Method and system for detecting zero value of inductive suspension type ceramic insulator

Abstract

The invention discloses an induction type suspension ceramic insulator zero value detection method and system, and relates to the technical field of power system detection.The method comprises the steps that an electric signal and an optical signal at the two ends of an insulator are collected through an induction assembly, and the collection sensitivity is adjusted in real time to adapt to environment changes; the signal processing unit is used for carrying out noise reduction and feature extraction on the collected signals, and the insulation performance state is judged by analyzing feature values; and generating a detection report according to an analysis result, and evaluating the potential risk of the insulation performance to generate a maintenance suggestion. According to the method, the insulation performance state of the insulator is accurately judged, the judgment accuracy of the insulation performance state is improved, reliable data support is provided for maintenance decision, the maintenance efficiency and the response speed are improved, potential risks of the insulation performance are evaluated in combination with environmental parameters, and a scientific basis is provided for preventive maintenance.

Description

Technical Field

[0001] The invention relates to the technical field of power system detection, and in particular to a method and system for detecting zero value of an inductive suspension ceramic insulator. Background Art

[0002] With the rapid development of the power industry and the increasing complexity of the transmission network, suspension ceramic insulators are being used more and more widely, playing a vital role in ensuring the stable operation of the power grid. In order to ensure the reliability and safety of insulators, insulator detection technology has also been continuously improving. From the initial visual inspection to the modern non-contact detection, technical means are becoming increasingly rich and efficient, especially non-contact detection technology, which has become a research hotspot and development trend because it can perform real-time monitoring without power outages.

[0003] However, the existing non-contact detection technology still has some significant deficiencies in practice. In terms of signal acquisition, traditional technology is often unable to adjust the sensitivity in real time according to environmental changes, resulting in low accuracy of signal acquisition in complex environments. Although the existing technology has made some progress in signal processing, it still has limitations in the accuracy of noise reduction and feature extraction, which directly affects the accuracy of insulation performance status judgment. Existing detection technology rarely provides a comprehensive detection report including insulation status, fault type and maintenance suggestions, which makes the maintenance work lack of pertinence and foresight. In particular, in terms of real-time adjustment of acquisition sensitivity, accurate analysis of characteristic values ​​and generation of maintenance suggestions, the existing technology fails to achieve the expected effect and cannot meet the high standards of insulator detection in the power system. Although some technologies have been tried to make improvements, the existing technology still cannot effectively solve the problems of adaptability of signal acquisition, accuracy of signal processing and practicality of detection reports. In particular, in terms of real-time adjustment of acquisition sensitivity to adapt to environmental changes, accurate judgment of insulation performance status through characteristic value analysis, and generation of targeted maintenance suggestions based on detection results, the existing technology has not yet achieved the ideal effect. Therefore, how to improve the accuracy and practicality of detection while ensuring detection efficiency has become an urgent problem to be solved in the field of power system detection. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is: the existing suspension ceramic insulator zero value detection technology has poor signal acquisition adaptability, insufficient signal processing and analysis accuracy, lack of an effective maintenance suggestion generation mechanism, and how to achieve real-time adjustment of acquisition sensitivity, accurate judgment of insulation performance status and generation of maintenance suggestions.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: an inductive suspended ceramic insulator zero value detection method, comprising collecting electrical signals and optical signals at both ends of the insulator through an inductive component, and adjusting the collection sensitivity in real time to adapt to environmental changes; using a signal processing unit to reduce noise and extract features of the collected signals, and judging the insulation performance status by analyzing the characteristic values; generating a detection report based on the analysis results, evaluating the potential risks of the insulation performance and generating maintenance recommendations.

[0007] As a preferred solution of the inductive suspension ceramic insulator zero value detection method described in the present invention, wherein: the collection of electrical signals and optical signals at both ends of the insulator by the inductive component includes the sensing component aligning the connection end of the insulator through the signal receiving unit, receiving and capturing the electrical signal and the optical signal, and using the adjustment function to enable the device to adapt to different installation angles and environmental conditions. The device removes the noise signals generated by the surrounding interference sources through the filtering function and collects valid data. During the collection process, the device sends a prompt message of the signal reception status to the user through the feedback mechanism, and the user adjusts the collection position for detection based on the prompt message. During the collection process, the device continuously monitors the signal quality and dynamically adjusts the receiving parameters.

