Power equipment element aging monitoring system and method based on capacitive coupling technology

Abstract

The application relates to the technical field of power equipment monitoring, in particular to a power equipment element aging monitoring system and method based on a capacitive coupling technology, which comprises a ring electrode sensor, a preamplifier, a data acquisition card and a system integration platform; the ring electrode sensor senses the electric field change in the power equipment through non-contact sensing and outputs a weak electric signal; the preamplifier receives the weak electric signal and converts the weak electric signal into an electric signal output; the data acquisition card converts the electric signal into a digital signal output to the system integration platform; the system integration platform processes the digital signal, establishes an equipment aging model, outputs an evaluation result through the equipment aging model and reflects the aging degree of the power equipment. The capacitive coupling technology is adopted to realize dynamic monitoring and early warning of the health state of the power equipment without stopping the power equipment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power equipment monitoring, in particular to a power equipment element aging monitoring system based on capacitive coupling technology and a method thereof. BACKGROUND

[0002] With the continuous development of power systems, the safe and stable operation of power equipment has become one of the core issues of the power industry. During the long-term operation of power equipment, its internal elements will gradually age, which not only affects the normal work of the equipment, but also may cause serious safety accidents. Therefore, effectively monitoring the aging state of power equipment elements is of great significance to ensure the safety and reliability of the power system. However, traditional methods often rely on periodic manual inspection and maintenance, which not only is inefficient, but also cannot find potential problems in time, and cannot meet the needs of modern power systems for real-time monitoring of equipment health status.

[0003] Traditional power equipment element aging monitoring methods mainly include periodic maintenance inspection, temperature monitoring, and vibration analysis. Although these methods can reflect the state of the equipment to some extent, they have obvious limitations. For example, periodic maintenance inspection is time-consuming and laborious, and it is difficult to find early subtle changes; temperature monitoring is not accurate due to the influence of external environmental factors; vibration analysis can detect some mechanical failures, but it is powerless to changes in electrical performance. In addition, these methods usually require the equipment to be shut down, which is unacceptable for continuously running power systems.

[0004] In recent years, with the development of sensing technology and data processing technology, many new online monitoring technologies have emerged, such as infrared thermal imaging monitoring, acoustic emission monitoring, etc. These technologies have improved the accuracy and real-time performance of monitoring to some extent, but still have problems such as high cost and complex operation. Especially in the aspect of aging monitoring of internal elements of power equipment, due to the complex internal environment of power equipment and serious electromagnetic interference, existing monitoring technologies are difficult to obtain satisfactory monitoring results. Therefore, it is particularly important to develop a new technology that can overcome the shortcomings of existing technologies and be suitable for the aging monitoring of internal elements of power equipment.

[0005] The present application proposes a power equipment element aging monitoring system based on capacitive coupling technology, aiming at solving the problems existing in the prior art. SUMMARY

[0006] The power equipment element aging monitoring system based on capacitive coupling technology of the present application comprises: a ring electrode sensor, a preamplifier, a data acquisition card, and a system integration platform.

[0007] The ring electrode sensor is installed on the shell of the power equipment, and outputs a weak electric signal by non-contact sensing of the electric field change inside the power equipment.

[0008] The preamplifier receives the weak electric signal output by the ring electrode sensor and converts it into an electric signal output.

[0009] The data acquisition card converts the electric signal output by the preamplifier into a digital signal output.

[0010] The system integration platform includes a signal processing module, a data storage module, a machine learning module, a communication module, a visualization module, and an alarm module.

[0011] The signal processing module filters and extracts features from the collected digital signals, and outputs feature information of the digital signals.

[0012] The data storage module stores the collected raw data and processed feature information.

[0013] The machine learning module combines the raw data and feature information, uses a machine learning algorithm to establish a device aging model, and outputs an evaluation result through the device aging model.

[0014] The communication module is responsible for data transmission, and receives feature information from the signal processing module and evaluation results from the machine learning module, and transmits them to the data storage module and the visualization module.

[0015] The visualization module receives the evaluation results transmitted by the communication module, and displays the health status of the device through a user interface.

[0016] The alarm module triggers an alarm based on the evaluation results transmitted by the communication module.

