days. During the detection period, the risk of the transmission lines is assessed and analyzed. Through this analysis, the corresponding transmission lines are marked as low-risk lines or lines with potential hazards, and the marking information is sent to the ground monitoring center. This timely strengthening of monitoring and management of lines with potential hazards helps ensure the transmission safety and stability of the transmission lines. The specific analysis process of the line risk assessment module is as follows: All faults that occur on the corresponding transmission line during the detection period are obtained and classified. The occurrence frequency of each type of fault is marked as the category feature value. Each type of fault is pre-set with a set of preset weight values ​​that are greater than zero. Furthermore, the greater the adverse impact of the corresponding type of fault on the transmission line, the greater the value of the preset weight value that matches it. Multiply the category feature value of the corresponding type of fault by the corresponding preset weight value, and mark the product as the category risk factor. Summate the category risk factors of all types of faults that appear on the corresponding transmission line during the detection period to obtain the total fault risk value. The total duration of the corresponding transmission line in a fault state during the detection period is collected and marked as the total fault duration performance value. The number of times the duration of a single fault state of the corresponding transmission line exceeds the preset duration threshold during the detection period is marked as the fault risk performance value. The line risk assessment coefficient is calculated by weighting and summing the total fault risk value, the total fault duration value, and the fault risk holding value. Specifically, each of the three values ​​is assigned a corresponding preset weight coefficient, and then multiplied by its respective preset weight coefficient. The sum of these three products is then marked as the line risk assessment coefficient. It should be noted that the larger the line risk assessment coefficient, the higher the overall operational risk of the corresponding transmission line during the detection period. The line risk assessment coefficient is compared with the preset line risk assessment coefficient threshold. If the line risk assessment coefficient exceeds the preset line risk assessment coefficient threshold, it indicates that the overall operational risk of the corresponding transmission line is relatively high during the inspection period, and the corresponding transmission line is marked as a line with potential risks. If the line risk assessment coefficient does not exceed the preset line risk assessment coefficient threshold, it indicates that the overall operational risk of the corresponding transmission line is relatively low during the inspection period, and the corresponding transmission line is marked as a low-risk line.

[0024] Example 3: Figure 2 As shown, the difference between this embodiment and Embodiments 1 and 2 is that the line risk assessment module is connected to the regional multi-dimensional analysis module. The line risk assessment module sends the line risk assessment coefficient and marking information of the transmission line to the regional multi-dimensional analysis module. The regional multi-dimensional analysis module marks the number of lines with hidden dangers in the management area as the hidden danger detection value. The hidden danger detection value is compared with the preset hidden danger detection threshold. If the hidden danger detection value exceeds the preset hidden danger detection threshold, it indicates that the transmission line management in the management area is more difficult, and the management area is marked as a key area. If the detected value of potential hazards does not exceed the preset threshold for potential hazards, the total number of transmission lines in the management area will be marked as the line statistics value, and the average value of the line hazard judgment coefficients of all transmission lines in the management area will be calculated to obtain the hazard judgment characteristic value. The comprehensive evaluation value of the regional power lines is obtained by weighted summation of the detected hidden danger values, line statistics values, and risk assessment characteristic values. Specifically, each of the detected hidden danger values, line statistics values, and risk assessment characteristic values ​​is assigned a corresponding preset weight coefficient, and each of these values ​​is multiplied by its corresponding preset weight coefficient. The sum of the three products is then marked as the risk assessment characteristic value. It should be noted that the larger the value of the risk assessment characteristic value, the greater the overall difficulty of managing the transmission lines in the management area. The comprehensive evaluation value of the regional transmission lines is compared with the preset comprehensive evaluation threshold. If the comprehensive evaluation value exceeds the preset threshold, it indicates that the overall management difficulty of the transmission lines in the management area is relatively high, and the management area is marked as a key area. If the comprehensive evaluation value does not exceed the preset threshold, it indicates that the overall management difficulty of the transmission lines in the management area is relatively low, and the management area is marked as a non-strict area. The marking information of the management area is sent to the ground monitoring center to facilitate the subsequent development of corresponding management plans for different areas, strengthen the supervision of transmission lines in key areas, and ensure the safety and stability of power transmission.

