A method and system for detecting and evaluating abnormal changes in insulator strings of transmission lines
Patent Information
- Application Number
- CN202410576146.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-05-10
- Publication Date
- 2024-12-31
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
The existing transmission line insulator string abnormal heating detection methods are costly, have poor reliability, strong environmental dependence, and lack accurate acquisition of characteristic parameters in actual heating state, resulting in large errors in evaluation and prediction results, increasing the risk of failure.
The insulator heat generation test platform is built, and the insulator string variation detection and evaluation system is constructed through the electric and thermal coupling model and the filth deterioration model, combined with the flexible temperature sensor and the gray prediction model, to obtain the filth leakage current, voltage, and magnetic field data, and to evaluate the filth deterioration and variation of the insulator string degree.
Reduce inspection costs, improve the reliability and accuracy of inspection, enhance the environmental adaptability of the system, effectively prevent potential safety hazards, realize intelligent operation and maintenance, and provide reliable technology for the safe and stable operation of the power system. support.
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Figure CN118584261B_ABST
Abstract
Description
Technical Field
[0001] The present invention mainly relates to the technical field of power transmission line detection, and in particular to a transmission line insulator string abnormality detection and evaluation system. Background Art
[0002] As a key component connecting power plants and local power grids, transmission lines have insulator strings that play a vital insulating role. However, due to the polarization effect stimulated by the power frequency voltage, insulator strings may experience abnormal heating during operation, which is crucial to ensure the normal operation of transmission lines. In recent years, abnormal heating failures of insulators have occurred frequently, and even large-scale abnormal temperature rises have occurred, seriously threatening the safe and stable operation of the power grid. Therefore, scholars at home and abroad have paid extensive attention to the problem of abnormal heating of insulators.
[0003] There are currently a variety of detection methods for the problem of abnormal heating of insulators, among which robot inspection and infrared thermal imager method are more commonly used. However, as a means of state perception and fault diagnosis, robot inspection has limitations such as high cost, low safety, and poor reliability, which limit its widespread application. At the same time, although the infrared thermal imager method can use the thermal effect on the surface of the insulator string for online detection, its effect is affected by the ambient temperature and humidity, and the environmental conditions need to be strictly controlled. In addition, the operation and maintenance must be completed by professionals, resulting in high costs. In addition, the existing methods lack accurate acquisition of characteristic parameters under actual heating conditions, resulting in large errors in evaluation and prediction results, further increasing the risk of abnormal heating failures. Therefore, in the face of these technical problems, it is urgent to develop a more reliable, accurate, and cost-effective method for detecting abnormal heating of insulators to ensure the safe and stable operation of transmission lines. Summary of the invention
[0004] In order to solve the above technical problems, the present invention provides a method and system for detecting and evaluating abnormal changes in insulator strings of power transmission lines, so as to solve the problems of high cost, poor reliability and strong environmental dependence in the detection method of abnormal heating of insulator strings.
[0005] In order to solve the above problems, the present invention adopts the following technical solutions:
[0006] A method for detecting and evaluating abnormal changes in insulator strings of a transmission line, characterized in that it comprises the following steps:
[0007] S1, build an insulator heating test platform to obtain the pollution degradation data of insulator strings under different pollution degradation conditions;
[0008] S2, inputting the pollution degradation data of the insulator string into the electrothermal coupling model of the insulator string to obtain the pollution leakage current or through-leakage current, voltage, magnetic field data of the insulator surface and the temperature field distribution data of each part of the insulator string;
[0009] S3, constructing a pollution degradation model based on the surface pollution leakage current or through-leakage current, voltage, magnetic field data and temperature field distribution data of each part of the insulator string, and obtaining the temperature corresponding to the surface pollution leakage current or through-leakage current generated under different pollution degradation conditions;
[0010] S4, according to the output results of the insulator string electrothermal coupling model, determine the tolerance range of the flexible temperature sensor to temperature, voltage, current and magnetic field, so as to guide the arrangement of the flexible temperature sensor.
[0011] S5, constructing an insulator string variation detection and evaluation model for evaluating the degree of variation of pollution degradation of the insulator string, wherein the insulator string variation detection and evaluation model combines the temperature of the flexible sensor with the pollution degradation model and is trained through a grey prediction model.
