A power transmission line operation and maintenance monitoring system

Abstract

The application provides a power transmission line operation and maintenance monitoring system, comprising a data acquisition layer, a data processing layer and a background management layer; wherein the data acquisition layer is used for collecting power transmission line state data in real time through a sensor acquisition module and a mobile acquisition module, and transmitting the acquired power transmission line state data to the data processing layer through a wireless communication base station; the data processing layer is used for analyzing and processing the acquired power transmission line state data, and extracting power transmission line monitoring feature information; the background management layer is used for integrating the power transmission line monitoring feature information into a preset display model, displaying the power transmission line monitoring feature information, and generating a corresponding operation and maintenance scheduling instruction when the power transmission line monitoring feature information is abnormal. The application realizes unmanned, intelligent and real-time operation and maintenance monitoring of the power transmission line, and helps to improve the reliability and intelligent level of the power transmission line operation and maintenance management.

Description

Technical Field

[0001] This invention relates to the field of transmission line operation and maintenance monitoring technology, and in particular to a transmission line operation and maintenance monitoring system. Background Technology

[0002] Transmission lines, as the physical transmission medium of electricity, are a fundamental component of the power grid. Their safety, reliability, and stability are crucial for ensuring the stable operation of the power system. Currently, most transmission lines are constructed in the field, characterized by long distances and complex geographical areas. In existing technology, the operation and maintenance monitoring of transmission lines largely relies on manual labor. This involves maintenance personnel conducting regular inspections and recording maintenance data for the transmission lines within their assigned areas, noting any abnormal data during inspections, and then submitting the data to the management department for unified repair of any anomalies after the inspections are completed.

[0003] However, traditional manual methods of power transmission line operation and maintenance monitoring require significant manpower and resources, and the feedback of transmission line information is often delayed, failing to meet the development needs of modern power systems. Therefore, developing an operation and maintenance monitoring system capable of real-time monitoring of transmission line status is imperative. Summary of the Invention

[0004] To address the aforementioned problems, this invention aims to provide a power transmission line operation and maintenance monitoring system.

[0005] The objective of this invention is achieved through the following technical solution:

[0006] This invention proposes a power transmission line operation and maintenance monitoring system, comprising a data acquisition layer, a data processing layer, and a back-end management layer; wherein,

[0007] The data acquisition layer includes a sensor acquisition module fixedly installed on the transmission line and a mobile acquisition module for inspection along the transmission line; the data acquisition layer is used to acquire transmission line status data in real time through the sensor acquisition module and the mobile acquisition module, and transmit the acquired transmission line status data to the data processing layer through a wireless communication base station.

[0008] The data processing layer is used to analyze and process the acquired power transmission line status data and extract power transmission line monitoring feature information;

[0009] The back-end management layer is used to integrate the transmission line monitoring feature information into the preset display model, display the transmission line monitoring feature information, and generate corresponding operation and maintenance scheduling instructions when the transmission line monitoring feature information is abnormal.

[0010] Preferably, the sensor acquisition module includes temperature sensors, humidity sensors, wind speed and direction sensors, tension sensors, etc., installed on the power transmission line; the power transmission line status data are collected by each type of sensor, including temperature data, humidity data, wind speed and direction data, tension data, etc.

[0011] Preferably, the mobile data acquisition module includes an inspection unit and an inspection data acquisition unit, wherein...

[0012] The inspection unit is mounted on a handheld terminal or drone terminal and is used to complete inspection tasks according to a preset inspection route.

[0013] The inspection and data acquisition unit is used to collect inspection and monitoring data in real time during the inspection task, including power transmission line image data.

[0014] Preferably, in the data acquisition layer, the sensor acquisition module and the mobile acquisition module transmit the acquired power line status data to the data processing layer via a wireless communication base station, specifically including:

[0015] A wireless IoT communication network is established between the sensor acquisition module and the mobile acquisition module. The sensor acquisition module acts as a sensor acquisition node in the wireless IoT communication network, and the mobile acquisition module acts as a mobile acquisition node in the wireless IoT communication network. The sensor acquisition module and the mobile acquisition module transmit the acquired power line status data to the wireless communication base station through single-hop or multi-hop transmission. The wireless communication base station further packages the aggregated power line status data and transmits it to the data processing layer.

