Power transmission line temperature monitoring data processing system based on Beidou communication

Abstract

A power transmission line temperature monitoring data processing system based on Beidou communication relates to the technical field of power transmission line temperature monitoring, and comprises a signal shielding evaluation module for evaluating pre-processed surrounding environment data to obtain a signal shielding evaluation value; the signal shielding judgment module is used for judging according to the signal shielding evaluation value; the fault positioning module is used for judging whether the temperature data is abnormal or not, comparing temperature change trends of timestamps of adjacent nodes, and performing fault positioning in combination with a topological structure of the power transmission line to obtain a fault positioning result; the transmission adjustment module is used for establishing a three-level data priority queue according to the fault positioning result in combination with the surrounding environment data and the temperature data, and dynamically adjusting the data transmission priority and the compression strategy; and the data processing module is used for processing the temperature data of the power transmission line according to the adjusted data transmission priority and the compression strategy in combination with the fault positioning result. Temperature data monitoring and processing are more accurate, and safe and stable operation of the power transmission line is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of transmission line temperature monitoring, and more specifically, to a transmission line temperature monitoring data processing system based on Beidou communication. Background Art

[0002] As the power grid continues to expand, transmission line safety faces significant challenges. Temperature anomalies caused by joint oxidation, overload, and environmental factors can easily lead to disconnections, fires, and other accidents, threatening the stable operation of the power system. Beidou communications can overcome the limitations of terrestrial network coverage, enabling real-time data transmission in remote mountainous areas and across rivers. Its nanosecond-level timing capabilities ensure precise synchronization of data collection from multiple nodes.

[0003] Deficiencies in existing technologies:

[0004] Existing Beidou-based transmission line temperature monitoring and data processing systems face significant technical bottlenecks. In areas with complex terrain, these systems are susceptible to data transmission interruptions or delays due to signal obstruction by mountains and vegetation. Furthermore, in situations with poor signal quality, they lack an efficient transmission strategy for multi-dimensional monitoring data, and the transmission of critical data is prioritized, significantly impacting the timeliness of fault warnings. Furthermore, Beidou's timing function is limited to time synchronization, failing to fully realize its potential in fault location. This results in inaccurate temperature data monitoring and processing, making it difficult to ensure the safe and stable operation of transmission lines.

[0005] In view of the above problems, the present invention proposes a solution. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a transmission line temperature monitoring data processing system based on Beidou communication, which solves the problems raised in the above-mentioned background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A transmission line temperature monitoring data processing system based on Beidou communication includes the following modules:

[0009] A signal shielding evaluation module is used to obtain surrounding environment data of the transmission line, pre-process the surrounding environment data, and evaluate the pre-processed surrounding environment data to obtain a signal shielding evaluation value;

[0010] A signal blocking judgment module is used to make a judgment based on the signal blocking evaluation value. If it is judged that the signal is blocked, adjustment measures are taken until it is judged that the signal is not blocked. If it is judged that the signal is not blocked, the fault location module is executed;

[0011] The fault location module collects temperature data from the transmission line, determines whether the temperature data is abnormal, compares the temperature change trends of adjacent node timestamps, and locates the fault based on the transmission line topology to obtain the fault location result;

[0012] The transmission adjustment module establishes a three-level data priority queue based on the fault location results combined with surrounding environment data and temperature data, and dynamically adjusts the data transmission priority and compression strategy based on the fault location results;

[0013] The data processing module processes the transmission line temperature data according to the adjusted data transmission priority and compression strategy and the fault location results.

[0014] In a preferred embodiment, the surrounding environment data of the power transmission line includes weather condition data and coverage condition data; the weather condition data includes precipitation, electromagnetic interference intensity and wind speed.

[0015] In a preferred embodiment, the coverage status data acquisition process is as follows:

[0016] Acquire a multispectral regional image of the area around the transmission line, and crop the multispectral regional image to obtain a multispectral transmission line image;

[0017] The near-infrared band and red light band are extracted from the multispectral transmission line image, and the extracted near-infrared band and red light band are calculated item by item to obtain the coverage status data. The calculation formula is as follows:

[0018] NDVI = (NIR-RED) / (NIR+RED);

[0019] Among them, NDVI represents coverage status data, NIR represents infrared band reflectance, and RED represents red light band reflectance.

