Power transmission line tower grounding resistance monitoring system and use method

Abstract

The invention relates to the technical field of grounding resistance detection, in particular to a power transmission line tower grounding resistance monitoring system and a use method, and the system comprises a signal collection and correction module which collects and updates various parameters of each tower in real time, builds a mathematical model of environment parameters and grounding resistance values, and obtains the real-time environment parameters and the grounding resistance values after obtaining the real-time environment parameters; automatically correcting the measured resistance value by using the mathematical model; the fault early warning module is used for collecting historical monitoring data and calculating an abnormal risk probability in combination with real-time abnormal data; the fault positioning module is used for realizing accurate positioning of a fault tower through a time difference positioning method; and the remote control module is linked with the meteorological early warning platform, starts high-frequency monitoring before thunderstorm, and dynamically adjusts a ground resistance threshold value. The measurement value is automatically corrected through the linear regression model, interference of environmental fluctuation on resistance measurement can be effectively eliminated, and errors of traditional static measurement are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of grounding resistance monitoring, and in particular to a transmission line tower grounding resistance monitoring system and a use method thereof. Background Art

[0002] The stable operation of the power system is crucial to the development of modern society. As the key channel for power transmission, the reliability and safety of transmission lines directly affect the quality of power supply. Grounding resistance is a key indicator for measuring the performance of the grounding system. Its size is directly related to the dispersion effect of the tower in the event of lightning strikes, fault currents, etc., which in turn affects the safe and stable operation of the transmission lines and the safety of surrounding personnel and equipment.

[0003] Existing ground resistance measurements are mostly completed using the three-pole method or the clamp meter method. Both methods are offline measurement methods, requiring power personnel to measure each tower on site, which is labor-intensive and inefficient. In addition, personnel cannot immediately discover situations where the ground resistance exceeds the standard due to rust or human damage to the grounding down conductor. In addition, changes in environmental factors may cause large errors in the measurement results, which cannot accurately reflect the true situation of the ground resistance. The present invention uses lightning current as the current passing through the ground resistance for real-time monitoring, so as to promptly detect abnormal ground resistance of the tower. It has high efficiency and strong timeliness, can effectively solve the problems existing in the current manual working method, and reduce human labor intensity and labor costs. Summary of the Invention

[0004] The present invention aims to solve the technical problems existing in the prior art and provides a transmission line tower grounding resistance monitoring system and a use method thereof.

[0005] The present invention solves the above-mentioned technical problem with the following technical solution: A transmission line tower grounding resistance monitoring system comprising:

[0006] Signal acquisition and correction module: This module collects and updates the grounding resistance, soil parameters, and current parameters of each tower in real time, establishes a mathematical model of environmental parameters and grounding resistance, and automatically corrects the measured resistance value using the mathematical model after obtaining the real-time environmental parameters.

[0007] Fault warning module: collects historical monitoring data, combines it with real-time abnormal data, and calculates the abnormal risk probability based on the number of abnormalities and the total amount of data;

[0008] Fault location module: When abnormal ground resistance is detected in a certain area, the fault tower can be accurately located through the time difference positioning method;

[0009] Remote control module: Based on the prediction results of the fault warning module, the monitoring platform remotely adjusts the monitoring parameters, links with the meteorological warning platform, starts high-frequency monitoring before thunderstorms, and dynamically adjusts the ground resistance threshold.

[0010] In a preferred embodiment, the signal acquisition and correction module regularly collects soil parameters and ground resistance values through soil parameter sensors, ground resistance measurement sensors, and current sensors. The soil parameters include soil moisture, temperature, and conductivity. When a lightning strike occurs, the current sensor responds quickly and accurately collects the magnitude of the lightning strike current. The data collected by the soil parameter sensors, ground resistance sensors, and current sensors are preprocessed, including signal amplification, filtering, and denoising. The preprocessed data is packaged and transmitted to a data processing center. The soil moisture, temperature, conductivity, and ground resistance values of several tower measurement points in different seasons and weather conditions are obtained, and a linear regression algorithm is used to establish a mathematical model between the environmental parameters and the ground resistance value.