[0016] Preferably, the data processing layer includes a preprocessing module, an analysis module, and a feature extraction module;

[0017] The preprocessing module is used to preprocess the acquired transmission line status data packets, including data cleaning, standardization and other preprocessing, to obtain preprocessed transmission line status data;

[0018] The analysis module is used to perform standard analysis based on the acquired single transmission line status data, or to perform joint analysis based on multiple transmission line status data, to obtain the transmission line operation and maintenance status analysis results;

[0019] The feature extraction module is used to extract operation and maintenance features based on the power transmission line status data and the analysis results of power transmission line operation and maintenance status over a period of time, so as to obtain power transmission line monitoring feature information; among which the power transmission line monitoring feature information includes status features and change features, etc.

[0020] Preferably, the analysis module includes standard analysis units and joint analysis units;

[0021] The standard analysis unit is used to compare and analyze the acquired single transmission line status data with the corresponding status standards. When the value of the transmission line status data is within the range of the corresponding status standards, the standard analysis result of the indicator is normal; otherwise, when the value of the transmission line status data exceeds the range of the corresponding status standards, the standard analysis result of the indicator is abnormal.

[0022] The joint analysis unit is used to form a feature dataset based on the acquired individual transmission line status data according to the preset grouping criteria, and input the feature dataset into the trained joint analysis model for joint analysis to obtain the transmission line operation and maintenance status analysis results.

[0023] Preferably, the analysis module further includes an image analysis unit;

[0024] The image analysis unit is used to perform image analysis processing on the power transmission line image data acquired by the mobile acquisition module to obtain the power transmission line image analysis results.

[0025] Preferably, the back-end management layer includes a visualization module and an operation and maintenance management module;

[0026] The visualization module is used to integrate the monitoring feature information of the power transmission line into the display model through the preset display model, and to display the monitoring results of the power transmission line status; the display model includes a digital twin model of the power transmission line, a two-dimensional GIS power transmission line map model, and a three-dimensional GIS power transmission line map model;

[0027] The operation and maintenance management module is used to monitor the characteristic information of the transmission line. When the characteristic information of the transmission line monitoring is abnormal, the module generates corresponding operation and maintenance scheduling instructions based on the abnormal results. The operation and maintenance scheduling instructions include the location information corresponding to the abnormal results and the abnormal transmission line monitoring characteristic information.

[0028] Preferably, the visualization module also includes a model building unit;

[0029] The model building unit is used to build a corresponding display model based on the actual construction of the transmission line, and set corresponding data nodes in the display model. The data nodes are then matched with the transmission line status data obtained by the data acquisition layer, so that the transmission line status data obtained by the data acquisition layer or the transmission line monitoring feature information obtained by analyzing the transmission line status data can be integrated into the corresponding data nodes for display.

[0030] The beneficial effects of this invention are as follows: By setting up a distributed architecture transmission line operation and maintenance monitoring system, real-time data acquisition of transmission lines can be achieved. Simultaneously, based on the cooperation of sensor acquisition modules and mobile acquisition modules, multi-dimensional monitoring data acquisition of transmission lines can be completed. Furthermore, the data processing layer comprehensively analyzes and processes the obtained transmission line status data to obtain transmission line monitoring characteristic information, which is then visualized by the back-end management layer. When an anomaly occurs, corresponding scheduling instructions can be intelligently generated, realizing unmanned, intelligent, and real-time operation and maintenance monitoring of transmission lines, thus helping to improve the reliability and intelligence level of transmission line operation and maintenance management. Attached Figure Description

[0031] The present invention will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present invention. For those skilled in the art, other drawings can be obtained based on the following drawings without creative effort.

[0032] Figure 1 This is a schematic diagram of a power transmission line operation and maintenance monitoring system according to an embodiment of the present invention. Detailed Implementation

[0033] The present invention will be further described in conjunction with the following application scenarios.

[0034] See Figure 1 The embodiment illustrates a power transmission line operation and maintenance monitoring system, comprising a data acquisition layer, a data processing layer, and a back-end management layer; wherein,

[0035] The data acquisition layer includes a sensor acquisition module fixedly installed on the transmission line and a mobile acquisition module for inspection along the transmission line; the data acquisition layer is used to acquire transmission line status data in real time through the sensor acquisition module and the mobile acquisition module, and transmit the acquired transmission line status data to the data processing layer through a wireless communication base station.