[0012] Furthermore, the electrothermal coupling model of the insulator string includes an electromagnetic field model and a heat conduction model. The electromagnetic field model is used to obtain surface contamination leakage current or through-leakage current voltage data, and the heat conduction model is used to obtain temperature field distribution data of each part of the insulator string. The specific steps are as follows:
[0013] S21, inputting the insulator string pollution degradation data into the electromagnetic field model, thereby obtaining the insulator surface pollution leakage current or through-leakage current, voltage, and magnetic field data;
[0014] S22, inputting the insulator surface contamination leakage current or through-leakage current, voltage, and magnetic field data into the thermal conduction model, thereby obtaining the temperature field distribution data of each part of the insulator string.
[0015] Furthermore, the electromagnetic field model is constructed based on Maxwell's equations, and the heat conduction model is constructed based on the heat conduction equations.
[0016] Furthermore, the specific calculation formula of the Maxwell equations is as follows: Where D is the electric displacement vector, Q0 is the amount of free charge passing through the closed surface S, E is the electric field intensity, B is the magnetic induction intensity, dl is the tiny loop element, B is the magnetic induction intensity vector, dS is the infinitesimal area vector of the closed surface, H is the magnetic field intensity, j c is the conduction current density, The rate of change of the electric displacement vector with time.
[0017] Furthermore, the specific calculation formula of the heat conduction equation is as follows: Where T is the temperature field, K is the thermal conductivity, t is the time, ▽ 2 is the Laplace operator, which represents the gradient of the temperature field.
[0018] Furthermore, the pollution degradation model is constructed by fitting a Newton interpolation polynomial model.
[0019] Furthermore, the guiding arrangement of the flexible temperature sensor also needs to determine the response range, resolution and response rate parameters of the flexible temperature sensor according to the temperature amplitude, gradient and change rate factors.
[0020] In addition, the present application also discloses a transmission line insulator string abnormality detection and evaluation system, the system comprising:
[0021] The acquisition module is used to build an insulator heating test platform to obtain the pollution degradation data of insulator strings under different pollution degradation conditions;
[0022] The electrothermal coupling module is used to input the pollution degradation data of the insulator string into the electrothermal coupling model of the insulator string to obtain the pollution leakage current or through-leakage current, voltage, magnetic field data of the insulator surface and the temperature field distribution data of each part of the insulator string;
[0023] The pollution degradation module is used to construct a pollution degradation model based on the surface pollution leakage current or through-leakage current, voltage, magnetic field data and temperature field distribution data of each part of the insulator string, and obtain the temperature corresponding to the surface pollution leakage current or through-leakage current generated under different pollution degradation conditions;
[0024] The layout guidance module is used to determine the tolerance range of the flexible temperature sensor to temperature, voltage, current and magnetic field according to the output results of the insulator string electrothermal coupling model, so as to guide the layout of the flexible temperature sensor.
[0025] The insulator string variation detection and evaluation is used to construct an insulator string variation detection and evaluation model, which is used to evaluate the degree of variation of the pollution degradation of the insulator string. The insulator string variation detection and evaluation model combines the temperature of the flexible sensor with the pollution degradation model and is trained through a grey prediction model.
[0026] Furthermore, the pollution degradation model is constructed by fitting a Newton interpolation polynomial model.
[0027] Furthermore, the electrothermal coupling model of the insulator string includes an electromagnetic field model and a heat conduction model. The electromagnetic field model is used to obtain surface contamination leakage current or through-leakage current voltage data, and the heat conduction model is used to obtain temperature field distribution data of each part of the insulator string.