[0017] Preferably, the ring electrode sensor interacts with the electric field generated inside the power equipment through capacitive coupling technology, and the ring electrode sensor and the electric field inside the power equipment form a capacitor. When the electric field inside the power equipment changes, the charge distribution of the capacitor changes, generating a small current. The ring electrode sensor outputs a weak electric signal to the preamplifier by receiving the small current.

[0018] Preferably, the preamplifier is internally provided with a high-gain operational amplifier chip and a low-noise operational amplifier chip. The weak electric signal is amplified by multiple stages of amplification circuit and high-gain operational amplifier chip inside the preamplifier to achieve high gain, and by low-noise operational amplifier chip and decoupling capacitor at the input end to achieve low noise.

[0019] Preferably, the data acquisition card filters the electrical signal through an internal signal conditioning circuit, converts the electrical signal into a digital signal through an analog-to-digital converter, and transmits the digital signal to the signal processing module and the data storage module through the communication module of the system integration platform.

[0020] Preferably, the signal processing module receives the digital signal of the digital acquisition card for filtering and feature extraction; the digital signal is filtered through an adaptive filtering technique, which removes error digital signals and repeated digital signals in the digital signal.

[0021] Preferably, the feature extraction extracts characteristic information from the digital signal; the feature extraction includes Fourier transform technology and wavelet transform technology to extract frequency spectrum features and multi-scale features from the digital signal; the frequency spectrum features are the amplitude and phase information of different frequency components extracted by Fourier transform, reflecting the changes of the internal electric field of the power equipment; the multi-scale features are the features of the signal in different time scales extracted by wavelet transform technology, capturing the transient and local changes in the signal.

[0022] Preferably, the machine learning module uses the labeled raw data and feature information to train the device aging model through a random forest algorithm; the device aging model outputs an evaluation result through the input of real-time digital signals, which is transmitted to the visualization module and the alarm module through the communication module.

[0023] Preferably, the visualization module receives the evaluation result and the feature information, and displays the health status, historical trend and fault warning information of the device through the user interface, providing intuitive visual reports; the visualization module uses dynamic data update technology to realize real-time data transmission through WebSocket, ensuring that the user interface can display the latest monitoring results and evaluation reports in real time.

[0024] Preferably, the warning module monitors the health status of the device in real time, and triggers an alarm when the health status of the device reaches a preset threshold; the warning module also uses a multi-level warning mechanism to set different threshold values for different warning levels according to different stages of device aging, accurately predicting the degree of device aging.

[0025] The power equipment element aging monitoring method based on the capacitive coupling technology comprises the following steps:

[0026] S1, install a ring electrode sensor on the shell of the power equipment to sense the internal electric field changes through non-contact sensing and output weak electrical signals;

[0027] S2, receive the weak electrical signals of the ring electrode sensor through a preamplifier, and output amplified electrical signals through the preamplifier;

[0028] S3, receiving the electrical signal of the preamplifier by the data acquisition card, filtering, and converting the electrical signal into a digital signal through an analog converter, and outputting the digital signal;

[0029] S4, the signal processing module receives the digital signal of the data acquisition card, filters through an adaptive filtering technology, and extracts feature information using Fourier transform and wavelet transform;

[0030] S5, combining the original data and the feature information through the machine learning module, using a random forest algorithm to establish a device aging model, outputting the evaluation result of the device health status, and transmitting the evaluation result to the visualization module and the early warning module to monitor the degree of device aging.

[0031] Compared with the prior art, the technical scheme of the present application has the following technical effects:

[0032] The present application solves the problems of inconvenient operation and safety hazards caused by the need to directly contact the internal components of the power equipment in the traditional monitoring method by using a non-contact ring electrode sensor to form a capacitor with the internal electric field of the power equipment, enabling the ring electrode sensor to monitor the electric field changes inside the power equipment in real time without stopping, outputting weak electrical signals, and further realizing continuous monitoring of the aging state of the power equipment components, greatly improving the efficiency and safety of the monitoring, and ensuring the stable operation of the power system.

[0033] The high-gain operational amplifier chip and the low-noise operational amplifier chip provided in the preamplifier solve the problems of low signal-to-noise ratio and signal distortion in the amplification process of weak electrical signals, effectively amplify the weak electrical signals from the ring electrode sensor, reduce noise interference, and ensure the purity of the signals. After processing by the preamplifier, the quality of the electrical signals is significantly improved, providing a reliable foundation for subsequent data processing, thereby improving the accuracy and reliability of the entire monitoring system.