[0036] The data processing layer is used to analyze and process the acquired power transmission line status data and extract power transmission line monitoring feature information;

[0037] The back-end management layer is used to integrate the transmission line monitoring feature information into the preset display model, display the transmission line monitoring feature information, and generate corresponding operation and maintenance scheduling instructions when the transmission line monitoring feature information is abnormal.

[0038] The above-described embodiments of the present invention, through the establishment of a distributed architecture transmission line operation and maintenance monitoring system, can achieve real-time data acquisition of transmission lines. Furthermore, based on the cooperation of sensor acquisition modules and mobile acquisition modules, it can complete the acquisition of multi-dimensional monitoring data of transmission lines. Simultaneously, the data processing layer comprehensively analyzes and processes the obtained transmission line status data to obtain transmission line monitoring characteristic information, which is then visualized by the back-end management layer. When an anomaly occurs, it can intelligently generate corresponding scheduling instructions, realizing unmanned, intelligent, and real-time operation and maintenance monitoring of transmission lines, thus helping to improve the reliability and intelligence level of transmission line operation and maintenance management.

[0039] This system is a power transmission line operation and maintenance monitoring system that integrates data acquisition, processing, analysis, and display. By monitoring the status of power transmission lines in real time and analyzing the data using appropriate algorithms and visualization tools, it helps to promptly detect anomalies and carry out maintenance.

[0040] Preferably, the sensor acquisition module includes temperature sensors, humidity sensors, wind speed and direction sensors, tension sensors, etc., installed on the power transmission line; the power transmission line status data are collected by each type of sensor, including temperature data, humidity data, wind speed and direction data, tension data, etc.

[0041] Based on the characteristics of the transmission line and its operating environment, appropriate sensors should be selected. For example, digital temperature sensors can be chosen for temperature monitoring; anemometers can be selected for wind speed and direction monitoring; and tension gauges can be selected for tension monitoring. Through a reasonable configuration of sensor acquisition modules, real-time and uninterrupted acquisition of transmission line monitoring data can be achieved, improving the reliability of transmission line monitoring data acquisition.

[0042] Preferably, the mobile data acquisition module includes an inspection unit and an inspection data acquisition unit, wherein...

[0043] The inspection unit is mounted on a handheld terminal or drone terminal and is used to complete inspection tasks according to a preset inspection route.

[0044] The inspection and data acquisition unit is used to collect inspection and monitoring data in real time during the inspection task, including power transmission line image data.

[0045] The system is also equipped with an inspection and data acquisition module based on drones or handheld acquisition terminals. This module periodically acquires image data of the power transmission lines, enabling both routine and targeted image data acquisition. Based on the image data, the system provides an intuitive display of the actual condition of the power transmission lines and conducts operation and maintenance monitoring, thereby improving the effectiveness of power transmission line operation and maintenance monitoring.

[0046] Preferably, in the data acquisition layer, the sensor acquisition module and the mobile acquisition module transmit the acquired power line status data to the data processing layer via a wireless communication base station, specifically including:

[0047] A wireless IoT communication network is established between the sensor acquisition module and the mobile acquisition module. The sensor acquisition module acts as a sensor acquisition node in the wireless IoT communication network, and the mobile acquisition module acts as a mobile acquisition node in the wireless IoT communication network. The sensor acquisition module and the mobile acquisition module transmit the acquired power line status data to the wireless communication base station through single-hop or multi-hop transmission. The wireless communication base station further packages the aggregated power line status data and transmits it to the data processing layer.

[0048] This invention also proposes a data transmission method based on the cooperation of a sensor acquisition module, a mobile acquisition module, and a wireless communication base station. Considering the energy characteristics of the sensor acquisition module (wireless sensors are typically configured with independent power sources, thus their data acquisition and transmission tasks are affected when their energy is depleted; even if the wireless sensor can automatically replenish its energy (e.g., through solar energy, backup battery replacement, etc.), its data acquisition and transmission performance is still negatively impacted when it is low on energy (performance decreases by 20-40% compared to when energy is sufficient), which can easily lead to insufficient reliability of data transmission in the traditional data transmission method for power line status data transmission at the data acquisition layer due to the performance of the sensor acquisition module). Therefore, this invention also specifically proposes a data transmission method in which the acquisition modules cooperate to build a wireless IoT communication network, which can optimize energy during data transmission at the data acquisition layer, improve the reliability of data transmission at the data acquisition layer, and enhance its adaptability to large-scale power line operation and maintenance monitoring.