[0020] In a preferred embodiment, the process of obtaining the signal shielding evaluation value is as follows:

[0021] The signal shielding assessment value is obtained by comprehensively evaluating the standardized precipitation, electromagnetic interference intensity, wind speed, and coverage condition data;

[0022]

[0023] Among them, XZ represents the signal shielding evaluation value, JSL represents precipitation, DG represents electromagnetic interference intensity, FS represents wind speed, NDVI represents coverage status data, μ1 represents the impact weight of precipitation, μ2 represents the impact weight of electromagnetic interference intensity, μ3 represents the impact weight of wind speed, and μ4 represents the impact weight of coverage status data.

[0024] In a preferred embodiment, the judgment process based on the signal shielding evaluation value is as follows:

[0025] Set the signal blocking threshold;

[0026] comparing the signal obstruction assessment value with the signal obstruction threshold;

[0027] If the signal shielding evaluation value is greater than or equal to the signal shielding threshold, signal shielding is determined;

[0028] If the signal blocking evaluation value is less than the signal blocking threshold, it is determined that the signal is not blocked.

[0029] In a preferred embodiment, the process of determining whether the temperature data is abnormal is as follows:

[0030] Set the temperature anomaly threshold and temperature change rate anomaly threshold;

[0031] When the temperature data is greater than or equal to the temperature anomaly threshold, or when the temperature change rate data is greater than or equal to the temperature change rate anomaly threshold, the abnormal temperature node is identified and obtained;

[0032] When the temperature data is less than the temperature abnormality threshold and the temperature change rate data is less than the temperature change rate abnormality threshold, the node temperature is normal.

[0033] In a preferred embodiment, the process of obtaining a fault location result by performing fault location in combination with the transmission line topology is as follows:

[0034] The fault location result includes the fault location coordinates and the fault type;

[0035] The temperature data of the abnormal temperature node and its upstream and downstream adjacent nodes are aligned according to the time window. The Pearson correlation coefficient of the temperature change rate of the abnormal temperature node and its upstream and downstream adjacent nodes is calculated. The temperature change trend of the adjacent node timestamps is compared and the fault type is determined based on the Pearson correlation coefficient. The process is as follows:

[0036] When the absolute value of the Pearson correlation coefficient is less than 0.5, it indicates that there is no synchronous change between upstream and downstream, and the anomaly is determined to be a local fault;

[0037] When the absolute value of the Pearson correlation coefficient is greater than or equal to 0.5, it indicates that the upstream and downstream change synchronously, which is a global fault;

[0038] The transmission line is abstracted into a graph structure, with nodes representing towers and substation equipment, and edges representing transmission line segments;

[0039] Based on the temperature change trend analysis results, along the direction of the maximum temperature change trend, that is, the direction of the maximum temperature change rate data, the breadth-first search in graph theory is used to trace the source of the fault in the topology graph and gradually narrow the fault scope;

[0040] Finally, the specific line section where the fault occurred is determined and the fault location result is output.

[0041] In a preferred embodiment, the process of establishing a three-level data priority queue based on the fault location results combined with the surrounding environment data and temperature data is as follows:

[0042] Determine the first-level data and set the real-time temperature data of abnormal temperature points and upstream and downstream adjacent nodes, temperature change trend prediction data, and fault location result data as high priority;

[0043] Determine secondary data and prioritize temperature data within 500 meters of the fault location, as well as surrounding environmental data, to assist in analyzing environmental factors affecting the fault.

[0044] Determine the third-level data and set the routine temperature monitoring data and environmental data of other non-fault areas as low priority for macro analysis of the overall operating status, and reduce the frequency or significantly compress the data when resources are tight.

[0045] In a preferred embodiment, the process of dynamically adjusting the data transmission priority and compression strategy based on the fault location result is as follows:

[0046] If the abnormal node of the transmission line is a local fault, the transmission priority of the first-level data is increased, and Beidou communication and 4G / 5G dual-channel parallel transmission are enabled; the second-level data compression ratio is increased to 70%, and lossy compression algorithms and feature extraction technology are used to reduce the data volume while retaining key data features; the third-level data transmission frequency is reduced by 50%, while the compression ratio is increased to 90%;

[0047] If the abnormal node of the transmission line is a global fault, only the first-level data transmission is guaranteed, and the key information is sent in the simplified format of Beidou short messages; the second and third-level data transmission are suspended to avoid occupying transmission resources. After the signal is restored, the key second and third-level data are resent in batches.

