Distribution line operation state sensing method and system

Abstract

The invention provides a distribution line operation state sensing method and system, and relates to the technical field of line state sensing, the operation state of a target stay wire pole in a distribution line is sensed in real time, and the sensed operation state data of the target stay wire pole is transmitted to a data terminal; extracting stay wire tension data and electric pole dip angle data of the target stay wire electric pole, determining tension response characteristics through the stay wire tension data, and determining dip angle fluctuation according to the electric pole dip angle data; acquiring wind load data of the position of the target stay wire pole, and determining a wind load collapse coefficient of the target stay wire pole based on the wind load data; and carrying out collapse prediction on the target stay wire pole according to the tension response characteristics, the inclination fluctuation degree and the wind load collapse coefficient to obtain a collapse prediction result, and carrying out perception early warning according to the collapse prediction result. According to the application, the collapse probability of the stay wire pole can be predicted by combining the stress change, the inclination angle change and the wind power influence of the stay wire pole, so that the pre-alarm of a sensing system is realized.

Description

Technical Field

[0001] The present application relates to the technical field of line status perception, and more specifically, to a method and system for perceiving the operating status of a distribution line. Background Art

[0002] The perception of the operating status of distribution lines is one of the core technologies to ensure the safe, stable and efficient operation of the power system. Its goal is to fully understand the operating status of the lines and warn of potential failure risks in advance through real-time monitoring and analysis of key parameters of distribution lines, thereby achieving precise operation and maintenance and intelligent management of the distribution system. The operating status perception of distribution lines mainly includes the monitoring of the tension of the guyed poles, the change of the pole inclination, the influence of environmental wind loads and their comprehensive coupling with line operation. Through multi-dimensional data collection and analysis, it is possible to identify abnormal conditions of the lines, predict potential damage risks, and provide a scientific basis for maintenance decisions.

[0003] However, in the perception of the operating status of distribution lines, the operating environment of distribution lines is complex, and the guy wires, poles and lines are significantly affected by multiple external factors such as temperature, humidity, wind, etc., and the monitoring data is easily interfered by noise. Secondly, the stress changes and inclination changes of guy wire poles are usually nonlinear and coupled, and their changing patterns are complex. Traditional single analysis methods are difficult to accurately identify potential fault characteristics. Therefore, how to combine the stress changes, inclination changes and wind effects of guy wire poles to predict the probability of collapse of guy wire poles in order to realize the early warning of the perception system is a difficult problem faced by the industry. Summary of the invention

[0004] The present application provides a distribution line operation status perception method and system, which can predict the collapse probability of the guyed poles by combining the stress changes, inclination changes and wind influence of the guyed poles, so as to realize the early warning of the perception system.

[0005] In a first aspect, the present application provides a method for sensing the operating status of a distribution line, the sensing method comprising the following steps:

[0006] Real-time sensing of the operating status of a target guyed pole in a distribution line, and transmitting the sensed operating status data of the target guyed pole to a data terminal based on the magnitude of the change in the operating status;

[0007] The data terminal extracts the guy wire tension data and the pole inclination data of the target guy wire pole from the operation status data, determines the tension response characteristics of the target guy wire pole through the guy wire tension data, and determines the inclination fluctuation degree of the target guy wire pole according to the pole inclination data;

[0008] Acquire wind load data of a target guyed pole at a location thereof, and determine a wind load collapse coefficient of the target guyed pole based on the wind load data;

[0009] The target guyed pole is predicted to collapse according to the tension response characteristics, the inclination fluctuation degree and the wind load collapse coefficient, a collapse prediction result of the target guyed pole is obtained, and perception warning is performed according to the collapse prediction result.

[0010] Furthermore, vibrating-wire strain gauges and dual-axis inclinometers are used to sense the operating status of target guy poles in the distribution line in real time.

[0011] Furthermore, edge computing is performed on the sensed operating status data of the target guyed pole to obtain a variation range of the operating status.

[0012] Furthermore, transmitting the sensed operating status data of the target guy pole to the data terminal based on the variation of the operating status means transmitting the sensed operating status data of the target guy pole to the data terminal when the variation of the operating status exceeds a set threshold.