[0049] Preferably, the sensor acquisition module transmits the acquired power line status data to the mobile acquisition module via single-hop or multi-hop transmission, specifically including:

[0050] Each sensor data acquisition node periodically calculates its own current performance characteristic factor; the performance characteristic factor calculation function used is:

[0051] PFMC t (i)=α1×{Ve1[PowC t (i), PowZ]+Ve2[PowC t (i)-PowC t-1 (i), PowS]}+α2×Ve3[SenC t (i), SenZ]+Ran

[0052] Among them, PFMCt (i) represents the performance characteristic factor of sensor acquisition node i at time t, where i = 1, 2, ..., N, and N represents the total number of sensor acquisition nodes; PowC t (i) represents the percentage of remaining energy at sensor node i at time t; PowC t-1 (i) represents the remaining energy percentage value of sensor node i at time t-1; PowZ represents the preset remaining energy percentage comparison value, and PowS represents the preset energy consumption percentage standard value; SenC t (i) represents the data transmission rate of sensor node i at time t; SenZ represents the preset standard rate value; where, Ve1[PowC t (i), PowZ] denotes the first judgment function, where when PowC t When (i)≥PowZ, Ve1[PowC] t (i), PowZ]=1, otherwise Ve1[PowC t (i), PowZ]=-1;Ve2[PowC t (i)-PowC t-1 (i), PowS] denotes the second judgment function, where when PowC t (i)-PowC t-1 When (i)>0, Ve2[PowC t (i)-PowC t-1 (i), PowS]=1; 0>PowC t (i)-PowC t-1 When (i) > PowS, Ve2[PowC t (i)-PowC t-1 (i), PowS] = 0; otherwise Ve2[PowC t (i)-PowC t-1 (i), PowS] = -1; Ve3[SenC t (i), SenZ] denotes the third judgment function, where SenC t When (i) > SenZ, Ve3(SenC) t (i), SenZ] = 0, otherwise Ve3[SenC t (i), SenZ]=-1; α1 and α2 represent preset weighting factors; Ran represents a random number between 0.01 and 0.1;

[0053] Each sensor acquisition node will display its own Performance Characteristic Factor (PFMC). t (i) Compare with the preset performance characteristic standard value PFMZ, when PFMC t(i) When <PFMZ, the sensor acquisition node marks its current node type as a node of interest; otherwise, it marks its current node type as a general node. Each sensor acquisition node broadcasts its current node type and performance characteristic factor to other neighboring nodes within its direct communication range.

[0054] The node of interest selects the general node with the largest performance characteristic factor as its next-hop node based on the node type and performance characteristic factor broadcast by other sensor acquisition nodes. The node then transmits the power line status data it has collected to the next-hop node, which in turn transmits the aggregated power line status data to the wireless communication base station.

[0055] The mobile acquisition node is equipped with a displacement monitoring unit, which can acquire the real-time displacement velocity Vel of the mobile acquisition node. t (j), where Vel t (j) represents the real-time displacement velocity of the moving acquisition node j at time t;

[0056] During the inspection process, the mobile data acquisition node detects its own real-time displacement velocity Vel. t (j), when the real-time displacement velocity Vel t (j) Vel Z is less than the preset speed standard value Vel t (j) < VelZ; The mobile acquisition node calculates its own intermediate feature factors, where the intermediate feature factor calculation function is:

[0057] MIDC t (j)=Ve4[PowC t (j), PowZ y ]+Ve5[SenC t (j), SenZ y ]