[0028] The present invention provides a method and system for detecting and evaluating abnormal changes in insulator strings of power transmission lines. By building an insulator heating test platform, using an insulator string electrothermal coupling model and a pollution degradation model, combined with flexible temperature sensor data and a grey prediction model, an accurate evaluation of the degree of pollution degradation variation of the insulator string is achieved. This reduces the cost of abnormal heating detection of insulators, improves reliability and accuracy, enhances the environmental adaptability of the system, effectively prevents potential safety hazards, realizes intelligent operation and maintenance, and provides reliable technical support for the safe and stable operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS
[0029] Figure 1 A schematic diagram of a method for detecting and evaluating abnormal changes in insulator strings of transmission lines;
[0030] Figure 2 It is a schematic diagram of establishing the electrothermal coupling model of the insulator string;
[0031] Figure 3 .Modeling process diagram for the fouling degradation model;
[0032] Figure 4 is the Newton interpolation polynomial difference quotient table;
[0033] Figure 5 A schematic diagram for constructing an insulator string abnormality detection and evaluation model;
[0034] Figure 6 This is a schematic diagram of the structure of a transmission line insulator string abnormality detection and evaluation system proposed in this application; DETAILED DESCRIPTION
[0035] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0036] In recent years, insulator strings, as key components, have important functions in high-voltage power transmission circuits. However, there are some limitations in traditional manual inspections or drone inspections, which are mainly reflected in the following aspects. First, there is a lack of real-time performance. Specifically, traditional inspection methods usually require regular arrangements, and cannot achieve real-time monitoring and feedback of the status of insulator strings. This leads to the inability to detect problems in time in some emergencies, increasing the risk of accidents; second, the level of digitization is insufficient. Specifically, traditional inspection methods mainly rely on manual visual or simple image acquisition, lacking the support of digital technology. This makes data acquisition and processing inefficient, and it is difficult to achieve accurate analysis and evaluation of the status of insulator strings; third, there is a lack of continuity. Specifically, traditional inspection methods can often only be carried out within a specific time period, and cannot achieve continuous monitoring of the status of insulator strings. This makes it difficult to track and grasp the performance changes of insulator strings in a timely manner during long-term operation. In summary, the traditional insulator string detection method has problems such as failure to meet real-time performance, insufficient digitization level, and lack of continuity. A new intelligent diagnostic technology is urgently needed to solve these challenges. In view of this background and demand, this application proposes a method and system for detecting and evaluating abnormal changes in insulator strings of transmission lines. By using the electromagnetic field model and the heat conduction model, combined with flexible temperature sensors, the real-time, continuous and reliable perception of the insulator string status is achieved, which will greatly improve the efficiency and accuracy of insulator string detection and help improve the safety and stability of transmission lines. Figure 1 and Figure 5 As shown, the specific steps are as follows:
[0037] Step S1, building an insulator heating test platform to obtain pollution degradation data of insulator strings under different pollution degradation conditions;
[0038] Specifically, in this step, the insulator heating test platform is built to simulate the working environment of the insulator string under different pollution and degradation conditions to obtain the corresponding pollution degradation data. Through this platform, the insulator string can be controlled and monitored for subsequent experiments. On this experimental platform, a large number of simulation experiments were carried out on the insulator string under different pollution levels, humidity, temperature and climate conditions. The purpose of these experiments is to collect and record the pollution degradation data of the insulator string under different pollution degradation conditions, including the pollution level on the insulator surface, environmental parameters such as humidity and temperature. These data are the key inputs in step S2, because in step S2, these pollution degradation data are input into the electrothermal coupling model of the insulator string. This model uses Maxwell's equations to calculate the pollution leakage current or through-leakage current, distributed voltage and magnetic field on the insulator surface. The parameters in the Maxwell equations are determined by the data collected in step S1.
[0039] Step S2, inputting the pollution degradation data of the insulator string into the electrothermal coupling model of the insulator string to obtain the pollution leakage current or through-leakage current, voltage, magnetic field data of the insulator surface and the temperature field distribution data of each part of the insulator string;
[0040] For details, see Figure 2 As shown, in this step, the electrothermal coupling model of the insulator string includes an electromagnetic field model and a heat conduction model. These two models are used to obtain the contamination leakage current or through-leakage current, voltage, and magnetic field data on the surface of the insulator, as well as the temperature field distribution data of each part of the insulator string. The specific steps are as follows:
[0041] Step S21, inputting the insulator string pollution degradation data into the electromagnetic field model, thereby obtaining the insulator surface pollution leakage current or through-leakage current, voltage, and magnetic field data;
[0042] Specifically, the pollution degradation data of the insulator string is input into the electromagnetic field model to obtain the pollution leakage current or through-leakage current, voltage, and magnetic field data on the surface of the insulator. In this step, the pollution degradation data of the insulator string is used as input, and the pollution leakage current or through-leakage current, voltage, and magnetic field data on the surface of the insulator are calculated through the electromagnetic field model. The electromagnetic field model is constructed based on Maxwell's equations, which describe the basic behavior of the electromagnetic field. The Maxwell equations are derived from Gauss's theorem and the loop theorem of the electromagnetic field state under two different conditions, see Figure 2 As shown below:
[0043] Steady current magnetic field: in The magnetic induction intensity vector, The infinitesimal area vector of a closed surface. This formula shows, through Gauss's theorem, that when there is no magnetic charge, the total flux of the magnetic field through the closed surface is zero. This means that the magnetic field has no source or leakage out of the closed surface, and they can enter and leave the surface freely; Where H is the magnetic field strength vector. The infinitesimal length vector of the closed loop. c The current in a closed loop. Current density vector. This formula shows, through the loop theorem, that there is a direct relationship between the magnetic field circulating within a loop and the current in that loop.