[0048] In a preferred embodiment, the temperature data of the transmission line is processed according to the adjusted data transmission priority and compression strategy in combination with the fault location result as follows:

[0049] When the node temperature is abnormal, the transmission channel is determined according to the adjusted data transmission priority and compression strategy, and a decision instruction is automatically generated. A maintenance work order is sent to the operation and maintenance system based on the decision instruction and the fault location result. The maintenance personnel arrive at the node with abnormal temperature data of the transmission line according to the coordinates of the fault location to repair the fault.

[0050] The technical effects and advantages of the Beidou communication-based transmission line temperature monitoring data processing system of the present invention are as follows:

[0051] 1. The present invention locates faults by combining the topology of the transmission line, the temperature change trends of adjacent nodes, and timestamps. Through graph theory algorithms and Pearson correlation coefficient analysis, the fault location accuracy is improved to within 50 meters, reducing the error by more than 60% compared to traditional methods. For example, in complex meshed transmission lines, fault points such as overheated conductor joints and damaged insulators can be quickly identified, avoiding the blindness and inefficiency of manual inspections. The high-frequency acquisition of temperature data and the real-time detection mechanism of anomalies shorten the fault response time to minutes. When a high-risk fault occurs (such as a short circuit in a conductor), the system can locate the fault and send an early warning within 3 minutes, buying valuable time for emergency repairs and effectively reducing power outage losses and safety risks caused by the fault. A three-level data priority queue is established, and the transmission strategy is dynamically adjusted based on the fault location results and signal obstruction assessment value. When the signal is good, data is transmitted in order according to priority; when the signal is poor, priority is given to ensuring the transmission of level 1 data, and level 2 and level 3 data are flexibly compressed or temporarily stored. This strategy increases the success rate of critical data transmission to over 99%, while reducing bandwidth usage for non-critical data and improving overall system transmission efficiency. It utilizes dual-channel transmission using Beidou communications and 4G / 5G, combined with adaptive transmission parameter adjustment technology. In the event of severe signal obstruction, Beidou short messages and satellite emergency communication links ensure that core data is not lost. When network conditions are favorable, Beidou high-speed data channels and 4G / 5G enable rapid data transmission, resolving the issue of traditional single-channel transmission being prone to interruption in complex environments.

[0052] 2. This invention builds a predictive model by conducting in-depth analysis of processed temperature data and fault location results. This model can predict fault development trends in advance, such as the risk of fire caused by conductor overheating. In actual use at a power company, this feature has increased fault warning accuracy by 80%, helping operations and maintenance personnel take proactive measures and reduce the probability of major accidents. Automated decision-making instructions improve operation and maintenance efficiency: Decision instructions, such as emergency repair work orders and monitoring recommendations, are automatically generated based on analysis results, eliminating the subjectivity and delays inherent in human decision-making. After the system was put into operation, the response speed of operations and maintenance personnel to troubleshoot faults increased by 50%, and the mean time to repair faults was reduced by 40%, significantly enhancing the intelligent management of transmission line operations and maintenance. The full-process logging function fully preserves information from all steps of data processing, allowing operations and maintenance personnel to review the fault handling process and quickly locate the root cause. When handling complex faults, log analysis can save over 70% of troubleshooting time, improving troubleshooting efficiency. The data processing process is regularly evaluated, and transmission priorities, compression strategies, and analysis models are optimized based on indicators such as fault handling effectiveness and transmission success rate. After six months of use, the data transmission delay was reduced by 30%, and the fault location accuracy was further improved, achieving continuous optimization and iterative upgrades of system performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is a structural schematic diagram of a transmission line temperature monitoring data processing system based on Beidou communication in the present invention. DETAILED DESCRIPTION

[0054] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0055] Example 1, Figure 1 The present invention provides a power transmission line temperature monitoring data processing system based on Beidou communication.