[0058] Among them, MIDC t (j) represents the intermediate feature factor of the moving acquisition node j at time t; PowC t (j) represents the remaining percentage of energy at time t for the moving acquisition node j, PowZ y This indicates a preset percentage comparison value for remaining energy; SenC t (j) represents the data transmission rate of the moving acquisition node j at time t; SenZ y Indicates the preset standard rate value; Ve4[PowC t (j), PowZ y ] represents the fourth judgment function, where when PowC t (j)>PowZ y At that time, Ve4[PowC t(j), PowZ y ] = 1, otherwise Ve4[PowC t (j), PowZ y ] = 0; Ve5[SenC t (j), SenZ y ] represents the fifth judgment function, where SenC t (j)>SenZ y At that time, Ve5[SenC t (j), SenZ y ] = 1, otherwise Ve5[SenC t (j), SenZ y ] = 0;

[0059] When the current intermediate characteristic factor MIDC is calculated t When (j) = 2; the mobile acquisition node periodically broadcasts mobile node information to the sensor acquisition nodes within its direct communication range, wherein the mobile node information carries the real-time intermediate feature factor of the mobile acquisition node and connection establishment invitation information.

[0060] The sensor acquisition node makes a judgment based on the received mobile node information, among which the node of interest will select the performance characteristic factor (PFMC) of the next-hop node with which it has established a connection. t (k) and the real-time intermediate feature factor MIDC of the mobile acquisition node t (j) compares when PFMC t (k) < MIDC t (j) When the node of interest establishes a communication connection with the mobile data collection node based on the connection establishment invitation information in the mobile node information, the mobile data collection node is used as its next-hop node, and the data of the power line status collected by the node of interest is transmitted to the next-hop node. The next-hop node then transmits the aggregated power line status data to the wireless communication base station.

[0061] Optionally, upon receiving information from a mobile node, a general node may directly reject the connection invitation sent by the mobile acquisition node, or it may compare its own performance characteristic factors with intermediate characteristic factors, establish a communication connection with the mobile acquisition node based on the comparison result, and use the mobile acquisition node as its next-hop node.

[0062] In one scenario, the performance parameters of a sensor acquisition node can be the parameters of the sensor at time t; or the average parameter value over a period of time with time t as the standard can be used as the corresponding performance parameter at time t.

[0063] Optionally, set α1 = α2 = 1; PowZ = 50%; PowS = 10%; SenZ = 10kb / s; PFMZ = 0;

[0064] PowZ y =40%; SenZ y =1000kb / s;

[0065] Ran is much smaller than α1+α2, so that the value of Ran will not cause a classification result.

[0066] In one scenario, in the above implementation, when a general node transmits the power line status data it collects or aggregates to a wireless communication base station, it can use either direct transmission or indirect transmission via cluster heads. Direct transmission involves the general node transmitting data to the wireless communication base station through the wireless communication network. Indirect transmission involves selecting a cluster head node from the current general nodes, having the cluster head node aggregate the data from other general nodes, and then transmitting the data to the wireless communication base station. The selection of the cluster head node can be based on any existing publicly available cluster head node selection method, and this invention does not impose specific limitations on this method.

[0067] The displacement monitoring unit can acquire the horizontal displacement of the mobile acquisition node within a certain period of time and obtain the corresponding real-time displacement velocity based on the displacement. The displacement monitoring unit can use a displacement monitoring sensor that can achieve the above functions in the prior art, and this application does not make specific limitations.

[0068] In traditional sensor communication networks, the energy characteristics of sensor nodes can lead to excessive energy consumption in some sensor acquisition modules, affecting their transmission performance and thus impacting the reliability of power transmission line status data acquisition and transmission. This invention proposes a data transmission method combining sensor acquisition modules and mobile acquisition modules. Firstly, a performance characteristic factor is proposed to obtain the real-time performance characteristics of sensor acquisition nodes. This factor specifically considers the energy characteristics of the sensor as a crucial parameter, combined with the sensor's data transmission performance as an auxiliary factor, to comprehensively evaluate the performance of the sensor acquisition nodes. Furthermore, considering poorly performing sensor acquisition nodes as nodes of interest, the data transmission path of these nodes is adaptively adjusted. Through multi-hop transmission, superior nodes within their neighborhood are used as next-hop nodes to assist in data transmission. This effectively optimizes the performance of nodes of interest (reducing data transmission distance and performance, and improving data transmission reliability), thereby improving the reliability of power transmission line status data transmission acquired by these nodes and the entire data acquisition layer. Considering that mobile acquisition nodes generally outperform fixed sensor acquisition nodes during inspection tasks, mobile acquisition nodes are further configured as auxiliary transmission nodes to assist sensor acquisition nodes in data transmission. When mobile acquisition nodes are performing low-speed inspections (to avoid invalid connections and adverse effects), they calculate their intermediate feature factors and broadcast them to other sensor acquisition nodes in the neighborhood. This allows sensor acquisition nodes, especially those of interest, to compare their intermediate feature factors with the performance feature factors of the current next-hop node, and select the more efficient mobile acquisition node to assist in data transmission. (When the performance of the next-hop node of the interest node is not high, indirect transmission may increase the load on the original next-hop sensor acquisition node, accelerating its performance consumption.) This further improves the performance optimization and reliability of the interest node in data transmission. Furthermore, using mobile acquisition nodes as temporary next-hop nodes for transmission assistance helps to compare the data obtained by the interest node during this period with data obtained in other time periods, thus promptly detecting sensor acquisition node "dead" situations and improving the overall performance and reliability of sensor acquisition module data transmission.