[0044] Displacement current magnetic field: in The magnetic induction intensity vector, The infinitesimal area vector of a closed surface. This formula shows that when there is no free magnetic charge, the total flux of the magnetic field through the closed surface is zero. This means that the magnetic field lines do not originate anywhere in space, nor do they disappear anywhere in space, but form a closed loop; in, is the magnetic field strength vector. The infinitesimal length vector of the closed loop. d Induced current. Electric displacement vector. t time. This formula describes that the circulation of the magnetic field along a closed loop is equal to the sum of the currents in the loop, and the induced current generated by the circulation of the electric field on the loop through time variation, and explains the relationship between the magnetic field circulation in the loop and the current in the loop, and the induced current generated by the electric field through time variation. From this, it is deduced that the Maxwell equations are: Equation 1 is Gauss's theorem (electric field version) in Maxwell's equations, where D is the electric displacement vector, Q0 is the amount of free charge passing through the closed surface S, which describes the origin and distribution of the electric field and shows the relationship between the electric field flux and the amount of free charge enclosed. Equation 2 is Faraday's law of electromagnetic induction in Maxwell's equations, where E is the electric field intensity, B is the magnetic induction intensity, and dl is a tiny loop element, which shows that a changing magnetic field can generate an electric field in a closed loop, and the loop integral of this electric field is equal to the rate of change of the magnetic flux. This equation explains the phenomenon of electromagnetic induction. Equation 3 is Gauss's theorem (magnetic field version) in Maxwell's equations. It shows that the closed flux of the magnetic field is zero, indicating that magnetic monopoles do not exist. In other words, the magnetic field lines are closed and there are no isolated magnetic charges. Equation 4 is Ampere's loop theorem in Maxwell's equations, where H is the magnetic field intensity, j c is the conduction current density, The rate of change of the electric displacement vector with time shows that the loop integral of the magnetic field intensity H through the closed loop is equal to the sum of the conduction current through the surface S and the rate of change of the electric displacement vector with time. This equation describes the generation and propagation of the magnetic field.
[0045] Step S22, inputting the insulator surface contamination leakage current or through-leakage current, voltage, and magnetic field data into the thermal conduction model, thereby obtaining the temperature field distribution data of each part of the insulator string.
[0046] Specifically, the contamination leakage current or through-leakage current, voltage, and magnetic field data on the insulator surface are input into the thermal conduction model to obtain the temperature field distribution data of each part of the insulator string. In this step, since the contamination leakage current or through-leakage current, voltage, and magnetic field data on the insulator surface will affect the heat release rate on the insulator surface, these data can be used to determine the heat source term in the thermal conduction model, that is, the term that describes the energy input system. Therefore, the electromagnetic field data obtained in step S21 is used as input, and the temperature field distribution data of each part of the insulator string is calculated by the thermal conduction model. The thermal conduction model is constructed based on the heat conduction equation, which describes the process of heat transfer inside an object. By applying the heat conduction equation and boundary conditions, the temperature distribution inside the insulator string can be calculated. The specific calculation formula of the heat conduction equation is as follows: Where T is the temperature field, K is the thermal conductivity, t is the time, ▽ 2 is the Laplace operator, which represents the gradient of the temperature field.
[0047] Step S3, constructing a pollution degradation model according to the surface pollution leakage current or through-leakage current, voltage, magnetic field data and temperature field distribution data of each part of the insulator string, and obtaining the temperature corresponding to the surface pollution leakage current or through-leakage current generated under different pollution degradation conditions;
[0048] In step S3, a pollution degradation model is constructed based on the surface pollution leakage current or through-leakage current, voltage, magnetic field data, and temperature field distribution data of each part of the insulator string, so as to predict the temperature corresponding to the surface pollution leakage current or through-leakage current generated under different pollution degradation conditions. Specifically, a pre-determined mathematical model is used to describe the relationship between the pollution degradation degree and the temperature. In one or more embodiments, refer to Figure 3 As shown, the Newton interpolation polynomial model is used for fitting. The model fits a polynomial function on the known pollution degradation degree and temperature data points through the polynomial interpolation method, so as to predict the pollution degradation degree at a given temperature.
