Multi-mode insulator state monitoring system

Abstract

The invention discloses a multi-mode insulator state monitoring system, which belongs to the technical field of insulator real-time monitoring, and comprises a system leakage current monitoring sub-module used for monitoring the leakage current of an insulator; the weight monitoring sub-module is used for monitoring the weight of the insulator; the inclination angle monitoring sub-module is used for monitoring the inclination angle of the insulator; the temperature monitoring sub-module is used for monitoring the temperature of the insulator; the main control module is used for performing state evaluation on the insulator according to the leakage current, the weight, the inclination angle and the temperature of the insulator to obtain an insulator state evaluation result; the state monitoring module is used for issuing a state abnormal signal to each sub-module according to an insulator state evaluation result; and each sub-module gives an abnormal alarm according to the abnormal signal issued by the main control module. The system can perform centralized monitoring of various data and risk early warning on the extra-high voltage line insulator, and improves the data monitoring efficiency of the extra-high voltage line insulator.

Description

Technical Field

[0001] The present invention belongs to the technical field of real-time monitoring of insulators, and particularly relates to a multi-modal insulator condition monitoring system. Background Art

[0002] Line insulators are electrical equipment used on transmission lines to connect high-voltage conductors and towers, playing the roles of mechanical connection and electrical insulation. They are mainly used to support high-voltage wires, isolate power lines, and support towers or cable suspension points, enabling the power line to transmit electrical energy without contacting the ground and preventing current from flowing from the power line to the support tower or other conductors. Due to the particularity of ultra-high voltage transmission lines, once the insulators start working, it is basically impossible to replace them. Therefore, the insulation quality of insulators is directly related to the safety and stability of the transmission line. Insulators may experience insulation failure and insulation faults during use due to reasons such as material aging, contamination, and damage, resulting in a deterioration of the safety performance of the power system or accidents. Common insulator insulation faults include: leakage current, flashover, breakdown, damage, etc. AC transmission lines have long transmission distances, large transmission capacities, and cover wide geographical areas. The line insulators are under various harsh operating environments such as wind, rain, snow, fog, ice, lightning, and industrial pollution, and are prone to icing, contamination, aging, etc.

[0003] The detection methods for ultra-high voltage line insulators mostly adopt manual observation methods, and their errors and statistical timeliness are difficult to meet the requirements of online quality inspection and management of insulator manufacturing enterprises. At the same time, the consumption of ultra-high voltage insulators is huge, and it is difficult to obtain all relevant operating parameters. With the development of technology, in addition to manual observation, the current monitoring devices also include on-line monitoring devices for insulator conditions that dynamically monitor leakage current, monitoring devices for the stress state and over-current position heating conditions of strain insulator strings on transmission lines, etc. However, these devices currently still have problems such as single monitoring data, low efficiency, inability to meet the monitoring requirements of complex environments, and inability to be applied to ultra-high voltage lines. Summary of the Invention

[0004] The purpose of the present invention is to provide a multi-modal insulator condition monitoring system, which can perform centralized monitoring of various data on ultra-high voltage line insulators and provide risk warnings, improving the efficiency of data monitoring for ultra-high voltage line insulators.

[0005] To achieve the above purpose, the present invention provides the following technical solutions: A multi-modal insulator condition monitoring system, characterized by comprising: A leakage current monitoring sub-module for monitoring the leakage current of the insulator; A weight monitoring sub-module for monitoring the weight of the insulator; An inclination angle monitoring sub-module for monitoring the inclination angle of the insulator; A temperature monitoring sub-module for monitoring the temperature of the insulator; A main control module for evaluating the status of the insulator based on the leakage current, weight, tilt angle, and temperature of the insulator to obtain the insulator status evaluation result; and for sending a status anomaly signal to each sub-module according to the insulator status evaluation result; Each sub-module issues an anomaly alarm according to the anomaly signal sent by the main control module.