[0013] Furthermore, the operating status data includes guy wire tension data and pole inclination data of the target guy wire pole.

[0014] Furthermore, determining the tension response characteristics of the target guyed pole through the guyed pole tension data specifically includes:

[0015] Performing time series analysis on the guy wire tension data to obtain a tension difference sequence of a target guy wire pole;

[0016] Response features are extracted from the tension difference sequence to obtain the tension response features of the target guyed pole.

[0017] Further, determining the inclination fluctuation of the target guyed pole according to the pole inclination data specifically includes:

[0018] Determining data fluctuation according to the pole inclination data;

[0019] Performing frequency domain analysis on the pole inclination data to obtain the total frequency domain energy;

[0020] The inclination fluctuation of the target guyed pole is determined by the data fluctuation and the sum of the frequency domain energy.

[0021] Furthermore, obtaining wind load data at the location of the target guyed pole specifically includes:

[0022] Real-time monitoring of wind speed information and wind direction angle at the location of the target guyed pole;

[0023] The wind load data of the target guy pole is determined by the wind speed information and the wind direction angle.

[0024] Further, the collapse of the target guyed pole is predicted based on the tension response characteristics, the inclination fluctuation degree and the wind load collapse coefficient, and the collapse prediction result of the target guyed pole is obtained, which specifically includes:

[0025] Get pre-trained machine learning-based collapse prediction models;

[0026] Using the tension response characteristics and the inclination fluctuation as input data, and using the wind load collapse coefficient as input weight;

[0027] The input data and the input weights are input into the collapse prediction model to perform collapse prediction, thereby obtaining a collapse prediction result of a target guy pole.

[0028] In a second aspect, the present application provides a distribution line operation status perception system, which is used to execute a distribution line operation status perception method, and the perception system includes:

[0029] An intelligent sensing module, used for sensing the operating status of a target guyed pole in a distribution line in real time, and transmitting the sensed operating status data of the target guyed pole to a data terminal based on the change amplitude of the operating status;

[0030] A data analysis module, used for the data terminal to extract the guy wire tension data and the pole inclination data of the target guy wire pole from the operation status data, determine the tension response characteristics of the target guy wire pole through the guy wire tension data, and determine the inclination fluctuation degree of the target guy wire pole according to the pole inclination data;

[0031] A wind load determination module, used to obtain wind load data of a target guyed pole at a location, and determine a wind load collapse coefficient of the target guyed pole based on the wind load data;

[0032] The perception and warning module is used to predict the collapse of the target guyed pole according to the tension response characteristics, the inclination fluctuation degree and the wind load collapse coefficient, obtain the collapse prediction result of the target guyed pole, and perform perception and warning according to the collapse prediction result.

[0033] The technical solution disclosed in this application has the following beneficial effects:

[0034] The operating status of the target guy pole in the distribution line is sensed in real time, and the operating status data of the sensed target guy pole is transmitted to a data terminal based on the change amplitude of the operating status; the data terminal extracts the guy wire tension data and the pole inclination data of the target guy pole from the operating status data, determines the tension response characteristics of the target guy pole through the guy wire tension data, and determines the inclination fluctuation degree of the target guy pole according to the pole inclination data; obtains the wind load data of the position of the target guy pole, and determines the wind load collapse coefficient of the target guy pole based on the wind load data; predicts the collapse of the target guy pole according to the tension response characteristics, the inclination fluctuation degree and the wind load collapse coefficient, obtains the collapse prediction result of the target guy pole, and performs perception and early warning according to the collapse prediction result.