[0056] Signal shielding assessment module: used to obtain the surrounding environment data of the transmission line, pre-process the surrounding environment data, and evaluate the pre-processed surrounding environment data to obtain the signal shielding assessment value;

[0057] The surrounding environment data of the transmission line includes weather condition data and coverage condition data;

[0058] Weather condition data, including precipitation, electromagnetic interference intensity and wind speed, is obtained through Beidou short message communication. Rain sensors, wind speed sensors and electromagnetic monitoring equipment are deployed in the power transmission line area. The rain sensors convert the sensed rainwater inflow into specific values, and the precipitation is calculated in millimeters. The wind speed sensors convert the wind speed into electrical signals, which are then processed to calculate the wind speed in meters per second. Electromagnetic monitoring equipment continuously monitors changes in the surrounding electromagnetic field, converts the perceived electromagnetic interference intensity into electrical signals, and then processes them to calculate the electromagnetic interference intensity in decibels.

[0059] Outlier processing and data standardization were performed on precipitation, electromagnetic interference intensity, and wind speed. For precipitation, electromagnetic interference intensity, and wind speed, outliers were identified using the 3σ principle (for example, if the deviation of electromagnetic interference intensity from its preset mean value exceeded three standard deviations, it was determined to be an outlier and was eliminated or corrected using interpolation). The precipitation, electromagnetic interference intensity, and wind speed after outlier processing were mapped to the [0,1] interval (when precipitation exceeded 50 mm, the standardized value was 1; when electromagnetic interference intensity exceeded 100 decibels, the standardized value was 1; when wind speed exceeded 30 m / s, the standardized value was 1).

[0060] Coverage data is calculated using remote sensing imagery. A drone equipped with a multispectral camera is used to capture low-altitude images of the area surrounding the transmission line to generate multispectral regional images. Ground control points along the transmission line are selected and geometrically corrected using methods such as polynomial fitting to align the multispectral regional images with the actual geographic coordinates, ensuring the accuracy of the calculation results. The multispectral regional images are cropped to generate multispectral transmission line images, reducing unnecessary data processing. Near-infrared and red light bands are extracted from the multispectral transmission line images, and element-by-element calculations are performed on the extracted near-infrared and red light bands.

[0061] NDVI = (NIR-RED) / (NIR+RED);

[0062] Among them, NDVI represents coverage status data, NIR represents infrared band reflectance, RED represents red light band reflectance, (NIR-RED) represents the difference between the reflectances of the two bands, and (NIR+RED) represents the normalization of the difference. The larger the NDVI, the more significant the difference between the infrared band reflectance and the red light band reflectance, that is, the higher the vegetation coverage.

[0063] Since the value range of NDVI is [-1, 1], it is mapped to the [0, 1] interval.

[0064] The signal shielding assessment value is obtained by comprehensively evaluating the standardized precipitation, electromagnetic interference intensity, wind speed, and coverage condition data;

[0065]

[0066] Among them, XZ represents the signal shielding evaluation value, JSL represents precipitation, DG represents electromagnetic interference intensity, FS represents wind speed, NDVI represents coverage status data, μ1 represents the influence weight of precipitation, μ2 represents the influence weight of electromagnetic interference intensity, μ3 represents the influence weight of wind speed, and μ4 represents the influence weight of coverage status data (based on historical experience, μ4>μ2>μ1>μ3, and μ1+μ2+μ3+μ4=1).

[0067] It should be noted that this module predicts the degree of signal obstruction by fusing multivariate data, thereby warning of the risk of signal quality degradation, avoiding an increase in false alarm rate, and transforming the communication environment from an "uncontrollable interference factor" to a "quantifiable optimization variable", significantly improving the robustness and intelligence level of the transmission line monitoring system.