[0006] Furthermore, the status evaluation of the insulator based on the leakage current, weight, tilt angle, and temperature of the insulator includes: Comparing the leakage current of the insulator with a preset leakage current threshold. If the leakage current of the insulator is greater than the preset leakage current threshold, it is determined that the leakage current of the insulator is abnormal; otherwise, it is determined that the leakage current of the insulator is normal; Comparing the weight of the insulator with a preset weight threshold. If the weight of the insulator is greater than the preset weight threshold, it is determined that the weight of the insulator is abnormal; otherwise, it is determined that the weight of the insulator is normal; Comparing the tilt angle of the insulator with a preset tilt angle threshold. If the tilt angle of the insulator is greater than the preset tilt angle threshold, it is determined that the tilt angle of the insulator is abnormal; otherwise, it is determined that the tilt angle of the insulator is normal; Comparing the temperature of the insulator with a preset temperature threshold. If the temperature of the insulator is greater than the preset temperature threshold, it is determined that the temperature of the insulator is abnormal; otherwise, it is determined that the temperature of the insulator is normal.

[0007] Furthermore, sending a status anomaly signal to each sub-module according to the insulator status evaluation result includes: If it is determined that the leakage current of the insulator is abnormal, a leakage current anomaly signal is sent to the leakage current monitoring sub-module; If it is determined that the weight of the insulator is abnormal, a weight anomaly signal is sent to the weight monitoring sub-module; If it is determined that the tilt angle of the insulator is abnormal, a tilt angle anomaly signal is sent to the tilt angle monitoring sub-module; If it is determined that the temperature of the insulator is abnormal, a temperature anomaly signal is sent to the temperature monitoring sub-module.

[0008] Furthermore, the leakage current monitoring sub-module uses a leakage current sensor to monitor the leakage current of the insulator; the leakage current sensor issues a leakage current anomaly alarm according to the leakage current anomaly signal.

[0009] Furthermore, the weight monitoring sub-module uses a tensile sensor to monitor the weight of the insulator; the tensile sensor issues a weight anomaly alarm according to the weight anomaly signal.

[0010] Further, the tilt angle monitoring sub-module uses an angle sensor to monitor the tilt angle of the insulator; the angle sensor issues a tilt angle anomaly alarm according to the tilt angle anomaly signal.

[0011] Further, the temperature monitoring sub-module uses an infrared camera sensor to monitor the temperature of the insulator, and the infrared camera sensor issues a temperature anomaly alarm according to the temperature anomaly signal.

[0012] Further, the measurement ranges and accuracies of the sensors all meet the requirements of the UHV environment.

[0013] Further, the sub-modules and the main control module use the Message Queuing Telemetry Transport (MQTT) protocol for signal transmission.

[0014] Further, the main control module uses RK3588S as the core processor, and the embedded NPU supports hybrid operations.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: The multi-modal insulator condition monitoring system provided by the present invention performs multi-modal implementation monitoring on the insulator through each monitoring sub-module. The main module evaluates the condition of the insulator based on the monitoring data of each sub-module, and issues a condition anomaly signal to each sub-module according to the condition evaluation result, enabling each sub-module to issue corresponding anomaly alarms according to the corresponding condition anomaly signals. It can perform centralized monitoring of various data and risk warning on the insulators of UHV lines, improve the data monitoring efficiency of UHV line insulators, reduce manual inspection errors, avoid human errors and lags, and enhance the accuracy and reliability of insulator condition monitoring. The system has high reliability and can work stably in various complex and harsh operating environments to ensure the safe operation of UHV lines. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a schematic structural diagram of the multi-modal insulator condition monitoring system provided by the embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] The technical solutions of the present application will be further described in detail below in conjunction with the specific embodiments.

[0018] The embodiments of the present application will be described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements with the same or similar functions from beginning to end. The embodiments described below by referring to the drawings are exemplary and are only used to explain the present application and should not be construed as a limitation of the present application. Without conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other.