[0035] It can be seen that in the present application, firstly, data transmission is determined based on the amplitude of the change, that is, edge computing can reduce the transmission of useless data and improve the processing efficiency of the perception system; then, by combining the guy wire tension data and the pole inclination data, the stability of the target guy wire pole under different working conditions can be fully understood, which helps to analyze the stress state and potential problems of the target guy wire pole, and determines the tension response characteristics and inclination fluctuation degree, so as to comprehensively and accurately perceive the operating state of the target guy wire pole; then, by obtaining the wind load data and determining the wind load collapse coefficient based on the wind load data, it can not only help to identify the impact of wind on the stability of the target guy wire pole in advance, but also optimize the early warning and monitoring functions of the perception system; finally, by using the tension response characteristics, inclination fluctuation degree and wind load collapse coefficient as input data and weights, and inputting them into the trained machine learning model, it is possible to accurately predict the collapse risk of the target guy wire pole, and by utilizing the pattern recognition ability of machine learning and combining real-time data for collapse prediction, timely decision support can be provided through the early warning system to realize the advance alarm of the perception system.

[0036] In summary, the technical solution adopted in the present application can combine the stress change, inclination change and wind influence of the guyed pole to predict the collapse probability of the guyed pole, so as to realize the early warning of the perception system. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0038] Figure 1 is a flow chart of a method for sensing the operating status of a distribution line provided in the present application;

[0039] Figure 2 It is a schematic diagram of a process for determining the inclination fluctuation of a target guyed pole provided by the present application;

[0040] Figure 3 It is a module structure diagram of the distribution line operation status perception system provided in this application. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0042] The embodiment of the present application provides a distribution line operation status perception method and system, the core of which is to perceive the operation status of a target guy pole in the distribution line in real time, and transmit the perceived operation status data of the target guy pole to a data terminal based on the change amplitude of the operation status; the data terminal extracts the guy wire tension data and the pole inclination data of the target guy pole from the operation status data, determines the tension response characteristics of the target guy pole through the guy wire tension data, and determines the inclination fluctuation degree of the target guy pole according to the pole inclination data; obtains the wind load data of the target guy pole, and determines the wind load collapse coefficient of the target guy pole based on the wind load data; predicts the collapse of the target guy pole according to the tension response characteristics, the inclination fluctuation degree and the wind load collapse coefficient, obtains the collapse prediction result of the target guy pole, and performs perception and early warning according to the collapse prediction result. The above scheme can be used to combine the stress change, inclination change and wind influence of the guyed pole to predict the collapse probability of the guyed pole, so as to realize the early warning of the perception system.

[0043] Embodiment 1: In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 As shown in FIG. 1 , this figure is an exemplary flow chart of a method for sensing the operating status of a distribution line according to this embodiment of the present application. The sensing method includes the following steps:

[0044] In step S1, the operating status of a target guy pole in a distribution line is sensed in real time, and the sensed operating status data of the target guy pole is transmitted to a data terminal based on the variation range of the operating status.

[0045] In this embodiment, a vibrating-wire strain gauge and a dual-axis inclinometer can be used to sense the operating status of a target guy pole in a distribution line in real time. In specific implementation, first, a vibrating-wire strain gauge with high precision and strong environmental interference resistance can be selected and installed on the guy wire of the target guy pole to monitor the stress change of the guy wire in real time and output the guy wire tension data; then, a dual-axis inclinometer can be installed in the middle section of the target guy pole to monitor the inclination change of the pole in the horizontal and vertical directions and output the pole inclination data, wherein the pole inclination refers to the inclination angle of the target guy pole relative to the vertical ground state toward the ground; finally, the data consisting of the guy wire tension data and the pole inclination data can be combined as the operating status data of the perceived target guy pole, that is, the operating status data includes the guy wire tension data and the pole inclination data of the target guy pole.

[0046] In this embodiment, edge computing is performed on the perceived operating status data of the target guy pole to obtain the variation range of the operating status; based on the variation range of the operating status, the perceived operating status data of the target guy pole is transmitted to the data terminal.

[0047] In specific implementation, first, edge computing can be performed on the perceived operating status data of the target guy pole, that is, the edge computing device is used to locally process the real-time perceived operating status data of the target guy pole, and the dynamic changes in the guy wire tension and the dynamic changes in the pole inclination are calculated respectively, and the dynamic changes of the two are weighted and summed, wherein the corresponding weights can be set according to historical experience, so that the result is used as the amplitude of change in the operating status; then, the operating status data of the perceived target guy pole can be transmitted to the data terminal based on the amplitude of change in the operating status, that is, when the amplitude of change in the operating status exceeds a set threshold, the operating status data of the perceived target guy pole is transmitted to the data terminal, wherein the set threshold can be set by analyzing historical data.