[0008] As a preferred solution of the inductive suspension ceramic insulator zero value detection method described in the present invention, the real-time adjustment of the acquisition sensitivity to adapt to environmental changes includes a built-in automatic adjustment function of the device, which dynamically optimizes the signal acquisition threshold by monitoring the surrounding signal strength and background noise level.

[0009] When the target signal collected is strong, the device automatically reduces the receiving sensitivity to avoid signal overload.

[0010] When the target signal is weak or the background noise is high, the device enhances sensitivity to accurately capture the valid signal.

[0011] In extreme environments, when humidity is high or noise is loud, the device further optimizes signal reception efficiency through real-time adjustments to environmental data and provides a manual adjustment function, allowing users to manually adjust the sensitivity parameters of signal acquisition according to specific working conditions.

[0012] As a preferred solution of the inductive suspension ceramic insulator zero value detection method described in the present invention, the use of a signal processing unit to perform noise reduction and feature extraction on the collected signal includes preprocessing the data using a noise reduction function after the device receives the signal, eliminating non-target signals through an efficient noise reduction algorithm, and extracting the time characteristics and frequency characteristics of the signal, including the change curve of the signal strength, duration and spectrum distribution. In the analysis stage, the device compares the extracted characteristic values ​​with the preset reference standard, and determines the state of the target insulator by the difference. All processing of the entire process is automatically completed by the device, and the processed signal characteristics are stored as data files for subsequent query and verification.

[0013] As a preferred solution of the zero-value detection method for inductive suspension ceramic insulators described in the present invention, the determination of the insulation performance status by analyzing characteristic values ​​includes the device determining whether the insulation performance of the target insulator is within a normal range by comparing and analyzing the amplitude, spectrum characteristics and duration of the collected signal.

[0014] When the signal strength exceeds the normal value and lasts for a short time, the system determines that the insulator may have internal breakdown.

[0015] When the spectrum distribution shows periodic peaks accompanied by weak signal fluctuations, it is judged to be performance degradation caused by surface contamination.

[0016] After completing the status analysis, the equipment stores the abnormal characteristics in the defect database and generates corresponding risk level labels. It uses preset algorithm rules to automatically complete the analysis process without the operator providing additional input. The analysis results are directly output as the basis for insulator maintenance and repair.

[0017] As a preferred solution of the inductive suspension ceramic insulator zero value detection method described in the present invention, the detection report includes the device integrating the analysis data into the report after completing the signal analysis, and the report content includes the information of the target insulator, the current status, fault characteristics and maintenance suggestions. The device generates a trend analysis chart based on the historical detection data to display the long-term change trajectory of the insulation performance. For the detected abnormal conditions, the report sorts the maintenance suggestions according to the fault risk priority. The report is sent to the remote management system in real time via wireless transmission, or is used by on-site maintenance personnel through the local storage of the device.

[0018] As a preferred solution of the zero-value detection method for inductive suspension ceramic insulators described in the present invention, the detection report also includes the equipment evaluating the potential risks of insulation performance in combination with the parameters of temperature, humidity and wind speed of the environment where the target insulator is located.

[0019] In areas with higher humidity, the device performs a weighted assessment of the risk of surface contamination and generates cleaning recommendations in a prioritized manner.

[0020] In high-temperature areas, the system highlights the possibility of insulation material degradation and generates a replacement plan.

[0021] The device analyzes the historical inspection data of insulators and uses trend analysis to predict the speed of their performance degradation. If the insulator is expected to reach a critical value within a future inspection cycle, it is recommended to perform maintenance or replacement in advance. The maintenance recommendations are generated based on a dynamic evaluation model, and the generation logic is optimized through an external fault case library.

[0022] Another object of the present invention is to provide an inductive suspension ceramic insulator zero value detection system, which can reduce noise and extract features of the collected signals by utilizing a signal processing unit, and judge the insulation performance status by analyzing the characteristic values, thereby solving the problems of large noise interference and inaccurate feature extraction in current signal processing technology.