[0011] Assume we have n training data samples, and for the i-th sample, the soil moisture is recorded as , the temperature is recorded as , the conductivity is recorded as , the actual measured value of the corresponding target variable ground resistance is recorded as , using the linear regression method, using the training set data to determine the linear relationship between the feature variables and the target variable, the calculation formula of the linear regression model is as follows:

[0012]

[0013] in, represents the model's predicted value for the i-th sample, represents the intercept, 、 、 is the coefficient of the corresponding characteristic variable, based on the calculation of the linear regression model, in order to find a set of optimal 、 、 、 , so that the predicted value With actual value The degree of fit becomes higher, and the least squares method is used to solve it, that is, to minimize the loss function. The specific calculation formula is as follows:

[0014]

[0015] Among them, by respectively analyzing the loss function 、 、 、 By finding the partial derivatives and setting them to 0, we can get a set of equations. Solving this set of equations can give us the optimal parameters. 、 、 、 The trained linear regression model is evaluated using the test set data. The performance of the model is judged by calculating the evaluation indicators, including the mean square error and the coefficient of determination. The mean square error measures the average square of the error between the model prediction value and the actual value, and the coefficient of determination is used to reflect the degree of fit of the model to the data. The data processing center receives soil moisture, temperature, conductivity data and ground resistance measurement data from sensors in real time, and calls the established and optimized linear regression model. The model contains the determined coefficients 、 、 、 These coefficients reflect the relationship between soil moisture, temperature, conductivity and ground resistance, and the soil moisture received in real time ,temperature , conductivity Substitute into the mathematical model Calculate the impact of environmental factors on grounding resistance , using the measured ground resistance value Subtract the calculated environmental factor impact value , get the corrected ground resistance value , the corrected ground resistance value Stored in the database.

[0016] In a preferred embodiment, the fault warning module collects historical monitoring data over a period of time, combines it with abnormal data monitored in real time, and calculates the ground resistance value after correction. When the value exceeds the mean value of historical data plus 3 times the standard deviation and is lower than the mean value of historical data minus 3 times the standard deviation, it is marked as abnormal data and transmitted to the data processing center. Fluctuation, count the number of abnormal data in historical data , calculate the total number of historical data points N, then the probability of abnormal risk occurrence is , arrange the historical ground resistance data in chronological order, and let the time series be The corresponding grounding resistance value is , using a linear regression model To fit the relationship between the ground resistance value and time, a represents the intercept, that is, the estimated value of the ground resistance when time t=0, and b represents the slope, which reflects the trend of the ground resistance value changing with time. The coefficients a and b are determined by the least squares method. The goal of the least squares method is to minimize the residual sum of squares. , calculate the partial derivatives of a and b respectively and set them to 0. The specific formula is as follows:

[0017]

[0018] Solving the above formula we can get:

[0019]

[0020]

[0021] in, represents the i-th time point in the time series, Indicates the corresponding time point The grounding resistance value is shown in Figure 2. a and b represent the coefficients in the linear regression model. S represents the residual sum of squares, which is an indicator used to evaluate the goodness of fit of the linear regression model. The degradation trend of the grounding resistance is judged based on the slope b. If b>0, it means that the grounding resistance has an upward trend and may have a degradation trend. If b<0, it is necessary to check for abnormal measurement errors. If b≈0, it means that the grounding resistance is relatively stable.

[0022] In a preferred embodiment, the fault location module collects the ground resistance data and lightning current signal through the ground resistance measurement sensor and current sensor of the signal acquisition and correction module. When there is an abnormality in the ground resistance of a certain tower, the positioning process is triggered and the time difference of the abnormal signal reaching the adjacent tower sensor is recorded by the data processing center. , combined with the signal propagation speed in air , calculate the distance difference between the abnormal signal source and each tower. The specific calculation formula is as follows:

[0023]

[0024] in, Represents the distance difference. Taking the adjacent towers as the focus, the distance difference is used to construct the hyperbola equation. Let the two focal towers be P1 and P2, and the distance difference is , then the hyperbolic equations of the two focal towers are:

[0025]

[0026] in,( )、( ) represents the tower coordinates, (x, y) represents the coordinates of the fault point, and the final coordinates of the fault tower are determined by the time difference positioning results and marked on the GIS map.