[0034] The signal processing module uses adaptive filtering technology, Fourier transform and wavelet transform technology for feature extraction, solving the problems of interference of error signals and repeated signals in the digital signal processing process, and how to extract useful features from complex signals, removing errors and repeated parts in the digital signal, and extracting frequency spectrum features and multi-scale features reflecting the changes of the internal electric field of the power equipment from the signal. This enables the system to more accurately analyze the health status of the power equipment, providing high-quality data support for the subsequent establishment of the device aging model, and enhancing the intelligent analysis capability of the monitoring system.

[0035] The application solves the problem of how to evaluate the aging degree of equipment by using original data and real-time monitoring data by using a random forest algorithm of a machine learning module to establish an equipment aging model. The model can accurately evaluate the aging state of equipment by combining original data and real-time monitoring feature information. The model can output evaluation results in real time, and the results are transmitted to a visualization module and an early warning module through a communication module, thereby realizing dynamic monitoring and early warning of the health state of power equipment. This not only improves the predictability and initiative of equipment maintenance, but also reduces the risk of accidents caused by equipment aging, and provides a strong guarantee for the safe operation of the power system.

[0036] The above description is only a summary of the technical solutions of the application. In order to more clearly understand the technical means of the application, the content of the description can be implemented, and in order to make the above and other purposes, characteristics and advantages of the application more obvious and easy to understand, the following will be described in detail with the preferred embodiments of the application and the accompanying drawings.

[0037] According to the detailed description of the specific embodiments of the application in the following text combined with the drawings, those skilled in the art will more clearly understand the above and other purposes, advantages and characteristics of the application. BRIEF DESCRIPTION OF DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the drawings needed in the embodiment or prior art description will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the application, and those skilled in the art can also obtain other drawings according to these drawings without creative labor. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, each element or part is not necessarily drawn according to the actual proportion.

[0039] Figure 1 The module diagram of the power equipment element aging monitoring system based on the capacitive coupling technology of the application;

[0040] Figure 2 The flowchart of the power equipment element aging monitoring method based on the capacitive coupling technology of the application. DETAILED DESCRIPTION

[0041] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the following will be combined with the accompanying drawings for the embodiments of the present application to make a clear and complete description of the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. In the following description, specific details such as specific configurations and components are provided only for the purpose of helping to fully understand the embodiments of the present application. Therefore, those skilled in the art should clearly understand that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. In addition, in order to be clear and concise, the description of known functions and structures is omitted in the embodiments.

[0042] It should be understood that the "one embodiment" or "the embodiment" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "one embodiment" or "the embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner.

[0043] In addition, reference numerals and / or letters can be repeated in different examples in the present application. Such repetition is for the purpose of simplification and clarity, and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed.

[0044] The term "and / or" herein is only a description of the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B can mean that A exists alone, B exists alone, and A and B exist together. The term "and" herein is a description of another association relationship of the associated objects, which means that there can be two relationships, for example, A and B can mean that A exists alone and A and B exist together. In addition, the character " / " herein generally represents an "or" relationship between the associated objects before and after it.

[0045] The term "at least one" herein is only a description of the association relationship of the associated objects, which means that there can be three relationships, for example, at least one of A and B can mean that A exists alone, A and B exist together, and B exists alone.

[0046] It should also be noted that the relationship terms such as first and second in the present document are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion.

[0047] Embodiment 1

[0048] The embodiment mainly describes the power equipment element aging monitoring system based on the capacitive coupling technology, as shown in Figure 1 It comprises a ring electrode sensor, a preamplifier, a data acquisition card and a system integration platform.

[0049] The ring electrode sensor is installed on the shell of the power equipment. It can perceive the electric field change inside the power equipment through non-contact sensing. The ring electrode sensor can be installed on the transformer and circuit breaker of the power equipment to ensure that the main electric field change area of the power equipment is covered and a weak electric signal is output.

[0050] Further, the ring electrode sensor interacts with the electric field generated inside the power equipment through the capacitive coupling technology. The ring electrode sensor and the electric field inside the power equipment form a capacitor. When the electric field inside the power equipment changes, the charge distribution of the capacitor changes, generating a small current. The ring electrode sensor outputs a weak electric signal to the preamplifier through receiving the small current.