[0049] N n (X) = f(X0) + (X-X0) f[X0,X1]
[0050] +(X-X0)(X-X1)f[X0,X1,X2]+……
[0051] +(X-X0)(X-X1)…(XX n-1 )f[X0,X1,…,X n ]
[0052] Where N n (X) is called the nth-order Newton interpolation polynomial.
[0053] The form f[X0,X1], f[X0,X1,X2], etc. is called the order difference quotient, which is defined as:
[0054] (called the zero-order difference quotient)
[0055] called the first-order difference quotient)
[0056] By analogy, the k-order difference quotient is:
[0057]
[0058] When solving the Newton interpolation polynomial, this embodiment adopts the form of a difference quotient table, see Figure 4 , different degrees of pollution degradation are taken as X variables, and the corresponding temperature is taken as the dependent variable f[X]. Then, the difference quotient is calculated using the formula defined above and filled in the table. Finally, based on the data in the difference quotient table, the final polynomial model can be obtained by applying the formula of Newton interpolation polynomial. The degree of pollution degradation can be predicted using the determined Newton interpolation polynomial model. According to the degree of pollution degradation at different temperatures, the degree can be divided so that the need for regular cleaning or replacement of insulator strings can be clearly understood at different degrees of pollution degradation.
[0059] Step S4, determining the tolerance range of the flexible temperature sensor to temperature, voltage, current and magnetic field according to the output result of the insulator string electrothermal coupling model, so as to guide the arrangement of the flexible temperature sensor.
[0060] In step S4, the tolerance range of the flexible temperature sensor to temperature, voltage, current and magnetic field is determined according to the output result of the electrothermal coupling model of the insulator string, so as to arrange the flexible temperature sensor. Specifically, the upper limits of the temperature, voltage, current and magnetic field of the abnormal hot spot obtained by the electrothermal coupling model are first used to determine the various parameter ranges that the flexible temperature sensor needs to tolerate. The determination of these parameter ranges is based on various abnormal conditions that may occur in the insulator string under different working conditions, ensuring that the flexible temperature sensor can work normally under these conditions and provide accurate monitoring data; secondly, according to the temperature amplitude, gradient and change rate factors, the response range, resolution and response rate parameters of the flexible temperature sensor are further determined. The determination of these parameters is to ensure that the flexible temperature sensor can respond quickly and accurately to the changes in the temperature of the insulator string and provide high-quality monitoring data. The computer automatically calculates the optimal layout position and parameter settings of the flexible temperature sensor according to the pre-set algorithm and conditions, and conveys this information to the relevant equipment or system, so that it automatically completes the layout of the sensor, for example, by controlling a robotic arm or other automated equipment, which will not be described in detail here. In this embodiment, the heating condition of the insulator string is converted into an electrical signal for processing, and the temperature, voltage, current and magnetic field information of the insulator string are collected in real time using a flexible temperature sensor. By analyzing and processing this information, real-time and accurate detection of the abnormal index of the insulator string can be achieved, so as to timely discover and deal with potential problems and ensure the safe and stable operation of the transmission line.
[0061] Step S5, constructing an insulator string variation detection and evaluation model for evaluating the degree of variation of pollution degradation of the insulator string. The insulator string variation detection and evaluation model combines the temperature of the flexible sensor with the pollution degradation model and is trained through a grey prediction model.
[0062] Specifically, in step S5, an insulator string variation detection and evaluation model is constructed to evaluate the degree of variation of the pollution degradation of the insulator string. The establishment of this model involves the combination of temperature data of the flexible sensor, the pollution degradation model and the gray prediction model, and training is performed through the gray prediction model. In this embodiment, the temperature data of the insulator string is obtained by using a flexible sensor. These data are collected in real time and can accurately reflect the temperature changes of the insulator string during operation. Next, the pollution degradation model is used, which is constructed in step S3 to describe the temperature conditions corresponding to the surface pollution leakage current or the through leakage current generated under different pollution degradation conditions. The pollution degradation degree is corresponded to the data of the temperature sensor, so as to evaluate the temperature change law of the insulator string under different pollution degradation degrees, and finally the gray prediction model is used to train the insulator string variation detection and evaluation model. The temperature data obtained by the flexible sensor is combined with the predicted temperature data obtained by the pollution degradation model using the grey prediction model. Specifically, the temperature, pollution degradation degree and other information in the experimental data are used as input, and the predicted temperature is used as output. The grey prediction model is trained to fit the experimental data and predict future temperature changes. Finally, the real-time temperature data collected by the flexible sensor is compared with the prediction results of the grey prediction model to evaluate the pollution degradation degree of the insulator string, thereby establishing an insulator string abnormality detection and evaluation model. The model realizes real-time monitoring and evaluation of the insulator string status, including timely detection of abnormal conditions and accurate evaluation of pollution degradation conditions of different degrees, providing a scientific basis for maintenance and management. Through automated monitoring and evaluation, the detection efficiency and accuracy are greatly improved, the labor cost and inspection cycle are reduced, and intelligent and scientific status diagnosis is realized, providing reliable support for the safe and stable operation of the power transmission system.