[0027] In a preferred embodiment, the remote control module obtains prediction results from the fault warning module and the fault location module. If a high probability of fault risk is detected, a parameter adjustment process is triggered. After the parameter adjustment process is triggered, the sampling interval of the grounding resistance and soil parameters is shortened from the conventional value to the high frequency, and the monitoring coverage of the adjacent towers around the abnormal tower is expanded. Instructions are sent to the sensor through wireless transmission to update its sampling frequency and data transmission interval parameters. Meteorological warning information is obtained through the API interface, focusing on the issuance time and affected area of the thunderstorm warning. When the meteorological warning platform issues a thunderstorm warning and covers the monitoring area, high-frequency monitoring is automatically started, and the threshold is dynamically adjusted according to the grounding resistance change law during historical thunderstorms.

[0028] An embodiment of the present invention further provides a method for using a transmission line tower grounding resistance monitoring system, comprising the following steps:

[0029] S101, by collecting and updating the ground resistance value, soil parameters and current parameters of each tower in real time, a mathematical model of environmental parameters and ground resistance value is established, and after obtaining the real-time environmental parameters, the measured resistance value is automatically corrected using the mathematical model;

[0030] S102. Collect historical monitoring data, combine it with real-time abnormal data, and calculate the abnormal risk probability based on the number of abnormalities and the total number of data;

[0031] S103. When abnormal ground resistance is detected in a certain area, the fault tower is accurately located by using a time difference positioning method;

[0032] S104. Based on the prediction results of the fault warning module, the monitoring platform remotely adjusts the monitoring parameters, links with the meteorological warning platform, starts high-frequency monitoring before the thunderstorm, and dynamically adjusts the ground resistance threshold.

[0033] The beneficial effects of the present invention are as follows: the present invention collects grounding resistance, soil moisture, temperature, conductivity and current parameters in real time, and automatically corrects the measured values through a linear regression model, which can effectively eliminate the interference of environmental fluctuations on resistance measurement, reduce the error of traditional static measurement, and ensure that the data truly reflects the state of grounding resistance. By combining historical data with real-time abnormal data, the abnormal risk probability and the grounding resistance degradation trend are calculated to quantitatively evaluate the fault risk. By using time differential positioning technology, when the grounding resistance is abnormal, the time difference between the signals reaching different sensors, combined with the hyperbola positioning algorithm, can be used to reduce the tower positioning error. Compared with manual inspections, the efficiency of fault positioning is improved, the time of power outage maintenance is shortened, and it is connected to the meteorological platform to automatically start high-frequency monitoring before thunderstorms and dynamically lower the grounding resistance threshold to improve the fault capture sensitivity in extreme weather. By remotely modifying sensor parameters, there is no need for manual on-site debugging, which reduces operation and maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 is a flow chart of the method of the present invention;

[0035] Figure 2 This is a system block diagram of the present invention. DETAILED DESCRIPTION

[0036] 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 embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0037] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the described features. In the description of this application, "plurality" means two or more, unless otherwise specifically specified.

[0038] In the description of this application, the term "for example" is used to mean "used as an example, illustration or explanation". Any embodiment described as "for example" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any person skilled in the art to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art will recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in this application.

[0039] like Figure 1 This embodiment provides: a method for using a transmission line tower grounding resistance monitoring system, comprising the following steps:

[0040] S101, by collecting and updating the ground resistance value, soil parameters and current parameters of each tower in real time, a mathematical model of environmental parameters and ground resistance value is established, and after obtaining the real-time environmental parameters, the measured resistance value is automatically corrected using the mathematical model;

[0041] S102. Collect historical monitoring data, combine it with real-time abnormal data, and calculate the abnormal risk probability based on the number of abnormalities and the total number of data;

[0042] S103. When abnormal ground resistance is detected in a certain area, the fault tower is accurately located by using a time difference positioning method;

[0043] S104. Based on the prediction results of the fault warning module, the monitoring platform remotely adjusts the monitoring parameters, links with the meteorological warning platform, starts high-frequency monitoring before the thunderstorm, and dynamically adjusts the ground resistance threshold.