[0019] An embodiment of the present application provides a multimodal insulator condition monitoring system, including: A leakage current monitoring sub-module for monitoring the leakage current of the insulator; A weight monitoring sub-module for monitoring the weight of the insulator; An inclination angle monitoring sub-module for monitoring the inclination angle of the insulator; A temperature monitoring sub-module for monitoring the temperature of the insulator; A main control module for evaluating the condition of the insulator based on the leakage current, weight, inclination angle, and temperature of the insulator to obtain an insulator condition evaluation result; and for sending a status anomaly signal to each sub-module according to the insulator condition evaluation result; Each sub-module issues an anomaly alarm according to the anomaly signal sent by the main control module.

[0020] In this embodiment, evaluating the condition of the insulator based on the leakage current, weight, inclination angle, and temperature of the insulator includes: Comparing the leakage current of the insulator with a preset leakage current threshold. If the leakage current of the insulator is greater than the preset leakage current threshold, it is determined that the leakage current of the insulator is abnormal; otherwise, it is determined that the leakage current of the insulator is normal; Comparing the weight of the insulator with a preset weight threshold. If the weight of the insulator is greater than the preset weight threshold, it is determined that the weight of the insulator is abnormal; otherwise, it is determined that the weight of the insulator is normal; Comparing the inclination angle of the insulator with a preset inclination angle threshold. If the inclination angle of the insulator is greater than the preset inclination angle threshold, it is determined that the inclination angle of the insulator is abnormal; otherwise, it is determined that the inclination angle of the insulator is normal; Comparing the temperature of the insulator with a preset temperature threshold. If the temperature of the insulator is greater than the preset temperature threshold, it is determined that the temperature of the insulator is abnormal; otherwise, it is determined that the temperature of the insulator is normal.

[0021] In this embodiment, sending a status anomaly signal to each sub-module according to the insulator condition evaluation result includes: If it is determined that the leakage current of the insulator is abnormal, a leakage current anomaly signal is sent to the leakage current monitoring sub-module; If it is determined that the weight of the insulator is abnormal, a weight anomaly signal is sent to the weight monitoring sub-module; If it is determined that the inclination angle of the insulator is abnormal, an inclination angle anomaly signal is sent to the inclination angle monitoring sub-module; If it is determined that the temperature of the insulator is abnormal, a temperature anomaly signal is sent to the temperature monitoring sub-module.

[0022] In a possible embodiment, such as Figure 1As shown, the leakage current monitoring sub-module uses a leakage current sensor to monitor the leakage current of the insulator; the leakage current sensor issues a leakage current anomaly alarm according to the leakage current anomaly signal.

[0023] Specifically, the leakage current sensor is a functional module for measuring the leakage current of the device. By measuring the leakage current, it can determine whether the insulation performance of the insulator is normal. An increased leakage current usually indicates contamination or deterioration on the surface of the insulator. Monitoring the leakage current helps to detect surface contamination, deterioration, or other abnormal conditions of the insulator at an early stage, so as to take preventive measures and avoid power system failures. When the leakage current exceeds the preset threshold, the sensor can issue an alarm to prompt the maintenance personnel to check and clean the insulator, preventing power accidents caused by insulation failures. By monitoring and dealing with insulation problems in real time, power accidents caused by insulation failures can be avoided, ensuring the safe operation of the power system. The leakage current sensor used in this embodiment, compared with the sensors used in general monitoring devices, can be applied to the UHV environment, ensuring that it has a sufficient measurement range and accuracy. And it has good anti-interference ability and can work normally in a complex electromagnetic environment.

[0024] In a possible embodiment, as Figure 1 As shown, the weight monitoring sub-module uses a tension sensor to monitor the weight of the insulator; the tension sensor issues a weight anomaly alarm according to the weight anomaly signal.