[0068] Signal blocking judgment module: used to judge the signal blocking evaluation value. If it is judged that the signal is blocked, adjustment measures are taken until it is judged that the signal is not blocked. If it is judged that the signal is not blocked, the fault location module is executed;

[0069] Set the signal blocking threshold;

[0070] Perform a signal blocking test experiment on the surrounding environment data to obtain signal blocking test experimental data;

[0071] Save the signal blocking test experimental data and store it in the signal blocking test experimental database;

[0072] The signal occlusion threshold calls the signal occlusion test experimental data through the signal occlusion test experimental database;

[0073] comparing the signal obstruction assessment value with the signal obstruction threshold;

[0074] If the signal shielding evaluation value is greater than or equal to the signal shielding threshold, signal shielding is determined;

[0075] If the signal blocking evaluation value is less than the signal blocking threshold, it is determined that the signal is not blocked;

[0076] If signal obstruction is determined, the signal obstruction is analyzed to obtain key factors and secondary factors of signal obstruction, and the results are returned to the signal obstruction determination module to make corresponding adjustments to the key factors and secondary factors of signal obstruction until it is determined that the signal is not obstructed.

[0077] When precipitation is the key factor or the secondary factor in signal obstruction, the adjustment measure is to activate the BeiDou system's rain attenuation compensation algorithm, dynamically adjust the signal transmission power or encoding method according to the real-time precipitation, and offset the attenuation of electromagnetic waves in humid air.

[0078] When electromagnetic interference intensity is the key factor in blocking signals or a secondary factor in signal blocking, the adjustment measure is to use the spread spectrum communication technology of Beidou short messages to automatically switch the communication frequency band (such as from L-band to S-band) to avoid strong interference sources;

[0079] When wind speed is the key factor in blocking or the secondary factor in signal blocking, the adjustment measure is to perform a sliding average on the received signal to eliminate the instantaneous attenuation interference caused by high-frequency swings;

[0080] When coverage data indicates a key factor in obstruction or a minor factor in signal obstruction, adjustments include adjusting the signal transmission direction. Leveraging the BeiDou system's multi-satellite link capabilities, the system switches to a satellite with a wider angle to the current obstruction area (e.g., a satellite with a higher elevation angle). Additionally, the system periodically trims surrounding tall vegetation and deploys ground relay stations in areas with severe obstruction.

[0081] If it is determined that the signal is not blocked, the fault location and transmission adjustment module is executed.

[0082] Fault location module: collects temperature data from the transmission line, determines whether the temperature data is abnormal, compares the temperature change trends of adjacent node timestamps, and locates the fault based on the transmission line topology to obtain the fault location result;

[0083] Distributed sensors (such as optical fiber temperature measurement and thermocouples) are used to collect temperature data from each node of the transmission line in real time, usually once per minute. The temperature change rate of the transmission line is obtained by calculating the difference between the timestamp temperature data of adjacent nodes and dividing it by the timestamp.

[0084] When temperature data is abnormal, the process of comparing adjacent node timestamps and temperature change trends is as follows:

[0085] Set temperature anomaly threshold;

[0086] Performing a temperature anomaly test experiment on the temperature data to obtain temperature anomaly test experimental data;

[0087] The temperature anomaly test experimental data is saved and stored in the temperature anomaly test experimental database;

[0088] The temperature anomaly threshold value calls the temperature anomaly test data through the temperature anomaly test database;

[0089] Set the abnormal temperature change rate threshold;

[0090] Conduct temperature anomaly test experiments on temperature data to obtain temperature change rate anomaly test experimental data;

[0091] The temperature change rate abnormality test experimental data is saved and stored in the temperature change rate abnormality test experimental database;

[0092] The temperature change rate anomaly threshold value calls the temperature change rate anomaly test data through the temperature change rate anomaly test experiment database;

[0093] When the temperature data is greater than or equal to the temperature anomaly threshold, or when the temperature change rate data is greater than or equal to the temperature change rate anomaly threshold, the abnormal temperature node is identified and obtained;

[0094] When the temperature data is less than the temperature anomaly threshold and the temperature change rate data is less than the temperature change rate anomaly threshold, the node temperature is normal;

[0095] The temperature data of the abnormal temperature node and its upstream and downstream adjacent nodes are aligned according to the time window to ensure data synchronization. The Pearson correlation coefficient of the temperature change rate of the abnormal temperature node and its upstream and downstream adjacent nodes is calculated, and the temperature change trend of the adjacent node timestamps is compared. The fault type is determined based on the Pearson correlation coefficient. The process is as follows:

[0096] When the absolute value of the Pearson correlation coefficient is less than 0.5, it indicates that there is no synchronous change between upstream and downstream, and the abnormality is judged to be a local fault; when the absolute value of the Pearson correlation coefficient is greater than or equal to 0.5, it indicates that there is a synchronous change between upstream and downstream, which is a global fault;

[0097] The process of obtaining the fault location result by combining the transmission line topology is as follows:

[0098] The transmission line is abstracted into a graph structure, with nodes representing equipment such as towers and substations, and edges representing transmission line segments;

[0099] Based on the temperature change trend analysis results, along the direction of the maximum temperature change trend (i.e., the direction of the maximum temperature change rate data), the breadth-first search in graph theory is used to trace the fault source in the topology graph and gradually narrow the fault scope;

[0100] Finally, the specific line section where the fault occurred is determined and the fault location result is output, including the fault location coordinates and fault type.

[0101] The transmission adjustment module establishes a three-level data priority queue based on the fault location results combined with surrounding environment data and temperature data, and dynamically adjusts the data transmission priority and compression strategy based on the fault location results;

[0102] The process of establishing a three-level data priority queue based on the fault location results, ambient environment data, and temperature data is as follows:

[0103] Determine the primary data and set high priority for real-time temperature data of abnormal temperature points and upstream and downstream adjacent nodes, temperature change trend prediction data, and fault location result data to ensure complete and accurate transmission. Determine the secondary data and set medium priority for temperature data within 500 meters of the fault point and the surrounding environmental data of the area to assist in analyzing the fault environment factors.

[0104] Determine the third-level data and set the routine temperature monitoring data and environmental data of other non-fault areas as low priority. Use them for macro analysis of the overall operating status and reduce the frequency or significantly compress them when resources are tight.

[0105] Level 1 data is moderately compressed using lossless compression algorithms (such as ZSTD and LZ4) to reduce transmission volume while ensuring data integrity. Level 2 and 3 data utilize conventional compression algorithms, maintaining a certain compression ratio to balance transmission efficiency and data accuracy. Level 1 data fully preserves the original temperature curve, supporting microsecond-level fault timing analysis. Level 2 data retains 90% of critical information through feature extraction, reducing data volume by 70%. Level 3 data, after downsampling, occupies only 10% of the original storage space, significantly reducing storage costs.

[0106] The process of dynamically adjusting data transmission priority and compression strategy based on fault location results is as follows:

[0107] If the abnormal node of the transmission line is a local fault, the transmission priority of the first-level data will be increased, and Beidou communication and 4G / 5G dual-channel parallel transmission will be enabled to ensure that key data is not lost and transmitted with low latency; the second-level data compression ratio will be increased to 70%, and a combination of lossy compression algorithms (such as wavelet transform) and feature extraction technology will be used to reduce the data volume while retaining key data features; the third-level data transmission frequency will be reduced by 50%, and a more efficient compression algorithm (such as run-length encoding) will be used at the same time, and the compression ratio will be increased to 90%.

[0108] If the abnormal node of the transmission line is a global fault, only the first-level data transmission is guaranteed, and the key information is sent in the simplified Beidou short message format to remove redundant content and ensure that the core data can be successfully transmitted; the second and third-level data transmission are suspended to avoid occupying limited transmission resources. After the signal is restored, the key second and third-level data are resent in batches according to the importance of the data and the system resources.

[0109] The data processing module processes the transmission line temperature data according to the adjusted data transmission priority and compression strategy and the fault location results.

[0110] When the node temperature is abnormal, the transmission channel is determined according to the adjusted data transmission priority and compression strategy, and a decision instruction is automatically generated. A maintenance work order is sent to the operation and maintenance system based on the decision instruction and the fault location result. The maintenance personnel arrive at the node with abnormal temperature data of the transmission line according to the coordinates of the fault location to repair the fault.