[0044] like Figure 2 This embodiment provides: a transmission line tower grounding resistance monitoring system, comprising:

[0045] Signal acquisition and correction module: This module collects and updates the grounding resistance, soil parameters, and current parameters of each tower in real time, establishes a mathematical model of environmental parameters and grounding resistance, and automatically corrects the measured resistance value using the mathematical model after obtaining the real-time environmental parameters.

[0046] In this embodiment, the signal acquisition and correction module needs to be specifically explained. The signal acquisition and correction module regularly collects soil parameters and ground resistance values through soil parameter sensors, ground resistance measurement sensors, and current sensors. Soil parameters include soil moisture, temperature, and conductivity. When a lightning strike occurs, the current sensor responds quickly and accurately collects the magnitude of the lightning strike current. The data collected by the soil parameter sensor, ground resistance sensor, and current sensor are preprocessed, including signal amplification, filtering, and denoising. The preprocessed data is packaged and transmitted to a data processing center. The soil moisture, temperature, conductivity, and ground resistance values of several tower measurement points in different seasons and weather conditions are obtained, and a linear regression algorithm is used to establish a mathematical model between the environmental parameters and the ground resistance value.

[0047] Assume we have n training data samples, and for the i-th sample, the soil moisture is recorded as , the temperature is recorded as , the conductivity is recorded as , the actual measured value of the corresponding target variable ground resistance is recorded as , using the linear regression method, using the training set data to determine the linear relationship between the feature variables and the target variable, the calculation formula of the linear regression model is as follows:

[0048]

[0049] in, represents the model's predicted value for the i-th sample, represents the intercept, 、 、 is the coefficient of the corresponding characteristic variable, based on the calculation of the linear regression model, in order to find a set of optimal 、 、 、 , so that the predicted value With actual value The degree of fit becomes higher, and the least squares method is used to solve it, that is, to minimize the loss function. The specific calculation formula is as follows:

[0050]

[0051] Among them, by respectively analyzing the loss function 、 、 、 By finding the partial derivatives and setting them to 0, we can get a set of equations. Solving this set of equations can give us the optimal parameters. 、 、 、 The trained linear regression model is evaluated using the test set data. The performance of the model is judged by calculating the evaluation indicators, including the mean square error and the coefficient of determination. The mean square error measures the average square of the error between the model's predicted value and the actual value. The specific calculation formula is as follows:

[0052]

[0053] in, represents the mean square error, m represents the number of test set samples, represents the actual ground resistance value of the i-th sample in the test set, It represents the predicted value of the ground resistance of the i-th test sample by the model. The value of the mean square error is small, which means that the predicted value of the model is close to the actual value and the prediction effect of the model is good. The degree of fit of the model to the data is reflected by calculating the coefficient of determination. The specific calculation formula is as follows:

[0054]

[0055] in, , represents the average value of the actual ground resistance of all samples in the test set, represents the coefficient of determination, The value of is close to 1, indicating that the model fits the test set data well. The value of is close to 0, which means that the model fitting effect is poor and the model has weak ability to explain the changes in ground resistance;

[0056] The data processing center receives soil moisture, temperature, conductivity data and ground resistance measurement data from sensors in real time, and calls the established and optimized linear regression model, which contains the determined coefficients. 、 、 、 These coefficients reflect the relationship between soil moisture, temperature, conductivity and ground resistance, and the soil moisture received in real time ,temperature , conductivity Substitute into the mathematical model Calculate the impact of environmental factors on grounding resistance It should be noted that this is not considered ,because It is a reference value and does not represent the influence of environmental factors. The ground resistance value obtained by measurement is Subtract the calculated environmental factor impact value , get the corrected ground resistance value , the corrected ground resistance value Stored in the database for subsequent analysis and judgment.