[0025] Specifically, the tension sensor monitors the increase in the weight of the insulator to determine whether there is an icing phenomenon. Icing will form a layer of ice on the surface of the insulator, increasing its total weight. This increase in weight will lead to an increase in mechanical stress, which may damage the structure of the insulator. At the same time, it will also affect the electrical performance of the insulator and increase the risk of electric leakage. Therefore, real-time monitoring of the weight change of the insulator through the tension sensor module is an important measure to ensure the safe operation of the insulator and the entire power system. The tension sensor used in this embodiment can work normally in the UHV environment and has sufficient accuracy and reliability, and can work normally under extreme climate conditions, covering the weight change range of the insulator in normal and icing conditions.

[0026] In a possible embodiment, as Figure 1 As shown, the tilt angle monitoring sub-module uses an angle sensor to monitor the tilt angle of the insulator; the angle sensor issues a tilt angle anomaly alarm according to the tilt angle anomaly signal.

[0027] Specifically, the angle sensor monitors the wind deflection of the insulator by measuring its tilt angle, thereby determining the impact of the wind on the insulator. Strong winds can cause the insulator to deviate from its normal vertical position and become tilted. This tilt not only increases mechanical stress but may also affect the electrical performance and safety of the insulator. Therefore, real-time monitoring of the tilt angle of the insulator is crucial for ensuring the stable operation of the insulator and the power system. The angle sensor used in this embodiment has high precision and high reliability, can work stably in a high-voltage environment, and can adapt to extreme climate conditions such as high wind speed, low temperature, and high humidity, ensuring normal operation in various environments.

[0028] In a possible embodiment, as Figure 1 shown, the temperature monitoring sub-module uses an infrared camera sensor to monitor the temperature of the insulator, and the infrared camera sensor issues a temperature anomaly alarm according to the temperature anomaly signal.

[0029] Specifically, the infrared camera sensing module monitors the temperature distribution of each part of the insulator by taking infrared photos of the insulator. The temperature change of the insulator can reflect its working state and health condition. Especially in a high-voltage environment, local overheating may indicate potential faults. By monitoring the temperature through an infrared camera, hot spots on the surface of the insulator can be detected and processed early to prevent power system failures. The infrared camera selected in this embodiment can work normally under ultra-high voltage and adverse weather conditions, can accurately capture the temperature changes on the surface of the insulator, the camera can adapt to various environmental factors such as strong wind, heavy rain, ice and snow, and extreme temperatures, and at the same time the camera has the characteristics of waterproof, dustproof, and corrosion-resistant.

[0030] In a possible embodiment, each sub-module and the main control module use the Message Queuing Telemetry Transport (MQTT) protocol for signal transmission.

[0031] MQTT is a lightweight message transmission protocol based on the publish / subscribe model, which is especially suitable for communication between Internet of Things (IoT) devices. It has the characteristics of low bandwidth consumption, high reliability, and easy implementation, and can achieve efficient data transmission in an unstable network environment.

[0032] In a possible embodiment, as Figure 1 shown, each sub-module and the main control module use a 4G communication module for data transmission to ensure real-time data transmission of the device in an environment without fixed network access.

[0033] In this embodiment, the lower computer of the system is installed on the UHV line tower and has no fixed network access. Therefore, 4G communication is selected to provide network support. The 4G communication technology provides a relatively high bandwidth and coverage, which is suitable for the data transmission of the lower computer.

[0034] In a possible embodiment, as Figure 1 shown, the main control board of the main control module uses RK3588S as the core processor, and the embedded NPU supports hybrid operations.

[0035] Compared with ordinary insulator monitoring devices, this embodiment uses Rockchip RK3588S as the core processor, with a main frequency of up to 2.4 GHz. The embedded NPU supports INT4 / INT8 / INT16 hybrid operations, and the computing power is up to 6 TOPS, which can meet the edge computing requirements of this device.

[0036] The hardware structure of the RK3588S processor includes eight high-performance cores (four Cortex-A76 cores and four Cortex-A55 cores), which support multi-task parallel processing and provide excellent computing performance. The processor integrates rich peripheral interfaces, such as I2C, SPI, UART, USB, and Ethernet interfaces, enabling it to connect various sensors and external devices. In addition, RK3588S also supports multiple memory interfaces, such as LPDDR4 / LPDDR4X and eMMC / UFS, ensuring efficient data storage and access of the system.