[0048] In step S2, the data terminal extracts the guy wire tension data and pole inclination data of the target guy wire pole from the operating status data, determines the tension response characteristics of the target guy wire pole through the guy wire tension data, and determines the inclination fluctuation degree of the target guy wire pole according to the pole inclination data.

[0049] In specific implementation, the data terminal can extract the guy wire tension data and the pole inclination data of the target guy wire pole from the running status data by traversing.

[0050] In this embodiment, the tension response characteristics of the target guyed pole can be determined by the guyed pole tension data in the following manner, namely:

[0051] Performing time series analysis on the guy wire tension data to obtain a tension difference sequence of a target guy wire pole;

[0052] Response features are extracted from the tension difference sequence to obtain the tension response features of the target guyed pole.

[0053] In specific implementation, first, a time series analysis can be performed on the guy wire tension data, that is, each data point in the guy wire tension data is sequentially subtracted, for example, the i-th data point in the guy wire tension data is subtracted from the i-1-th data point, and the result is used as the tension difference value, which represents the tension change value between adjacent time points, so that the sequence composed of all tension difference values ​​can be used as the tension difference sequence of the target guy wire pole; then, the response feature of the tension difference sequence can be extracted to obtain the tension response feature of the target guy wire pole, wherein the tension response feature is a feature used to measure the tension fluctuation degree of the target guy wire pole, and the standard deviation of all tension difference values ​​in the tension difference sequence can be used as the tension response feature of the target guy wire pole.

[0054] Preferably, in this embodiment, the inclination fluctuation degree of the target guyed pole is determined according to the pole inclination data, referring to Figure 2 As shown in FIG. 1 , this figure is a schematic diagram of a process for determining the inclination fluctuation of a target guyed pole in some embodiments of the present application. In this embodiment, determining the inclination fluctuation of a target guyed pole can be achieved by using the following steps:

[0055] First, in step S21, the data fluctuation is determined according to the pole inclination data;

[0056] Then, in step S22, the pole inclination data is subjected to frequency domain analysis to obtain the frequency domain energy sum;

[0057] Finally, in step S23, the inclination fluctuation of the target guyed pole is determined by the data fluctuation and the frequency domain energy sum.

[0058] In the specific implementation, first, the data fluctuation degree can be determined according to the pole inclination data, wherein the data fluctuation degree represents the fluctuation degree of all data points in the pole inclination data yesterday, and the ratio of the standard deviation of all data points in the pole inclination data to the mean of all data points can be used as the data fluctuation degree; then, the pole inclination data can be subjected to frequency domain analysis, and the frequency domain analysis can help identify the periodic characteristics of the pole inclination change, and the fast Fourier transform can be used to convert the pole inclination data into frequency domain data, thereby calculating the energy sum of all frequency components and obtaining the frequency The result of frequency domain analysis can provide the periodic information of the inclination change of the target guyed pole. According to the distribution of energy, the main frequency range of the pole inclination change can be determined, and its stability and potential risks can be further analyzed. Finally, the inclination fluctuation of the target guyed pole can be determined by the data fluctuation and the sum of frequency domain energy, wherein the inclination fluctuation represents the degree of fluctuation of the inclination of the target guyed pole. The sum of frequency domain energy can be normalized, and the product of the normalized result and the data fluctuation is taken as the inclination fluctuation of the target guyed pole.

[0059] It should be noted that by combining the guy wire tension data and the pole inclination data, we can fully understand the stability of the target guy wire pole under different working conditions, help analyze the stress state and potential problems of the target guy wire pole, and determine the tension response characteristics and inclination fluctuation degree. It can fully and accurately perceive the operating status of the target guy wire pole and help identify potential failure risks, thereby improving the accuracy and reliability of the early warning.

[0060] In step S3, wind load data of the target guyed pole at the location is obtained, and the wind load collapse coefficient of the target guyed pole is determined based on the wind load data.