[0057] It should be noted that the collection cycle is set for the soil parameter sensor, for example, data is collected every 15 minutes to ensure that changes in soil environmental parameters can be tracked in a timely manner. The ground resistance value can be measured once an hour. The cycle can be appropriately shortened in the season with frequent lightning strikes. The current sensor should be on standby at all times under normal circumstances. Once a lightning current signal is detected, the size and waveform data of the lightning current are immediately collected at a high-frequency sampling rate until the current signal disappears. When pre-processing the data collected by the soil parameter sensor, ground resistance sensor and current sensor, the technologies used include: signal amplification, filtering and denoising processing, which belong to the existing technology and will not be described in detail here.

[0058] Fault warning module: collects historical monitoring data, combines it with real-time abnormal data, and calculates the abnormal risk probability based on the number of abnormalities and the total amount of data;

[0059] In this embodiment, it is necessary to specifically explain the fault warning module, which collects historical monitoring data over a period of time and combines it with the abnormal data monitored in real time. When the value exceeds the mean value of historical data plus 3 times the standard deviation and is lower than the mean value of historical data minus 3 times the standard deviation, it is marked as abnormal data and transmitted to the data processing center. Fluctuation, count the number of abnormal data in historical data , calculate the total number of historical data points N, then the probability of abnormal risk occurrence is , arrange the historical ground resistance data in chronological order, and let the time series be The corresponding grounding resistance value is , using a linear regression model To fit the relationship between the ground resistance value and time, a represents the intercept, that is, the estimated value of the ground resistance when time t=0, and b represents the slope, which reflects the trend of the ground resistance value changing with time. The coefficients a and b are determined by the least squares method. The goal of the least squares method is to minimize the residual sum of squares. , calculate the partial derivatives of a and b respectively and set them to 0. The specific formula is as follows:

[0060]

[0061] Solving the above formula we can get:

[0062]

[0063]

[0064] in, represents the i-th time point in the time series, Indicates the corresponding time point The grounding resistance value is shown in Figure 2. a and b represent the coefficients in the linear regression model. S represents the residual sum of squares, which is an indicator used to evaluate the goodness of fit of the linear regression model. The degradation trend of the grounding resistance is judged based on the slope b. If b>0, it means that the grounding resistance has an upward trend and may have a degradation trend. If b<0, it is necessary to check for abnormal measurement errors. If b≈0, it means that the grounding resistance is relatively stable.

[0065] It should be noted that the historical monitoring data of ground resistance over a period of time is collected from the database. , clean the historical data, remove the data that exceeds the reasonable range, and calculate the mean of the historical data for the time period with more missing values and standard deviation :

[0066]

[0067]

[0068] Fault location module: When abnormal ground resistance is detected in a certain area, the fault tower can be accurately located through the time difference positioning method;

[0069] In this embodiment, it is necessary to specifically explain the fault location module. The fault location module collects the ground resistance data and lightning current signal through the ground resistance measurement sensor and current sensor of the signal acquisition and correction module. When there is an abnormality in the ground resistance of a certain tower, the positioning process is triggered, and the time difference of the abnormal signal reaching the adjacent tower sensor is recorded by the data processing center. , combined with the signal propagation speed in air , calculate the distance difference between the abnormal signal source and each tower. The specific calculation formula is as follows:

[0070]

[0071] in, Represents the distance difference. Taking the adjacent towers as the focus, the distance difference is used to construct the hyperbola equation. Let the two focal towers be P1 and P2, and the distance difference is , then the hyperbolic equations of the two focal towers are:

[0072]

[0073] in,( )、( ) represents the tower coordinates, (x, y) represents the coordinates of the fault point, and the final coordinates of the fault tower are determined by the time difference positioning results and marked on the GIS map.

[0074] It should be noted that the abnormal situation of the tower grounding resistance is obtained through the abnormal data of the fault warning module.