[0069] Preferably, the data processing layer includes a preprocessing module, an analysis module, and a feature extraction module;

[0070] The preprocessing module is used to preprocess the acquired transmission line status data packets, including data cleaning, standardization and other preprocessing, to obtain preprocessed transmission line status data;

[0071] The analysis module is used to perform standard analysis based on the acquired single transmission line status data, or to perform joint analysis based on multiple transmission line status data, to obtain the transmission line operation and maintenance status analysis results;

[0072] The feature extraction module is used to extract operation and maintenance features based on the power transmission line status data and the analysis results of power transmission line operation and maintenance status over a period of time, so as to obtain power transmission line monitoring feature information; among which the power transmission line monitoring feature information includes status features and change features, etc.

[0073] The data processing layer, as the core of the entire system, uses machine learning algorithms to process and analyze the collected data, such as regression, classification, and clustering. These algorithms can effectively extract useful information from the data, providing a basis for prediction and maintenance. Specifically, before data processing, the obtained transmission line status data undergoes preprocessing to improve data quality and lay the foundation for further data analysis and processing.

[0074] Preferably, the analysis module includes standard analysis units and joint analysis units;

[0075] The standard analysis unit is used to compare and analyze the acquired single transmission line status data with the corresponding status standards. When the value of the transmission line status data is within the range of the corresponding status standards, the standard analysis result of the indicator is normal; otherwise, when the value of the transmission line status data exceeds the range of the corresponding status standards, the standard analysis result of the indicator is abnormal.

[0076] The joint analysis unit is used to form a feature dataset based on the acquired individual transmission line status data according to the preset grouping criteria, and input the feature dataset into the trained joint analysis model for joint analysis to obtain the transmission line operation and maintenance status analysis results.

[0077] Based on the actual operation and maintenance monitoring situation and needs of transmission lines, the system can accurately analyze the status of transmission lines through single-indicator comparative analysis or multi-indicator joint analysis, adapting to the needs of transmission line operation and maintenance monitoring in different scenarios, while improving the intelligence level of transmission line status data analysis.

[0078] In one scenario, the joint analysis unit can employ a deep learning-based clustering analysis model or a state analysis model built on a neural network. The aforementioned joint analysis model can be a pre-trained data analysis model from the prior art, and this invention does not impose any specific limitations on it.

[0079] Preferably, the analysis module further includes an image analysis unit;

[0080] The image analysis unit is used to perform image analysis processing on the power transmission line image data acquired by the mobile acquisition module to obtain the power transmission line image analysis results.

[0081] The analysis model can also perform image analysis and processing on the power transmission line image data acquired by the mobile acquisition module. It can perform analysis of power transmission line coverings and bird damage based on the image data, thereby improving the adaptability of power transmission line abnormality analysis.

[0082] Preferably, the back-end management layer includes a visualization module and an operation and maintenance management module;

[0083] The visualization module is used to integrate the monitoring feature information of the power transmission line into the display model through the preset display model, and to display the monitoring results of the power transmission line status; the display model includes a digital twin model of the power transmission line, a two-dimensional GIS power transmission line map model, and a three-dimensional GIS power transmission line map model;

[0084] The operation and maintenance management module is used to monitor the characteristic information of the transmission line. When the characteristic information of the transmission line monitoring is abnormal, the module generates corresponding operation and maintenance scheduling instructions based on the abnormal results. The operation and maintenance scheduling instructions include the location information corresponding to the abnormal results and the abnormal transmission line monitoring characteristic information.