[0061] In this embodiment, the wind load data at the location of the target guyed pole may be obtained in the following manner:

[0062] Real-time monitoring of wind speed information and wind direction angle at the location of the target guyed pole;

[0063] The wind load data of the target guy pole is determined by the wind speed information and the wind direction angle.

[0064] In specific implementation, first, the wind speed information and wind direction angle at the location of the target guyed pole can be monitored in real time, and the wind direction information at the location of the target guyed pole can be obtained in real time by installing a wind direction sensor (such as an anemometer, wind vane). The wind direction sensor can usually provide an accurate wind direction angle, that is, the angle between the direction of the wind blowing and the relative direction of the pole; finally, the wind load data at the location of the target guyed pole can be determined by the wind speed information and the wind direction angle, that is, after obtaining the wind speed information and the wind direction angle data, the two can be combined to calculate the wind load on the target guyed pole at the location. In actual implementation, the wind load on the target guyed pole at the location can be determined by the following formula:

[0065] F wind (t) = C*S*V 2 (t)*ρ*sin 2 θ t

[0066] Among them, F wind (t) represents the wind load on the target guyed pole at the time t, C represents the wind resistance coefficient of the target guyed pole, S represents the projected area of ​​the target guyed pole perpendicular to the wind flow direction, V(t) represents the wind speed at the time t, ρ represents the air density, and θ t It represents the wind direction angle at time t. The wind load data of the target guy pole can be obtained by the above method.

[0067] In this embodiment, the wind load collapse coefficient of the target guyed pole is determined based on the wind load data; it should be noted that in this application, the wind load collapse coefficient is an indicator used to indicate the possibility of collapse of the target guyed pole under the current wind load. In actual implementation, the wind load collapse coefficient can be determined by the following formula:

[0068]

[0069] Where P represents the wind load collapse coefficient of the target guyed pole, F represents the standard value of the wind load, which can be set empirically, σ and μ represent the standard deviation and mean of all data points in the wind load data, respectively, and F wind (t) represents the wind load on the target guyed pole at the location at time t. It should be noted that the greater the wind load collapse coefficient, the higher the risk of the target guyed pole tilting or collapsing.

[0070] It should be noted that by obtaining wind load data and determining the wind load collapse coefficient based on the wind load data, it can not only help identify the impact of wind on the stability of the target guyed poles in advance, but also optimize the early warning and monitoring functions of the perception system, thereby ensuring the stable operation of the power system, reducing the occurrence of failures and reducing maintenance costs.

[0071] In step S4, the collapse of the target guyed pole is predicted based on the tension response characteristics, the inclination fluctuation degree and the wind load collapse coefficient to obtain a collapse prediction result of the target guyed pole, and a perception warning is performed based on the collapse prediction result.

[0072] In this embodiment, the collapse prediction of the target guyed pole is performed according to the tension response characteristics, the inclination fluctuation degree and the wind load collapse coefficient, and the collapse prediction result of the target guyed pole can be obtained in the following manner, namely:

[0073] Get pre-trained machine learning-based collapse prediction models;

[0074] Using the tension response characteristics and the inclination fluctuation as input data, and using the wind load collapse coefficient as input weight;

[0075] The input data and the input weights are input into the collapse prediction model to perform collapse prediction, thereby obtaining a collapse prediction result of a target guy pole.

[0076] In the specific implementation, first, it is necessary to build and train a collapse prediction model based on machine learning. The training process of the collapse prediction model requires the use of a large amount of historical data, including the tension response characteristics of the pole, the inclination fluctuation, the wind load collapse coefficient and the actual collapse of the pole. The collapse prediction model used in this application is a machine learning model based on the long short-term memory network; then, the tension response characteristics and the inclination fluctuation can be used as input data, and the wind load collapse coefficient can be used as input weights; finally, the input data and input weights can be input into the collapse prediction model for collapse prediction. The collapse prediction model outputs the collapse prediction result of the target guyed pole according to the pattern learned during the training process. In this application, the collapse prediction result includes the following information:

[0077] Collapse probability: represents the probability of the target guyed pole collapsing, usually a value between 0 and 1. For example, 0.85 means that the probability of the pole collapsing is 85%.