[0075] Remote control module: Based on the prediction results of the fault warning module, the monitoring platform remotely adjusts monitoring parameters, links with the meteorological warning platform, initiates high-frequency monitoring before thunderstorms, and dynamically adjusts the ground resistance threshold;

[0076] In this embodiment, what needs to be specifically explained is the remote control module. The remote control module obtains prediction results from the fault warning module and the fault location module. If it is monitored that the probability of fault risk is high, the parameter adjustment process is triggered. After the parameter adjustment process is triggered, the sampling interval of the grounding resistance and soil parameters is shortened from the conventional value to the high frequency, and the monitoring coverage of the adjacent towers around the abnormal tower is expanded. Instructions are sent to the sensor through wireless transmission to update its sampling frequency and data transmission interval parameters. Meteorological warning information is obtained through the API interface, focusing on the issuance time and affected area of the thunderstorm warning. When the meteorological warning platform issues a thunderstorm warning and covers the monitoring area, high-frequency monitoring is automatically started, and the threshold is dynamically adjusted according to the grounding resistance change law during historical thunderstorms.

[0077] It should be noted that, in the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0078] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0079] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, 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 computer, or other programmable data processing device to produce 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 flowcharts and / or block diagrams. Figure 1a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0080] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0081] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0082] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0083] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A transmission line tower grounding resistance monitoring system, characterized in that: include: Signal acquisition and correction module: This module collects and updates the grounding resistance, soil parameters, and current parameters of each tower in real time, establishes a mathematical model of environmental parameters and grounding resistance, and automatically corrects the measured resistance value using the mathematical model after obtaining the real-time environmental parameters. Fault warning module: collects historical monitoring data, combines it with real-time abnormal data, and calculates the abnormal risk probability based on the number of abnormalities and the total amount of data; Fault location module: When abnormal ground resistance is detected in a certain area, the fault tower can be accurately located through the time difference positioning method; Remote control module: Based on the prediction results of the fault warning module, the monitoring platform remotely adjusts the monitoring parameters, links with the meteorological warning platform, starts high-frequency monitoring before thunderstorms, and dynamically adjusts the ground resistance threshold.

2. A transmission line tower grounding resistance monitoring system according to claim 1, characterized in that: The signal acquisition and correction module regularly collects soil parameters and ground resistance values through soil parameter sensors, ground resistance measurement sensors and current sensors. Soil parameters include soil moisture, temperature and conductivity. When a lightning strike occurs, the current sensor accurately collects the magnitude of the lightning current, and pre-processes the data collected by the soil parameter sensor, ground resistance sensor and current sensor, including signal amplification, filtering and denoising. The pre-processed data is packaged and transmitted to the data processing center. The soil moisture, temperature, conductivity and ground resistance values of several tower measurement points in different seasons and weather conditions are obtained, and a linear regression algorithm is used to establish a mathematical model between environmental parameters and ground resistance values. There are n training data samples. For the i-th sample, the soil moisture is recorded as , the temperature is recorded as , the conductivity is recorded as , the actual measured value of the corresponding target variable ground resistance is recorded as .

3. A transmission line tower grounding resistance monitoring system according to claim 2, characterized in that: The linear regression algorithm establishes a mathematical model between environmental parameters and ground resistance by using the linear regression method and using the training set data to determine the linear relationship between the characteristic variables and the target variable. The calculation formula of the linear regression model is as follows: in, represents the model's predicted value for the i-th sample, represents the intercept, 、 、 is the coefficient of the corresponding characteristic variable, based on the calculation of the linear regression model, in order to find a set of optimal 、 、 、 , so that the predicted value With actual value The degree of fit becomes higher, and the least squares method is used to solve it.

4. A transmission line tower grounding resistance monitoring system according to claim 3, characterized in that: The least squares method is solved by respectively calculating the loss function with respect to 、 、 、 By finding the partial derivatives and setting them to 0, we can get a set of equations. Solving this set of equations can get the optimal parameters. 、 、 、 The trained linear regression model is evaluated using the test set data, and the performance of the model is judged by calculating the evaluation indicators, including the mean square error and the coefficient of determination. The data processing center receives soil moisture, temperature, conductivity data and ground resistance measurement data from the sensor in real time, and calls the established and optimized linear regression model, which contains the determined coefficients. 、 、 、 , the soil moisture received in real time ,temperature , conductivity Substitute into the mathematical model Calculate the impact of environmental factors on grounding resistance , using the measured ground resistance value Subtract the calculated environmental factor impact value , get the corrected ground resistance value , the corrected ground resistance value Stored in the database.