[0025] Furthermore, the regional multi-dimensional analysis module is used to conduct management security assessment of the management area, obtain the average response time for transmission line faults in the management area during the monitoring period and mark it as the time characteristic value, mark the number of times the response time for transmission line faults in the management area exceeds the preset response time threshold as the response anomaly measurement value, and mark the time during which no supervisory personnel are present in the management area during the monitoring period as the unattended time measurement value. The management assessment characteristic value is obtained by weighted summation of the time-based characteristic value, the anomaly detection value, and the unattended time-based measurement value. Specifically, each of the time-based characteristic value, anomaly detection value, and unattended time-based measurement value is assigned a corresponding preset weight coefficient, and then each of these values ​​is multiplied by its respective preset weight coefficient. The sum of these three products is then labeled as the management assessment characteristic value. It should be noted that the larger the value of the management assessment characteristic value, the higher the overall management risk for the managed area during the monitoring period. If the management area is a key area, a preset management assessment characteristic threshold FX1 is assigned to it; if the management area is a non-strict area, a preset management assessment characteristic threshold FX2 is assigned to it, and FX2 > FX1 > 0; the management assessment characteristic value is compared with the corresponding preset management assessment characteristic threshold. If the management assessment characteristic value exceeds the corresponding preset management assessment characteristic threshold, it indicates that the overall management risk of the management area is relatively high during the monitoring period, and a management assessment non-qualification signal is generated. If the management assessment characteristic value does not exceed the corresponding preset management assessment characteristic threshold, it indicates that the overall management risk of the management area during the monitoring period is relatively low. In this case, a management assessment qualified signal is generated, and a management assessment unqualified signal or a management assessment qualified signal is sent to the ground monitoring center. When the ground monitoring center receives the management assessment unqualified signal, it issues a corresponding warning to strengthen the training and supervision of personnel in the corresponding management area in a timely manner, thereby significantly reducing the management risk of the management area.

[0026] Example 4: Figure 3 As shown, the difference between this embodiment and Embodiments 1, 2, and 3 is that the online monitoring method for BeiDou transmission lines proposed in this invention includes the following steps: Step 1: Real-time acquisition of location information for transmission line towers and conductors; Step 2: Collect various environmental data around the transmission line; Step 3: Preprocess and fuse the collected data to generate comprehensive monitoring data; Step 4: Based on comprehensive monitoring data, use intelligent algorithms to analyze and diagnose the operating status of the transmission lines in real time to determine whether there are any faults in the transmission lines; Step 5: Utilize the short message communication function of the BeiDou satellite to transmit the fault diagnosis results and comprehensive monitoring data to the ground monitoring center in real time.

[0027] The working principle of this invention is as follows: During use, the BeiDou high-precision positioning acquisition module collects real-time location information of transmission line towers and conductors; the multi-parameter environmental perception module senses environmental parameters around the transmission line; the data preprocessing and fusion module preprocesses and fuses the collected data to generate comprehensive monitoring data; the intelligent fault diagnosis module analyzes and diagnoses the operating status of the transmission line in real time based on the comprehensive monitoring data to determine whether a fault exists; and the BeiDou short message communication module transmits the fault diagnosis results and comprehensive monitoring data to the ground monitoring center in real time. By leveraging BeiDou high-precision positioning technology and environmental perception technology, precise monitoring of the transmission line's status and location is achieved, effectively improving the accuracy and timeliness of fault location, reducing inspection costs and labor intensity, and ensuring reliable data transmission even in areas without public network coverage, ensuring the continuity and stability of monitoring. This provides strong support for the safe and stable operation of transmission lines and greatly improves the level and reliability of power grid operation and maintenance management.

[0028] In this invention, the threshold, preset value, or preset range settings are for result comparison and analysis to determine whether the result is good or bad. The magnitude of these values ​​is determined by a combination of large-scale model analysis of sample data and human experience, and can also be appropriately adjusted based on seasonal or common-sense influence conditions. Similarly, the preset weight coefficients and influence factors are assigned specific values ​​based on the magnitude of each parameter's influence on the result, ultimately reflecting the impact on the result. These settings are also determined by a combination of large-scale model analysis of sample data and human experience, and can also be appropriately adjusted based on seasonal or common-sense influence conditions.

[0029] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, enabling those skilled in the art to better understand and utilize it. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A BeiDou-based online monitoring system for power transmission lines, characterized in that, It includes a BeiDou high-precision positioning acquisition module, a multi-parameter environmental perception module, a data preprocessing and fusion module, an intelligent fault diagnosis module, a BeiDou short message communication module, and a ground monitoring center. The BeiDou high-precision positioning acquisition module collects the location information of transmission line towers and conductors in real time. The multi-parameter environmental perception module is used to perceive the environmental parameters around the transmission line. The data preprocessing and fusion module preprocesses and fuses the collected data to generate comprehensive monitoring data and sends it to the intelligent fault diagnosis module. The intelligent fault diagnosis module uses intelligent algorithms to analyze and diagnose the operating status of transmission lines in real time based on comprehensive monitoring data, and determines whether there are faults in the transmission lines. The Beidou short message communication module uses the short message communication function of Beidou satellites to transmit the fault diagnosis results and comprehensive monitoring data to the ground monitoring center in real time. The ground monitoring center receives the data sent by the Beidou short message communication module, decapsulates and parses it, and displays the monitoring data and fault diagnosis results to the operation and maintenance personnel through a visual interface.