[0078] Risk level: The collapse prediction model can classify the risks of poles into different levels (such as high risk, medium risk, and low risk) according to the probability of collapse, helping operation and maintenance personnel to respond quickly.

[0079] It should be noted that by taking the tension response characteristics, inclination fluctuation and wind load collapse coefficient as input data and weights and inputting them into the trained machine learning model, the collapse risk of the target guyed pole can be accurately predicted. By utilizing the pattern recognition capability of machine learning and combining it with real-time data for collapse prediction, timely decision support can be provided through the early warning system to ensure the safety and stability of the distribution network.

[0080] In this embodiment, the perception and warning based on the collapse prediction result is that the data terminal sends the collapse prediction result as warning information to the control center; the collapse prediction result will be fed back to the relevant management personnel or monitoring platform of the control center as warning information. If the prediction result shows that the probability of collapse is high or the risk level is high, the system will trigger a warning and notify the operation and maintenance personnel to take appropriate measures, such as checking the pole structure, strengthening the support or limiting the impact of wind loads.

[0081] It can be seen that in the present application, firstly, data transmission is determined based on the amplitude of the change, that is, edge computing can reduce the transmission of useless data and improve the processing efficiency of the perception system; then, by combining the guy wire tension data and the pole inclination data, the stability of the target guy wire pole under different working conditions can be fully understood, which helps to analyze the stress state and potential problems of the target guy wire pole, and determines the tension response characteristics and inclination fluctuation degree, so as to comprehensively and accurately perceive the operating state of the target guy wire pole; then, by obtaining the wind load data and determining the wind load collapse coefficient based on the wind load data, it can not only help to identify the impact of wind on the stability of the target guy wire pole in advance, but also optimize the early warning and monitoring functions of the perception system; finally, by using the tension response characteristics, inclination fluctuation degree and wind load collapse coefficient as input data and weights, and inputting them into the trained machine learning model, it is possible to accurately predict the collapse risk of the target guy wire pole, and by utilizing the pattern recognition ability of machine learning and combining real-time data for collapse prediction, timely decision support can be provided through the early warning system to realize the advance alarm of the perception system.

[0082] In summary, the technical solution adopted in the present application can combine the stress change, inclination change and wind influence of the guyed pole to predict the collapse probability of the guyed pole, so as to realize the early warning of the perception system.

[0083] Embodiment 2: This application provides a distribution line operation status perception system, referring to Figure 3 As shown, this figure is a schematic diagram of a distribution line operation status perception system according to this embodiment of the present application, and the perception system includes:

[0084] The intelligent sensing module 100 is used to sense the operating status of the target guyed pole in the distribution line in real time, and transmit the sensed operating status data of the target guyed pole to the data terminal based on the change amplitude of the operating status;

[0085] A data analysis module 200, which is used for the data terminal to extract the guy wire tension data and the pole inclination data of the target guy wire pole from the operation status data, determine the tension response characteristics of the target guy wire pole through the guy wire tension data, and determine the inclination fluctuation degree of the target guy wire pole according to the pole inclination data;

[0086] A wind load determination module 300, for acquiring wind load data at a location of a target guyed pole, and determining a wind load collapse coefficient of the target guyed pole based on the wind load data;

[0087] The perception and warning module 400 is used to predict the collapse of the target guyed pole according to the tension response characteristics, the inclination fluctuation degree and the wind load collapse coefficient, obtain the collapse prediction result of the target guyed pole, and perform perception and warning according to the collapse prediction result.