[0063] Based on the description of the above-mentioned transmission line insulator string abnormality detection and evaluation method embodiment, the present application embodiment also discloses a transmission line insulator string abnormality detection and evaluation system, and the transmission line insulator string abnormality detection and evaluation system can be a computer program (including program code) for running the above-mentioned transmission line insulator string abnormality detection and evaluation method. Figure 6 As shown in the figure, the transmission line insulator string abnormality detection and evaluation system can run the following modules:
[0064] An acquisition module 110 is used to build an insulator heating test platform and obtain pollution degradation data of insulator strings under different pollution degradation conditions;
[0065] The electrothermal coupling module 120 is used to input the pollution degradation data of the insulator string into the electrothermal coupling model of the insulator string to obtain the pollution leakage current or through-leakage current, voltage, magnetic field data of the insulator surface and the temperature field distribution data of each part of the insulator string;
[0066] The pollution degradation module 130 is used to construct a pollution degradation model based on the surface pollution leakage current or the through leakage current, voltage, magnetic field data and the temperature field distribution data of each part of the insulator string, and obtain the temperature corresponding to the surface pollution leakage current or the through leakage current generated under different pollution degradation conditions;
[0067] The arrangement guidance module 140 is used to determine the tolerance range of the flexible temperature sensor to temperature, voltage, current and magnetic field according to the output result of the insulator string electrothermal coupling model, so as to guide the arrangement of the flexible temperature sensor.
[0068] The insulator string variation detection and evaluation module 150 is used to construct an insulator string variation detection and evaluation model, which is used to evaluate the degree of variation of the pollution degradation of the insulator string. The insulator string variation detection and evaluation model combines the temperature of the flexible sensor with the pollution degradation model and is trained through a grey prediction model.
[0069] The pollution degradation model is constructed by fitting the Newton interpolation polynomial model. The insulator string electrothermal coupling model includes an electromagnetic field model and a heat conduction model. The electromagnetic field model is used to obtain surface pollution leakage current or through-leakage current voltage data, and the heat conduction model is used to obtain temperature field distribution data of each part of the insulator string.
[0070] The above is only a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the form disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be modified within the scope of the concept described herein through the above teachings or the technology or knowledge of the relevant field. The changes and modifications made by those skilled in the art shall not deviate from the spirit and scope of the present invention, and shall be within the scope of protection of the claims attached to the present invention.
Claims
1. A method for detecting and evaluating abnormal changes in insulator strings of transmission lines, characterized in that: The following steps are involved: S1, building an insulator heating test platform to obtain pollution degradation data of insulator strings under different pollution degradation conditions, wherein the pollution degradation data includes the pollution degree of the insulator surface and environmental parameters, wherein the environmental parameters include temperature and humidity; S2, inputting the pollution degradation data of the insulator string into the electrothermal coupling model of the insulator string to obtain the pollution leakage current or through-leakage current, voltage, magnetic field data of the insulator surface and the temperature field distribution data of each part of the insulator string; S3, constructing a pollution degradation model based on the surface pollution leakage current or through-leakage current, voltage, magnetic field data and temperature field distribution data of each part of the insulator string, and obtaining the temperature corresponding to the surface pollution leakage current or through-leakage current generated under different pollution degradation conditions; S4, determining the tolerance range of the flexible temperature sensor to temperature, voltage, current and magnetic field according to the output result of the insulator string electrothermal coupling model, so as to guide the arrangement of the flexible temperature sensor; S5, constructing an insulator string variation detection and evaluation model for evaluating the degree of variation of pollution degradation of the insulator string, wherein the insulator string variation detection and evaluation model combines the temperature of the flexible temperature sensor with the pollution degradation model and is trained through a grey prediction model.