[0085] The back-end management system can visualize the operation and maintenance monitoring status information of the transmission lines within the region according to the needs of operation and maintenance management. At the same time, it can quickly respond to abnormal operation and maintenance monitoring situations and further generate operation and maintenance dispatch instructions to send relevant abnormality reminders to the management personnel in the abnormal areas. This enables on-site management personnel to arrive at the scene based on the abnormality reminders to handle the abnormal monitoring situation, prevent the abnormal situation from escalating, and improve the efficiency and effectiveness of transmission line operation and maintenance.

[0086] Preferably, the visualization module also includes a model building unit;

[0087] The model building unit is used to build a corresponding display model based on the actual construction of the transmission line, and set corresponding data nodes in the display model. The data nodes are then matched with the transmission line status data obtained by the data acquisition layer, so that the transmission line status data obtained by the data acquisition layer or the transmission line monitoring feature information obtained by analyzing the transmission line status data can be integrated into the corresponding data nodes for display.

[0088] The built display model can be customized according to the actual situation, which helps to improve the display effect of the display model.

[0089] It should be noted that the functional units / modules in the various embodiments of the present invention can be integrated into one processing unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated into one unit / module. The integrated unit / module described above can be implemented in hardware or in the form of software functional units / modules.

[0090] From the above description of the embodiments, those skilled in the art will clearly understand that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code, or any suitable combination thereof. For hardware implementation, the processor can be implemented in one or more of the following units: Application-Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field-Programmable Gate Array (FPGA), processor, controller, microcontroller, microprocessor, other electronic units designed to implement the functions described herein, or combinations thereof. For software implementation, some or all of the processes of the embodiments can be implemented by a computer program instructing the associated hardware. During implementation, the program can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of a computer program from one place to another. Storage media can be any available medium accessible to a computer. Computer-readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code having the form of instructions or data structures and accessible to a computer.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should be able to analyze that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. A power transmission line operation and maintenance monitoring system, characterized in that, It includes a data acquisition layer, a data processing layer, and a back-end management layer; among which, The data acquisition layer includes a sensor acquisition module fixedly installed on the transmission line and a mobile acquisition module for inspection along the transmission line; the data acquisition layer is used to acquire transmission line status data in real time through the sensor acquisition module and the mobile acquisition module, and transmit the acquired transmission line status data to the data processing layer through a wireless communication base station. The data processing layer is used to analyze and process the acquired power transmission line status data and extract power transmission line monitoring feature information; The back-end management layer is used to integrate the transmission line monitoring feature information into the display model through the preset display model, display the transmission line monitoring feature information, and generate corresponding operation and maintenance scheduling instructions when the transmission line monitoring feature information is abnormal. A wireless IoT communication network is established between the sensor acquisition module and the mobile acquisition module. The sensor acquisition module and the mobile acquisition module transmit the collected power line status data to the wireless communication base station via single-hop or multi-hop transmission. The wireless communication base station then packages the aggregated power line status data and transmits it to the data processing layer. Specifically, this includes: Each sensor acquisition node periodically calculates its current performance characteristic factor, which is obtained by calculating the remaining energy percentage value of the sensor acquisition node, the difference between the remaining energy percentage values ​​at adjacent times, the data transmission rate value, and the preset values ​​of the three. Each sensor acquisition node will display its own performance characteristic factor. Compared with the preset performance characteristic standard value When a comparison is performed, When the sensor acquisition node is active, it marks its current node type as a node of interest; otherwise, it marks its current node type as a general node. Each sensor acquisition node broadcasts its current node type and performance characteristic factors to other neighboring nodes within its direct communication range. The node of interest selects the general node with the largest performance characteristic factor as its next-hop node based on the node type and performance characteristic factor broadcast by other sensor acquisition nodes. The node then transmits the power line status data it has collected to the next-hop node, which in turn transmits the aggregated power line status data to the wireless communication base station. The mobile acquisition node calculates its own intermediate characteristic factors, which are obtained by calculating the remaining energy percentage value, data transmission rate value, and preset values ​​of both of the mobile acquisition node. The sensor acquisition node makes a judgment based on the received mobile node information, among which the node of interest will consider the performance characteristics factor of the next-hop node with which it has established a connection. Real-time intermediate feature factors of mobile acquisition nodes When comparing, At that time, the node of interest establishes a communication connection with the mobile data collection node based on the connection establishment invitation information in the mobile node information, and uses the mobile data collection node as its next-hop node. The node then transmits the power line status data it has collected to the next-hop node, which in turn transmits the aggregated power line status data to the wireless communication base station.