[0051] The preamplifier receives the weak electric signal output by the ring electrode sensor and converts it into a processable electric signal output.

[0052] Further, the preamplifier is internally provided with a high-gain operational amplifier chip and a low-noise operational amplifier chip. The weak electric signal realizes high gain through the multi-stage amplification circuit and the high-gain operational amplifier chip inside the preamplifier, and realizes low noise through the low-noise operational amplifier chip and the decoupling capacitor at the input end.

[0053] The data acquisition card converts the electric signal output by the preamplifier into a digital signal output through receiving the electric signal.

[0054] Further, the data acquisition card filters the electric signal through the internal signal conditioning circuit, converts the electric signal into a digital signal through the analog converter, and transmits it to the signal processing module and the data storage module through the communication module of the system integration platform.

[0055] The system integration platform comprises a signal processing module, a data storage module, a machine learning module, a communication module, a visualization module and an alarm module.

[0056] The signal processing module filters and extracts features from the collected digital signal, and outputs the feature information of the digital signal.

[0057] Further, the signal processing module receives the digital signals from the digital acquisition card for filtering and feature extraction. The digital signals are filtered through adaptive filtering techniques, which remove erroneous and repetitive digital signals from the digital signals. The adaptive filtering techniques can remove random noise from the digital signals, which comes from the sensor itself, the preamplifier, power supply interference, or other external electromagnetic interference. At the same time, the adaptive filtering techniques can remove frequency components unrelated to device aging from the signals. For example, if the device aging mainly manifests as changes in the electric field within a specific frequency range, the filter can remove signals within other frequency ranges to reduce interference. The adaptive filtering techniques can also smooth out transient spikes or mutations in the signals, which can affect subsequent feature extraction and analysis.

[0058] Further, the feature extraction extracts feature information from the digital signals. The feature extraction includes Fourier transform techniques and wavelet transform techniques to extract frequency spectrum features and multi-scale features from the digital signals. The frequency spectrum features extract the amplitude and phase information of different frequency components through Fourier transform, reflecting changes in the internal electric field of the power equipment. The multi-scale features extract the characteristics of the signal at different time scales through wavelet transform techniques, capturing transient and local changes in the signal.

[0059] Further, the frequency spectrum features refer to the amplitude and phase information of different frequency components extracted from the digital signals. Through Fourier transform, time-domain signals can be converted into frequency-domain signals, allowing for analysis of the distribution of signals at different frequencies and reflecting changes in the internal electric field of the power equipment. For example, degradation of insulation materials within the device may cause an increase or decrease in electric field strength within a specific frequency range. By analyzing the amplitude and phase changes of these frequency components, the health status and aging trend of the device can be effectively identified.

[0060] Further, the multi-scale features refer to the feature information extracted from the digital signals at different time scales. Through wavelet transform techniques, the signal can be decomposed into sub-signals at different time scales, capturing transient and local changes in the signal. For example, mechanical wear and tear or partial discharge within the device may cause transient changes in the signal, which may be difficult to capture in traditional time-domain or frequency-domain analysis. By extracting multi-scale features through wavelet transform, the health status of the device can be more comprehensively evaluated, improving the accuracy and reliability of the aging monitoring.

[0061] The data storage module stores the raw data collected and the processed feature information.

[0062] The machine learning module combines the raw data and feature information to establish a device aging model using machine learning algorithms, and outputs an evaluation result through the device aging model.

[0063] Further, the original data is the device operation data in the past period of time, including temperature, humidity, voltage, current and electric field change data obtained by capacitive coupling technology; by labeling the original data, a training data set is generated, a model is trained using a random forest algorithm through the training data set, and a device aging model is established;

[0064] Further, the machine learning module uses the labeled original data and feature information to train the device aging model through the random forest algorithm; the device aging model outputs an evaluation result through the input real-time digital signal, which is transmitted to the visualization module and the alarm module through the communication module.

[0065] The communication module is responsible for data transmission, and receives feature information from the signal processing module and evaluation results from the machine learning module, and transmits them to the data storage module and the visualization module.