[0023] As a preferred solution of the inductive suspension ceramic insulator zero value detection system described in the present invention, it includes: a sensitivity adjustment module, a signal processing and analysis module, and a detection report generation module.

[0024] The sensitivity adjustment module is used to collect electrical signals and optical signals at both ends of the insulator through the sensing component, and adjust the collection sensitivity in real time to adapt to environmental changes; the signal processing and analysis module is used to use the signal processing unit to reduce noise and extract features of the collected signals, and judge the insulation performance status by analyzing the characteristic values; the detection report generation module is used to generate a detection report containing insulation status, fault type and maintenance suggestions based on the analysis results.

[0025] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of a method for zero value detection of an inductive suspension ceramic insulator.

[0026] A computer-readable storage medium stores a computer program, which implements the steps of a zero-value detection method for an inductive suspension ceramic insulator when executed by a processor.

[0027] Beneficial effects of the present invention: The inductive suspended ceramic insulator zero value detection method provided by the present invention collects electrical signals and optical signals at both ends of the insulator through an inductive component, and adjusts the collection sensitivity in real time to adapt to environmental changes, thereby improving the accuracy and reliability of signal collection and the ability to adjust receiving parameters in a dynamic state, optimizing the signal receiving efficiency under extreme environments, and laying a solid foundation for subsequent signal processing and analysis. The signal processing unit is used to reduce noise and extract features of the collected signals, and the insulation performance state is judged by analyzing characteristic values. By comparing and analyzing the characteristic values, the insulation performance state of the insulator can be accurately judged, thereby improving the accuracy of insulation performance state judgment and providing reliable data support for maintenance decisions. A detection report is generated based on the analysis results, and the potential risks of insulation performance are evaluated to generate maintenance suggestions, thereby improving maintenance efficiency and response speed. The potential risks of insulation performance are evaluated in combination with environmental parameters, providing a scientific basis for preventive maintenance. The present invention achieves better results in signal collection adaptability, signal processing and analysis accuracy, and maintenance decision support. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0029] Figure 1 An overall flow chart of a zero-value detection method for an inductive suspension ceramic insulator provided in the first embodiment of the present invention.

[0030] Figure 2 An insulator zero value detection sample diagram of an inductive suspension ceramic insulator zero value detection method provided in the second embodiment of the present invention.

[0031] Figure 3 An overall flow chart of an inductive suspension ceramic insulator zero value detection system provided for the third embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0033] Example 1, reference Figure 1, as an embodiment of the present invention, provides a method for detecting zero value of an inductive suspension ceramic insulator, comprising:

[0034] S1: The electrical and optical signals at both ends of the insulator are collected through the sensing component, and the collection sensitivity is adjusted in real time to adapt to environmental changes.

[0035] Furthermore, the electrical signals and optical signals at both ends of the insulator are collected through the sensing component, including the sensing component aligning the connection end of the insulator through the signal receiving unit, receiving and capturing the electrical signals and optical signals, and using the adjustment function to enable the device to adapt to different installation angles and environmental conditions. The device uses the filtering function to eliminate noise signals generated by surrounding interference sources and collect valid data. During the collection process, the device sends a prompt message of the signal reception status to the user through the feedback mechanism. The user adjusts the collection position for detection based on the prompt message. During the collection process, the device continuously monitors the signal quality and dynamically adjusts the receiving parameters.

[0036] It should be noted that real-time adjustment of the acquisition sensitivity to adapt to environmental changes includes the built-in automatic adjustment function of the device, which dynamically optimizes the signal acquisition threshold by monitoring the surrounding signal strength and background noise level.

[0037] When the target signal collected is strong, the device automatically reduces the receiving sensitivity to avoid signal overload;

[0038] When the target signal is weak or the background noise is high, the device enhances sensitivity to accurately capture the valid signal.

[0039] In extreme environments, when humidity is high or noise is loud, the device further optimizes signal reception efficiency through real-time adjustments to environmental data and provides a manual adjustment function, allowing users to manually adjust the sensitivity parameters of signal acquisition according to specific working conditions.