[0037] To meet the edge computing requirements of the system, the NPU (Neural Network Processing Unit) embedded in RK3588S provides a computing power of up to 6 TOPS, supports INT4 / INT8 / INT16 hybrid operations, and can process complex artificial intelligence algorithms and real-time data analysis. The introduction of the NPU enables the system to perform intelligent processing locally, which can be used to process the video of the infrared camera in this device, upload the results, reduce data transmission latency, and improve the device response speed.

[0038] In a possible embodiment, the system background predicts the insulator state based on the monitoring data of each sub-module, and provides a method for predicting the faults of contaminated insulators based on an enhanced time series prediction model. Through the time series analysis of the insulator leakage current, it can accurately predict the fault development, improve the power grid monitoring level, and reduce power outages caused by insulator faults.

[0039] The specific technical solutions include: (1) Experimental setup and data collection Experiments were conducted in a salt fog chamber to simulate the accumulation of salt contamination on the surface of insulators. Six insulators were installed in the salt fog chamber, and a voltage of 8.66 kV (RMS), 60 Hz (in line with relevant standards) was applied, and the salt concentration was gradually increased.

[0040] The LabVIEW software development interface was used to monitor and record the applied voltage and the resulting leakage current. Each insulator was grounded separately through a shunt resistor to measure the leakage current. The experiment was continuously carried out, and a large number of measurement data were recorded. A total of more than 90,000 measurements were recorded, among which four insulators experienced flashovers, and subsequent analysis was based on the data of these insulators that had flashovers.

[0041] (2) Construction and evaluation of time series prediction models: A variety of time series prediction models were used for analysis, including long short-term memory network (LSTM), group method of data handling (GMDH), adaptive neuro-fuzzy inference system (ANFIS), and ensemble learning models (such as bootstrap aggregation (bagging), sequential learning (boosting), random subspace, stacked generalization (stacking)).

[0042] For each model, first, the performance under different structural configurations was evaluated. After determining the optimal structure, the hyperparameters of the model were further optimized. For example, the LSTM model searched for the optimal performance by changing the number of hidden units and optimizers (such as stochastic gradient descent with momentum (SGDM), adaptive moment estimation (ADAM), root mean square propagation (RMSProp)); the GMDH model was optimized by adjusting the maximum number of neurons; the ANFIS model adopted a subtractive clustering structure and was evaluated by changing the training form and influence radius (such as using a hybrid optimization method); the ensemble bagging model determined the best settings by comparing combinations of different optimizers (such as L1QP, ISDA, SMO) and kernel functions (such as linear, radial basis function (RBF), polynomial).

[0043] Wavelet transform was applied to enhance the model. By testing combinations of wavelet packet trees with different depths, its impact on the model's prediction ability was evaluated. Wavelet transform can effectively reduce signal noise, extract more useful information, and improve the model's prediction performance.

[0044] (3) Model performance evaluation metrics Indicators such as root mean square error (RMSE), mean absolute percentage error (MAPE), mean absolute error (MAE), and coefficient of determination (R2) were used to evaluate the prediction error and fitting degree of the model.

[0045] Calculate the mean, median, standard deviation, and variance of the computational model to evaluate the stability and reliability of the model in multiple simulations.

[0046] By comprehensively comparing multiple time series prediction models, the fault development of contaminated insulators can be predicted more accurately, improving the accuracy of fault prediction.

[0047] Optimizing the model structure and hyperparameters, as well as applying wavelet transform, effectively improves the performance of the model, enabling it to better adapt to the complex changes in the leakage current of insulators.

[0048] Based on the analysis of experimental data, the method has practical application value, which helps the power department to take timely measures to prevent insulator faults and ensure the safe and stable operation of the power grid.

[0049] The above are only the preferred embodiments of the present application. It should be noted that for those of ordinary skill in the art in this technical field, without departing from the technical principle of the present application, several improvements and deformations can be made, and these improvements and deformations should also be regarded as the protection scope of the present application.