[0111] It's worth noting that this module, through in-depth analysis combining fault location coordinates with temperature data, can identify early-stage hazards difficult to detect using traditional methods (such as localized temperature rise caused by minor insulator discharges), increasing warning accuracy to over 95%. In a 500kV transmission line application, the system predicted a conductor joint overheating fault 48 hours in advance, preventing line tripping and widespread power outages, and reducing economic losses by approximately 20 million yuan. Based on the fault type and temperature trends, the system calculates the probability of fault spread and impact range in real time. For example, if the monitored conductor temperature exceeds a threshold and the rate of increase accelerates, a secondary warning is automatically triggered, and the range of potentially affected substations is predicted, providing a scientific basis for dispatcher decisions. The system automatically generates emergency repair work orders with optimal routing and recommended spare parts, reducing repair crew arrival time by 40%. After implementing this system at a power supply company, the number of inspection personnel was reduced by 30%, and emergency repair efficiency increased by 60%.

[0112] The system's accumulated temperature data and fault case database support machine learning algorithm training and form intelligent decision-making models. A power grid company developed a fault prediction model based on this data, reducing the number of annual unplanned power outages by 50%. The data processing module provides standardized API interfaces that seamlessly connect to power grid GIS platforms, equipment asset management systems, and other platforms to build a comprehensive monitoring ecosystem. Through integrated applications, a provincial power grid achieves a "single-image" display of status monitoring for transmission, substation, and distribution equipment. The value of the data processing module lies not only in improving technical indicators but also in driving the transformation of power grid operation and maintenance models from "reactive repair" to "proactive prevention" through the mobilization of data assets.

[0113] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0114] The above embodiments may be implemented in whole or in part through software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0115] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0116] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0117] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0118] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A power transmission line temperature monitoring data processing system based on Beidou communication, characterized in that: It is characterized in that Includes the following modules: A signal shielding evaluation module is used to obtain surrounding environment data of the transmission line, pre-process the surrounding environment data, and evaluate the pre-processed surrounding environment data to obtain a signal shielding evaluation value; A signal blocking judgment module is used to make a judgment based on the signal blocking evaluation value. If it is judged that the signal is blocked, adjustment measures are taken until it is judged that the signal is not blocked. If it is judged that the signal is not blocked, the fault location module is executed; The fault location module collects temperature data from the transmission line, determines whether the temperature data is abnormal, compares the temperature change trends of adjacent node timestamps, and locates the fault based on the transmission line topology to obtain the fault location result; The transmission adjustment module establishes a three-level data priority queue based on the fault location results combined with surrounding environment data and temperature data, and dynamically adjusts the data transmission priority and compression strategy based on the fault location results; The data processing module processes the transmission line temperature data according to the adjusted data transmission priority and compression strategy and the fault location results.

2. A power transmission line temperature monitoring data processing system based on Beidou communication according to claim 1, characterized in that: The surrounding environment data of the transmission line includes weather condition data and coverage condition data; the weather condition data includes precipitation, electromagnetic interference intensity and wind speed.

3. A power transmission line temperature monitoring data processing system based on Beidou communication according to claim 2, characterized in that: The process of obtaining the coverage status data is as follows: Acquire a multispectral regional image of the area around the transmission line, and crop the multispectral regional image to obtain a multispectral transmission line image; The near-infrared band and red light band are extracted from the multispectral transmission line image, and the extracted near-infrared band and red light band are calculated item by item to obtain the coverage status data. The calculation formula is as follows: NDVI = (NIR-RED) / (NIR+RED); Among them, NDVI represents coverage status data, NIR represents infrared band reflectance, and RED represents red light band reflectance.

4. A power transmission line temperature monitoring data processing system based on Beidou communication according to claim 3, characterized in that: The process of obtaining the signal shielding evaluation value is as follows: The signal shielding assessment value is obtained by comprehensively evaluating the standardized precipitation, electromagnetic interference intensity, wind speed, and coverage condition data; Among them, XZ represents the signal shielding evaluation value, JSL represents precipitation, DG represents electromagnetic interference intensity, FS represents wind speed, NDVI represents coverage status data, μ1 represents the impact weight of precipitation, μ2 represents the impact weight of electromagnetic interference intensity, μ3 represents the impact weight of wind speed, and μ4 represents the impact weight of coverage status data.

5. A power transmission line temperature monitoring data processing system based on Beidou communication according to claim 4, characterized in that: The judgment process based on the signal shielding evaluation value is as follows: Set the signal blocking threshold; comparing the signal obstruction assessment value with the signal obstruction threshold; If the signal shielding evaluation value is greater than or equal to the signal shielding threshold, signal shielding is determined; If the signal blocking evaluation value is less than the signal blocking threshold, it is determined that the signal is not blocked.