2. The power transmission line operation and maintenance monitoring system according to claim 1, characterized in that, The sensor acquisition module includes temperature sensors, humidity sensors, wind speed and direction sensors, and tension sensors installed on the power transmission line; it collects power transmission line status data through each type of sensor, including temperature data, humidity data, wind speed and direction data, and tension data.

3. The power transmission line operation and maintenance monitoring system according to claim 1, characterized in that, The mobile data acquisition module includes an inspection unit and an inspection data acquisition unit, wherein... The inspection unit is mounted on a handheld terminal or drone terminal and is used to complete inspection tasks according to a preset inspection route. The inspection and data acquisition unit is used to collect inspection and monitoring data in real time during the inspection task, including power transmission line image data.

4. The power transmission line operation and maintenance monitoring system according to claim 1, characterized in that, The data processing layer includes a preprocessing module, an analysis module, and a feature extraction module; The preprocessing module is used to preprocess the acquired transmission line status data packets, including data cleaning and standardization preprocessing, to obtain preprocessed transmission line status data. The analysis module is used to perform standard analysis based on the acquired single transmission line status data, or to perform joint analysis based on multiple transmission line status data, to obtain the transmission line operation and maintenance status analysis results; The feature extraction module is used to extract operation and maintenance features based on the power transmission line status data and the analysis results of power transmission line operation and maintenance status over a period of time, so as to obtain power transmission line monitoring feature information. The monitoring characteristics of power transmission lines include status characteristics and change characteristics.

5. A power transmission line operation and maintenance monitoring system according to claim 4, characterized in that, The analysis module includes standard analysis units and joint analysis units; The standard analysis unit is used to compare and analyze the acquired single transmission line status data with the corresponding status standards. When the value of the transmission line status data is within the range of the corresponding status standards, the standard analysis result of the indicator is normal; otherwise, when the value of the transmission line status data exceeds the range of the corresponding status standards, the standard analysis result of the indicator is abnormal. The joint analysis unit is used to form a feature dataset based on the acquired individual transmission line status data according to the preset grouping criteria, and input the feature dataset into the trained joint analysis model for joint analysis to obtain the transmission line operation and maintenance status analysis results.

6. The power transmission line operation and maintenance monitoring system according to claim 1, characterized in that, The analysis module also includes an image analysis unit; The image analysis unit is used to perform image analysis processing on the power transmission line image data acquired by the mobile acquisition module to obtain the power transmission line image analysis results.

7. The power transmission line operation and maintenance monitoring system according to claim 1, characterized in that, The back-end management layer includes a visualization module and an operations and maintenance management module; The visualization module is used to integrate the characteristic information of power transmission line monitoring into the display model through a preset display model, and to display the monitoring results of power transmission line status. The models on display include a digital twin model of a power transmission line, a two-dimensional GIS power transmission line map model, and a three-dimensional GIS power transmission line map model. The operation and maintenance management module is used to monitor the characteristic information of the transmission line. When the characteristic information of the transmission line monitoring is abnormal, the module generates corresponding operation and maintenance scheduling instructions based on the abnormal results. The operation and maintenance scheduling instructions include the location information corresponding to the abnormal results and the abnormal transmission line monitoring characteristic information.

8. A power transmission line operation and maintenance monitoring system according to claim 7, characterized in that, The visualization module also includes model building units; The model building unit is used to build a corresponding display model based on the actual construction of the transmission line, and set corresponding data nodes in the display model. The data nodes are then matched with the transmission line status data obtained by the data acquisition layer, so that the transmission line status data obtained by the data acquisition layer or the transmission line monitoring feature information obtained by analyzing the transmission line status data can be integrated into the corresponding data nodes for display.

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