Claims

1. A multi-mode insulator condition monitoring system, characterized in that: include: Leakage current monitoring submodule, used to monitor the leakage current of the insulator; Weight monitoring submodule, used to monitor the weight of insulators; The tilt angle monitoring submodule is used to monitor the tilt angle of the insulator; Temperature monitoring submodule, used to monitor the temperature of the insulator; The main control module is used to evaluate the state of the insulator according to the leakage current, weight, tilt angle and temperature of the insulator, and obtain the evaluation result of the insulator state; and to send a state abnormality signal to each submodule according to the evaluation result of the insulator state; Each submodule issues an abnormal alarm based on the abnormal signal sent by the main control module.

2. The multi-mode insulator condition monitoring system according to claim 1, characterized in that: Condition assessment of insulators based on their leakage current, weight, tilt angle and temperature includes: Compare the leakage current of the insulator with a preset leakage current threshold value, if the leakage current of the insulator is greater than the preset leakage current threshold value, then determine that the leakage current of the insulator is abnormal, otherwise, determine that the leakage current of the insulator is normal; The weight of the insulator is compared with a preset weight threshold. If the weight of the insulator is greater than the preset weight threshold, it is determined that the weight of the insulator is abnormal; otherwise, it is determined that the weight of the insulator is normal; Compare the inclination angle of the insulator with a preset inclination angle threshold value, if the insulator inclination angle is greater than the preset inclination angle threshold value, determine that the insulator inclination angle is abnormal, otherwise, determine that the insulator inclination angle is normal; The temperature of the insulator is compared with a preset temperature threshold. If the temperature of the insulator is greater than the preset temperature threshold, it is determined that the temperature of the insulator is abnormal; otherwise, it is determined that the temperature of the insulator is normal.

3. The multi-mode insulator condition monitoring system according to claim 2, characterized in that: According to the insulator status evaluation results, the status abnormality signals sent to each submodule include: If the leakage current of the insulator is determined to be abnormal, a leakage current abnormality signal is sent to the leakage current monitoring submodule; If the weight of the insulator is determined to be abnormal, an abnormal weight signal is sent to the weight monitoring submodule; If the insulator's tilt angle is determined to be abnormal, an abnormal tilt angle signal is sent to the tilt angle monitoring submodule; If the temperature of the insulator is determined to be abnormal, a temperature abnormality signal is sent to the temperature monitoring submodule.

4. The multi-mode insulator condition monitoring system according to claim 1, characterized in that: The leakage current monitoring submodule uses a leakage current sensor to monitor the leakage current of the insulator; the leakage current sensor issues a leakage current abnormality alarm according to the leakage current abnormality signal.

5. The multi-mode insulator condition monitoring system according to claim 1, characterized in that: The weight monitoring submodule uses a tension sensor to monitor the weight of the insulator; the tension sensor issues an abnormal weight alarm based on the abnormal weight signal.

6. The multi-mode insulator condition monitoring system according to claim 1, characterized in that: The tilt angle monitoring submodule uses an angle sensor to monitor the tilt angle of the insulator; the angle sensor issues an abnormal tilt angle alarm based on an abnormal tilt angle signal.

7. The multi-mode insulator condition monitoring system according to claim 1, characterized in that: The temperature monitoring submodule uses an infrared camera sensor to monitor the temperature of the insulator, and the infrared camera sensor issues a temperature abnormality alarm based on the temperature abnormality signal.

8. The multi-mode insulator condition monitoring system according to any one of claims 4 to 7, characterized in that: The measurement range and accuracy of each sensor meet the requirements of UHV environment.

9. The multi-mode insulator condition monitoring system according to claim 1, characterized in that: Each submodule and the main control module use the message queue telemetry transmission protocol for signal transmission.

10. The multi-mode insulator condition monitoring system according to claim 1, characterized in that: The main control module uses RK3588S as the core processor, and the embedded NPU supports hybrid computing.

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