[0088] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0089] Those skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0090] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

Claims

1. A method for sensing the operating status of a distribution line, characterized in that: The sensing method comprises the following steps: Real-time sensing of the operating status of a target guyed pole in a distribution line, and transmitting the sensed operating status data of the target guyed pole to a data terminal based on the magnitude of the change in the operating status; The data terminal extracts the guy wire tension data and the pole inclination data of the target guy wire pole from the operation status data, determines the tension response characteristics of the target guy wire pole through the guy wire tension data, and determines the inclination fluctuation degree of the target guy wire pole according to the pole inclination data; Acquire wind load data of a target guyed pole at a location thereof, and determine a wind load collapse coefficient of the target guyed pole based on the wind load data; The target guyed pole is predicted to collapse according to the tension response characteristics, the inclination fluctuation degree and the wind load collapse coefficient, a collapse prediction result of the target guyed pole is obtained, and perception warning is performed according to the collapse prediction result.

2. A method for sensing the operating status of a distribution line according to claim 1, characterized in that: Use vibrating-wire strain gauges and dual-axis inclinometers to sense the operating status of target guy poles in distribution lines in real time.

3. A method for sensing the operating status of a distribution line according to claim 1, characterized in that: Edge computing is performed on the sensed operating status data of the target guyed pole to obtain the variation range of the operating status.

4. A method for sensing the operating status of a distribution line according to claim 1, characterized in that: Transmitting the sensed operating status data of the target guy pole to the data terminal based on the change amplitude of the operating status means transmitting the sensed operating status data of the target guy pole to the data terminal when the change amplitude of the operating status exceeds a set threshold.

5. A method for sensing the operating status of a distribution line according to claim 1, characterized in that: The operating status data includes the guy wire tension data and the pole inclination data of the target guy wire pole.

6. A method for sensing the operating status of a power distribution line according to claim 1, characterized in that: Determining the tension response characteristics of the target guyed pole through the guyed pole tension data specifically includes: Performing time series analysis on the guy wire tension data to obtain a tension difference sequence of a target guy wire pole; Response features are extracted from the tension difference sequence to obtain the tension response features of the target guyed pole.

7. A method for sensing the operating status of a power distribution line according to claim 1, characterized in that: Determining the inclination fluctuation of the target guyed pole according to the pole inclination data specifically includes: Determining data fluctuation according to the pole inclination data; Performing frequency domain analysis on the pole inclination data to obtain the total frequency domain energy; The inclination fluctuation of the target guyed pole is determined by the data fluctuation and the sum of the frequency domain energy.

8. A method for sensing the operating status of a power distribution line according to claim 1, characterized in that: Obtaining wind load data at the location of the target guyed pole specifically includes: Real-time monitoring of wind speed information and wind direction angle at the location of the target guyed pole; The wind load data of the target guy pole is determined by the wind speed information and the wind direction angle.

9. A method for sensing the operating status of a power distribution line according to claim 1, characterized in that: The collapse prediction of the target guyed pole is performed according to the tension response characteristics, the inclination fluctuation degree and the wind load collapse coefficient, and the collapse prediction result of the target guyed pole is obtained, which specifically includes: Get pre-trained machine learning-based collapse prediction models; Using the tension response characteristics and the inclination fluctuation as input data, and using the wind load collapse coefficient as input weight; The input data and the input weights are input into the collapse prediction model to perform collapse prediction, thereby obtaining a collapse prediction result of a target guy pole.

10. A distribution line operation status perception system, used to execute a distribution line operation status perception method according to any one of claims 1 to 9, characterized in that: The sensing system comprises: An intelligent sensing module, used for sensing the operating status of a target guyed pole in a distribution line in real time, and transmitting the sensed operating status data of the target guyed pole to a data terminal based on the change amplitude of the operating status; A data analysis module, used for the data terminal to extract the guy wire tension data and the pole inclination data of the target guy wire pole from the operation status data, determine the tension response characteristics of the target guy wire pole through the guy wire tension data, and determine the inclination fluctuation degree of the target guy wire pole according to the pole inclination data; A wind load determination module, used to obtain wind load data of a target guyed pole at a location, and determine a wind load collapse coefficient of the target guyed pole based on the wind load data; The perception and warning module is used to predict the collapse of the target guyed pole according to the tension response characteristics, the inclination fluctuation degree and the wind load collapse coefficient, obtain the collapse prediction result of the target guyed pole, and perform perception and warning according to the collapse prediction result.

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