5. A transmission line tower grounding resistance monitoring system according to claim 1, characterized in that: The fault warning module collects historical monitoring data and combines it with the abnormal data of real-time monitoring. When the corrected ground resistance value When the value exceeds the mean value of historical data plus 3 times the standard deviation and is lower than the mean value of historical data minus 3 times the standard deviation, it is marked as abnormal data and transmitted to the data processing center. Fluctuation, count the number of abnormal data in historical data , calculate the total number of historical data points N, then the probability of abnormal risk occurrence is , arrange the historical ground resistance data in chronological order, and let the time series be The corresponding grounding resistance value is , using a linear regression model To fit the relationship between the ground resistance value and time, a represents the intercept and b represents the slope. The coefficients a and b are determined by the least squares method. The degradation trend of the ground resistance is judged according to the slope b. If b>0, it means that the ground resistance has an upward trend and may have a degradation trend. If b<0, it is necessary to check for abnormal measurement errors. If b≈0, it means that the ground resistance is relatively stable.

6. A transmission line tower grounding resistance monitoring system according to claim 1, characterized in that: The fault location module collects the ground resistance data and lightning current signal through the ground resistance measurement sensor and current sensor of the signal acquisition and correction module. When there is an abnormality in the ground resistance of a tower, the location process is triggered and the time difference of the abnormal signal reaching the adjacent tower sensor is recorded by the data processing center. , combined with the signal propagation speed in air , calculate the distance difference between the abnormal signal source and each tower. The specific calculation formula is as follows: in, Represents the distance difference. Taking the adjacent towers as the focus, the distance difference is used to construct the hyperbola equation. Let the two focal towers be P1 and P2, and the distance difference is , then the hyperbola equations of the two focal towers are: in,( )、( ) represents the tower coordinates, (x, y) represents the coordinates of the fault point, and the final coordinates of the fault tower are determined by the time difference positioning results and marked on the GIS map.

7. A transmission line tower grounding resistance monitoring system according to claim 1, characterized in that: The remote control module obtains prediction results from the fault warning module and the fault location module. If a high fault risk probability is detected, a parameter adjustment process is triggered. After the parameter adjustment process is triggered, the sampling interval of the ground resistance and soil parameters is shortened from the conventional value to the high frequency, and the monitoring coverage of the adjacent towers around the abnormal tower is expanded. Instructions are sent to the sensor via wireless transmission to update its sampling frequency and data transmission interval parameters. Meteorological warning information is obtained through the API interface, focusing on the issuance time and affected area of the thunderstorm warning. When the meteorological warning platform issues a thunderstorm warning and covers the monitoring area, high-frequency monitoring is automatically started, and the threshold is dynamically adjusted according to the ground resistance change law during historical thunderstorms.

8. A method for using a transmission line tower grounding resistance monitoring system, applied to a transmission line tower grounding resistance monitoring system according to any one of claims 1 to 7, characterized in that: The following steps are involved: S101, by collecting and updating the ground resistance value, soil parameters and current parameters of each tower in real time, a mathematical model of environmental parameters and ground resistance value is established, and after obtaining the real-time environmental parameters, the measured resistance value is automatically corrected using the mathematical model; S102. Collect historical monitoring data, combine it with real-time abnormal data, and calculate the abnormal risk probability based on the number of abnormalities and the total number of data; S103. When abnormal ground resistance is detected in a certain area, the faulty tower is accurately located by using a time difference positioning method; S104. Based on the prediction results of the fault warning module, the monitoring platform remotely adjusts the monitoring parameters, links with the meteorological warning platform, starts high-frequency monitoring before the thunderstorm, and dynamically adjusts the ground resistance threshold.

Images