[0066] The visualization module receives the evaluation results transmitted by the communication module, and displays the health status of the device through the user interface.

[0067] Further, the visualization module includes a front-end development module, a back-end development module and a user interface; the front-end development module receives the feature information and evaluation results transmitted by the communication module and transmits them to the back-end development module, and the back-end development module generates the health status, historical trend and fault warning information of the device by integration and transmits them to the user interface.

[0068] Further, the visualization module receives the evaluation results and feature information, and displays the health status, historical trend and fault warning information of the device through the user interface, providing intuitive visual reports; the visualization module uses dynamic data updating technology to realize real-time data transmission through WebSocket, ensuring that the user interface can display the latest monitoring results and evaluation reports in real time.

[0069] The alarm module triggers an alarm through the evaluation results transmitted by the communication module; the warning module triggers an alarm when the health status of the device reaches a preset threshold by monitoring the health status of the device in real time; the warning module also uses a multi-level warning mechanism to set different threshold values for different stages of device aging, accurately predicting the degree of device aging.

[0070] The embodiment details that the system adopts a non-contact ring electrode sensor to sense the electric field change inside the power equipment, realizes real-time monitoring of the aging state of the power equipment element through preamplifier, data acquisition card and system integration platform and the like components, can not only improve the monitoring precision and efficiency and reduce the labor cost, but also can realize long-term tracking of the equipment health state and timely early warning of potential faults, thereby effectively improving the safety and stability of the power system, and in addition, the application also combines an advanced machine learning algorithm, constructs an equipment aging model, and further improves the intelligent level and prediction ability of the monitoring system.

[0071] Embodiment 2

[0072] The embodiment based on embodiment 1 details the power equipment element aging monitoring method based on the capacitive coupling technology, as shown in Figure 2 , including the following steps;

[0073] S1, installing a ring electrode sensor on the power equipment shell, sensing the internal electric field change through a non-contact mode, and outputting a weak electric signal;

[0074] S2, receiving the weak electric signal of the ring electrode sensor through a preamplifier, and outputting an amplified electric signal through the preamplifier;

[0075] S3, receiving the electric signal of the preamplifier by using a data acquisition card, filtering, and converting the electric signal into a digital signal through an analog converter, and outputting the digital signal;

[0076] S4, the signal processing module receives the digital signal of the data acquisition card, filters through an adaptive filtering technology, and uses Fourier transform and wavelet transform to extract feature information;

[0077] S5, combining the original data and the feature information through a machine learning module, using a random forest algorithm to establish an equipment aging model, outputting an evaluation result of the equipment health state, and transmitting the evaluation result to a visualization module and an early warning module to monitor the equipment aging degree.

[0078] The embodiment can realize real-time monitoring of the internal insulation material aging of the high-voltage transformer, early detection of the slight electric field change, and timely discovery of the aging signs by implementing the power equipment element aging monitoring method based on the capacitive coupling technology.

[0079] The above is only the preferred embodiment of the application, which does not limit the protection scope of the application; for those skilled in the art, the application can have various changes and variations; any change, modification, replacement, integration and parameter change of the embodiments within the spirit and principle of the application, which can realize the same function without departing from the principle and spirit of the application, falls within the protection scope of the application.

Claims

1. A power equipment element aging monitoring system based on a capacitance coupling technique, characterized by, The application relates to a system for monitoring the health of power equipment, comprising a ring electrode sensor, a preamplifier, a data acquisition card and a system integration platform. The ring electrode sensor is installed on the shell of the power equipment and outputs a weak electric signal by non-contact sensing of the electric field change in the power equipment. The preamplifier receives the weak electric signal output by the ring electrode sensor and converts the weak electric signal into an electric signal output. The data acquisition card receives the electric signal output by the preamplifier and converts the electric signal into a digital signal output. The system integration platform comprises a signal processing module, a data storage module, a machine learning module, a communication module, a visualization module and an alarm module. The signal processing module filters and extracts features of the collected digital signal and outputs feature information of the digital signal. The data storage module stores the collected original data and the processed feature information. The machine learning module combines the original data and the feature information, uses a machine learning algorithm to establish a device aging model and outputs an evaluation result through the device aging model. The communication module is responsible for data transmission and receives the feature information from the signal processing module and the evaluation result from the machine learning module and transmits the feature information and the evaluation result to the data storage module and the visualization module. The visualization module receives the evaluation result transmitted by the communication module and displays the health state of the device through a user interface. The alarm module triggers an alarm through the evaluation result transmitted by the communication module. The ring electrode sensor interacts with the electric field generated in the power equipment through a capacitive coupling technology, the ring electrode sensor and the electric field in the power equipment form a capacitor, when the electric field in the power equipment changes, the charge distribution of the capacitor changes, a small current is generated, the ring electrode sensor receives the small current and outputs a weak electric signal to the preamplifier.