2. A method for detecting and evaluating abnormal changes in insulator strings of transmission lines according to claim 1, characterized in that: The insulator string electrothermal coupling model includes an electromagnetic field model and a heat conduction model. The electromagnetic field model is used to obtain the surface contamination leakage current or through-leakage current, voltage, and magnetic field data of the insulator. The heat conduction model is used to obtain the temperature field distribution data of each part of the insulator string. The specific steps are as follows: S21, inputting the pollution degradation data of the insulator string into the electromagnetic field model, thereby obtaining the pollution leakage current or through-leakage current, voltage, and magnetic field data of the insulator surface; S22, inputting the insulator surface contamination leakage current or through-leakage current, voltage, and magnetic field data into the thermal conduction model, thereby obtaining the temperature field distribution data of each part of the insulator string.
3. A method for detecting and evaluating abnormal changes in insulator strings of transmission lines according to claim 2, characterized in that: The electromagnetic field model is constructed according to Maxwell's equations, and the heat conduction model is constructed according to the heat conduction equation.
4. A method for detecting and evaluating abnormal changes in insulator strings of transmission lines according to claim 3, characterized in that: The specific calculation formula of the Maxwell equations is as follows: where D is The electric displacement vector, Q0 is the amount of free charge passing through the closed surface S, E is the electric field intensity, B is the magnetic induction intensity, dl is the tiny loop element, B is the magnetic induction intensity vector, dS is the infinitesimal area vector of the closed surface, H is the magnetic field intensity, j c is the conduction current density, The rate of change of the electric displacement vector with time.
5. A method for detecting and evaluating abnormal changes in insulator strings of power transmission lines according to claim 3, characterized in that: The specific calculation formula of the heat conduction equation is as follows: Where T is the temperature field, K is the thermal conductivity, and t is the time. is the Laplace operator, which represents the gradient of the temperature field.
6. A method for detecting and evaluating abnormal changes in insulator strings of power transmission lines according to claim 1, characterized in that: The pollution degradation model is constructed by fitting a Newton interpolation polynomial model.
7. A method for detecting and evaluating abnormal changes in insulator strings of power transmission lines according to claim 1, characterized in that: The guidance for arranging the flexible temperature sensor also needs to determine the response range, resolution and response rate parameters of the flexible temperature sensor according to the temperature amplitude, gradient and change rate factors.
8. A transmission line insulator string abnormality detection and evaluation system, characterized in that: The system comprises: An acquisition module is used to build an insulator heating test platform to obtain pollution degradation data of insulator strings under different pollution degradation conditions, wherein the pollution degradation data includes the pollution degree of the insulator surface and environmental parameters, wherein the environmental parameters include temperature and humidity; The electrothermal coupling module is used to input the pollution degradation data of the insulator string into the electrothermal coupling model of the insulator string to obtain the pollution leakage current or through-leakage current, voltage, magnetic field data of the insulator surface and the temperature field distribution data of each part of the insulator string; The pollution degradation module is used to construct a pollution degradation model based on the surface pollution leakage current or through-leakage current, voltage, magnetic field data and temperature field distribution data of each part of the insulator string, and obtain the temperature corresponding to the surface pollution leakage current or through-leakage current generated under different pollution degradation conditions; A layout guidance module is used to determine the tolerance range of the flexible temperature sensor to temperature, voltage, current and magnetic field according to the output result of the insulator string electrothermal coupling model, so as to guide the layout of the flexible temperature sensor; The insulator string variation detection and evaluation module is used to construct an insulator string variation detection and evaluation model, which is used to evaluate the degree of variation of the pollution degradation of the insulator string. The insulator string variation detection and evaluation model combines the temperature of the flexible temperature sensor with the pollution degradation model and is trained through a grey prediction model.
9. A transmission line insulator string abnormality detection and evaluation system according to claim 8, characterized in that: The pollution degradation model is constructed by fitting a Newton interpolation polynomial model.
10. A transmission line insulator string abnormality detection and evaluation system according to claim 8, characterized in that: The electrothermal coupling model of the insulator string includes an electromagnetic field model and a heat conduction model. The electromagnetic field model is used to obtain the surface contamination leakage current or through-leakage current, voltage, and magnetic field data of the insulator, and the heat conduction model is used to obtain the temperature field distribution data of each part of the insulator string.