2. The Beidou online monitoring system for power transmission lines according to claim 1, characterized in that, The multi-parameter environmental sensing module integrates various types of sensors, including temperature sensors, humidity sensors, wind speed and direction sensors, rainfall sensors, and insulator pollution sensors.

3. The Beidou online monitoring system for power transmission lines according to claim 1, characterized in that, The data preprocessing and fusion module acquires raw data from the BeiDou high-precision positioning acquisition module and the multi-parameter environmental perception module. For the positioning data, the Kalman filter algorithm is used to smooth the data and remove measurement noise. For the environmental parameter data, the data is normalized to convert data of different dimensions into a unified standard range. The data fusion algorithm is used to fuse the positioning data and environmental parameter data to generate comprehensive monitoring data.

4. The Beidou online monitoring system for power transmission lines according to claim 1, characterized in that, The specific operation process of the intelligent fault diagnosis module includes: Comprehensive monitoring data is obtained from the data preprocessing and fusion module, and fault-related feature parameters are extracted. A fault diagnosis algorithm based on machine learning is used to analyze and judge the extracted feature parameters. The feature parameters of the current monitoring data are compared with the pre-established fault model, and the similarity is used to determine whether there is a fault in the transmission line. If a fault is determined, the type and location of the fault are further determined.

5. The Beidou online monitoring system for power transmission lines according to claim 1, characterized in that, The ground monitoring center has a communication connection to the line risk assessment module. This module is used to set the detection period, assess and analyze the risk of the transmission lines during the detection period, and mark the corresponding transmission lines as low-risk lines or lines with potential hazards. The marking information of the corresponding transmission lines is then sent to the ground monitoring center.

6. The Beidou online monitoring system for power transmission lines according to claim 5, characterized in that, The specific analysis process of the line risk assessment module is as follows: The line risk assessment coefficient is calculated by weighting and summing the total value of the fault risk, the total fault duration, and the fault risk holding value. If the line risk assessment coefficient exceeds the preset line risk assessment coefficient threshold, the corresponding transmission line is marked as a line with potential risks. Otherwise, the corresponding transmission line will be marked as a low-risk line.

7. The Beidou online monitoring system for power transmission lines according to claim 5, characterized in that, The line risk assessment module and the communication connection area multi-dimensional analysis module mark the number of lines with hidden dangers in the management area as hidden danger detection values. If the hidden danger detection value exceeds the preset hidden danger detection threshold, the management area is marked as a key area. If the detected value of potential hazards does not exceed the preset threshold for potential hazards, the detected value of potential hazards, the line statistics value, and the risk assessment characteristic value are weighted and summed to obtain the comprehensive evaluation value of the line in the area. If the comprehensive evaluation value of a regional route exceeds the preset comprehensive evaluation threshold for regional routes, the management area will be marked as a key area. Otherwise, the managed area will be marked as a non-strict area; and the marking information of the managed area will be sent to the ground monitoring center.

8. The Beidou online monitoring system for power transmission lines according to claim 7, characterized in that, The regional multi-dimensional analysis module is used to conduct management security assessments of the managed area. It obtains the management assessment characteristic values ​​during the monitoring period through assessment and analysis. If the management assessment characteristic value exceeds the corresponding preset management assessment characteristic threshold, a management assessment non-qualified signal is generated; if the management assessment characteristic value does not exceed the corresponding preset management assessment characteristic threshold, a management assessment qualified signal is generated, and the management assessment non-qualified signal or management assessment qualified signal is sent to the ground monitoring center.

9. The Beidou online monitoring system for power transmission lines according to claim 8, characterized in that, The method for obtaining the characteristic values ​​of management evaluation is as follows: The average response time for transmission line faults in the management area during the monitoring period is obtained and marked as the time characteristic value. The number of times the response time for transmission line faults in the management area exceeds the preset response time threshold during the monitoring period is marked as the response anomaly measurement value. The time during which no supervisory personnel are present in the management area during the monitoring period is marked as the unattended time measurement value. The management evaluation characteristic value is obtained by weighted summation of the time characteristic value, the response anomaly measurement value, and the unattended time measurement value.

10. A method for online monitoring of BeiDou transmission lines, characterized in that, Includes the following steps: Step 1: Real-time acquisition of location information for transmission line towers and conductors; Step 2: Collect various environmental data around the transmission line; Step 3: Preprocess and fuse the collected data to generate comprehensive monitoring data; Step 4: Determine if there is a fault in the transmission line; Step 5: Utilize the short message communication function of the BeiDou satellite to transmit the fault diagnosis results and comprehensive monitoring data to the ground monitoring center in real time.

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