2. The system for monitoring the aging of power equipment elements based on the capacitive coupling technique according to claim 1, characterized in that, The preamplifier is internally provided with a high-gain operational amplifier chip and a low-noise operational amplifier chip, the weak electric signal realizes high gain through the multi-stage amplification circuit and the high-gain operational amplifier chip in the preamplifier and realizes low noise through the low-noise operational amplifier chip and the decoupling capacitor at the input end.

3. The system for monitoring the aging of power device elements based on the capacitive coupling technology according to claim 2, characterized in that, The data acquisition card filters the electric signal through an internal signal conditioning circuit, converts the electric signal into a digital signal through an analog converter and transmits the digital signal to the signal processing module and the data storage module through the communication module of the system integration platform.

4. The power device element aging monitoring system based on a capacitance coupling technique according to claim 1 or 3, characterized by, The signal processing module receives the digital signal of the data acquisition card and filters and extracts features; the digital signal is filtered through an adaptive filtering technology, the adaptive filtering technology removes error digital signals and repeated digital signals in the digital signal.

5. The system for monitoring the aging of power device elements based on the capacitive coupling technology according to claim 4, characterized in that, The feature extraction extracts feature information from the digital signal; the feature extraction comprises a Fourier transform technology and a wavelet transform technology, frequency spectrum features and multi-scale features are extracted from the digital signal; the frequency spectrum features are amplitude and phase information of different frequency components extracted through the Fourier transform and reflect the change of the electric field in the power equipment; the multi-scale features are features of the signal at different time scales extracted through the wavelet transform technology and capture the transient and local changes in the signal.

6. The system for monitoring the aging of power device elements based on the capacitive coupling technology according to claim 5, characterized in that, ​ 7. The system for monitoring the aging of power equipment elements based on the capacitive coupling technique according to claim 1, characterized in that, The machine learning module uses the labeled raw data and feature information to train the device aging model through a random forest algorithm; the device aging model outputs an evaluation result through input real-time digital signals, which is transmitted to the visualization module and the alarm module through the communication module.

8. The system for monitoring the aging of power device elements based on the capacitive coupling technology according to claim 7, characterized in that, The visualization module receives the evaluation result and feature information, and displays the health status, historical trends, and failure warning information of the device through a user interface, providing intuitive visual reports; the visualization module uses dynamic data updating technology to achieve real-time data transmission through WebSocket, ensuring that the user interface can display the latest monitoring results and evaluation reports in real time.

9. The system for monitoring the aging of power equipment elements based on the capacitive coupling technique according to claim 7, characterized in that, The alarm module monitors the health status of the device in real time and triggers an alarm when the device health status reaches a preset threshold; the alarm module also uses a multi-level warning mechanism to set different threshold values for different stages of device aging, accurately predicting the degree of device aging.

10. A method for monitoring the ageing of power equipment elements based on the capacitive coupling technique, characterized in that, The method comprises the following steps: S1, install a ring electrode sensor on the power equipment shell to output weak electric signals by non-contact sensing of internal electric field changes; S2, receive the weak electric signals of the ring electrode sensor through a preamplifier and output amplified electric signals through the preamplifier; S3, use a data acquisition card to receive the electric signals of the preamplifier, filter them, and convert the electric signals into digital signals through an analog converter, and output the digital signals; S4, the signal processing module receives the digital signals of the data acquisition card, filters them through adaptive filtering technology, and extracts feature information using Fourier transform and wavelet transform; S5, use the machine learning module to combine the raw data and feature information, use a random forest algorithm to establish a device aging model, output an evaluation result of the device health status, and transmit the evaluation result to the visualization module and the warning module to monitor the degree of device aging.

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