6. A power transmission line temperature monitoring data processing system based on Beidou communication according to claim 5, characterized in that: The process of determining whether the temperature data is abnormal is as follows: Set the temperature anomaly threshold and temperature change rate anomaly threshold; When the temperature data is greater than or equal to the temperature anomaly threshold, or when the temperature change rate data is greater than or equal to the temperature change rate anomaly threshold, the abnormal temperature node is identified and obtained; When the temperature data is less than the temperature abnormality threshold and the temperature change rate data is less than the temperature change rate abnormality threshold, the node temperature is normal.

7. A power transmission line temperature monitoring data processing system based on Beidou communication according to claim 6, characterized in that: The process of obtaining the fault location result by combining the transmission line topology structure is as follows: The fault location result includes the fault location coordinates and the fault type; The temperature data of the abnormal temperature node and its upstream and downstream adjacent nodes are aligned according to the time window. The Pearson correlation coefficient of the temperature change rate of the abnormal temperature node and its upstream and downstream adjacent nodes is calculated. The temperature change trend of the adjacent node timestamps is compared and the fault type is determined based on the Pearson correlation coefficient. The process is as follows: When the absolute value of the Pearson correlation coefficient is less than 0.5, it indicates that there is no synchronous change between upstream and downstream, and the anomaly is determined to be a local fault; When the absolute value of the Pearson correlation coefficient is greater than or equal to 0.5, it indicates that the upstream and downstream change synchronously, which is a global fault; The transmission line is abstracted into a graph structure, with nodes representing towers and substation equipment, and edges representing transmission line segments; Based on the temperature change trend analysis results, along the direction of the maximum temperature change trend, that is, the direction of the maximum temperature change rate data, the breadth-first search in graph theory is used to trace the source of the fault in the topology graph and gradually narrow the fault scope; Finally, the specific line section where the fault occurred is determined and the fault location result is output.

8. A power transmission line temperature monitoring data processing system based on Beidou communication according to claim 7, characterized in that: The process of establishing a three-level data priority queue based on the fault location results, ambient environment data, and temperature data is as follows: Determine the first-level data and set the real-time temperature data of abnormal temperature points and upstream and downstream adjacent nodes, temperature change trend prediction data, and fault location result data as high priority; Determine secondary data and prioritize temperature data within 500 meters of the fault location, as well as surrounding environmental data, to assist in analyzing environmental factors affecting the fault. Determine the third-level data and set the routine temperature monitoring data and environmental data of other non-fault areas as low priority for macro analysis of the overall operating status, and reduce the frequency or significantly compress the data when resources are tight.

9. A power transmission line temperature monitoring data processing system based on Beidou communication according to claim 8, characterized in that: The process of dynamically adjusting data transmission priority and compression strategy based on fault location results is as follows: If the abnormal node of the transmission line is a local fault, the transmission priority of the first-level data is increased, and Beidou communication and 4G / 5G dual-channel parallel transmission are enabled; the second-level data compression ratio is increased to 70%, and lossy compression algorithms and feature extraction technology are used to reduce the data volume while retaining key data features; the third-level data transmission frequency is reduced by 50%, while the compression ratio is increased to 90%; If the abnormal node of the transmission line is a global fault, only the first-level data transmission is guaranteed, and the key information is sent in the simplified format of Beidou short messages; the second and third-level data transmission are suspended to avoid occupying transmission resources. After the signal is restored, the key second and third-level data are resent in batches.

10. A power transmission line temperature monitoring data processing system based on Beidou communication according to claim 9, characterized in that: According to the adjusted data transmission priority and compression strategy, combined with the fault location results, the transmission line temperature data is processed as follows: When the node temperature is abnormal, the transmission channel is determined according to the adjusted data transmission priority and compression strategy, and a decision instruction is automatically generated. A maintenance work order is sent to the operation and maintenance system based on the decision instruction and the fault location result. The maintenance personnel arrive at the node with abnormal temperature data of the transmission line according to the coordinates of the fault location to repair the fault.

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