[0040] It should also be noted that the specific steps for dynamically optimizing the signal acquisition threshold are as follows: First, the system's built-in automatic adjustment function continuously monitors the surrounding signal strength and background noise level through the signal receiving unit of the sensing component, and performs quantitative analysis of the signal strength and noise level, where the signal strength is measured in decibels (dB) and the background noise level is also measured in decibels (dB); the device automatically adjusts the specific parameters of the acquisition threshold through an algorithm based on the monitoring data. For example, when the monitored signal strength exceeds the set upper threshold (such as 60dB), the device will reduce the receiving sensitivity to prevent signal overload; conversely, when the signal strength is lower than the set lower threshold (such as 40dB) or the background noise level exceeds a certain threshold (such as 50dB), the device will automatically adjust the receiving sensitivity to prevent signal overload. ), the device will increase the receiving sensitivity to ensure the accurate capture of valid signals. The device has the function of environmental data monitoring. When environmental parameters such as humidity exceeding 70% or noise level exceeding 60dB are detected, the system will further refine the threshold adjustment strategy, for example, by fine-tuning the gain of the signal amplifier or changing the cutoff frequency of the filter to adapt to extreme environmental conditions. The adjustments are performed through the built-in processor of the device without external intervention, ensuring the continuity and stability of signal acquisition. During the threshold adjustment process, the device will also record the parameter changes of each adjustment to facilitate subsequent data analysis and system optimization. The device can optimize the signal acquisition threshold in real time to adapt to changing environmental conditions, thereby improving the accuracy and reliability of signal acquisition.

[0041] It should also be noted that the electrical and optical signals at both ends of the insulator are collected through the sensing component, and the collection sensitivity is adjusted in real time to adapt to environmental changes, thereby realizing comprehensive monitoring of the insulator status. The simultaneous collection of electrical and optical signals can more accurately reflect the actual working status of the insulator. These two signals can reveal the performance of the insulator from different angles. The function of adjusting the collection sensitivity in real time enables the equipment to adapt to various complex environmental conditions, such as different installation angles, temperature changes, humidity changes, etc., thereby ensuring the stability and reliability of signal collection. The feedback mechanism sends prompt information about the signal reception status to the user, and the user can adjust the collection position according to this information, ensuring the accuracy of signal collection and improving the signal collection efficiency. Even in extreme environments, such as high humidity or strong noise interference, the signal reception efficiency can be optimized by dynamically adjusting the receiving parameters, thereby providing a high-quality data basis for subsequent signal processing and analysis.

[0042] S2: Use the signal processing unit to reduce noise and extract features from the collected signals, and determine the insulation performance status by analyzing the characteristic values.

[0043] Furthermore, the signal processing unit is used to perform noise reduction and feature extraction on the collected signals. After the device receives the signal, the denoising function is used to pre-process the data, and non-target signals are eliminated through an efficient noise reduction algorithm. The device extracts the time characteristics and frequency characteristics of the signal, including the change curve of the signal strength, duration and spectrum distribution. In the analysis stage, the device compares the extracted characteristic values ​​with the preset reference standards, and determines the state of the target insulator by the difference. All processing of the entire process is automatically completed by the device, and the processed signal characteristics are stored as data files for subsequent query and verification.

[0044] It should be noted that judging the insulation performance status by analyzing characteristic values ​​includes the device judging whether the insulation performance of the target insulator is within a normal range by comparing and analyzing the amplitude, spectrum characteristics and duration of the collected signal.

[0045] When the signal strength exceeds the normal value and lasts for a short time, the system determines that the insulator may have internal breakdown.

[0046] When the spectrum distribution shows periodic peaks accompanied by weak signal fluctuations, it is judged to be performance degradation caused by surface contamination.

[0047] After completing the status analysis, the equipment stores the abnormal characteristics in the defect database and generates corresponding risk level labels. It uses preset algorithm rules to automatically complete the analysis process without the operator providing additional input. The analysis results are directly output as the basis for insulator maintenance and repair.

[0048] It should also be noted that the efficient noise reduction algorithm includes: using the fast Fourier transform (FFT) algorithm to perform spectrum analysis on the collected signal, identifying and eliminating noise components that are significantly different from the target signal spectrum, such as power frequency interference and environmental noise, using a noise reduction method based on wavelet transform, selecting a suitable wavelet basis and decomposition level, performing multi-scale decomposition on the signal, separating the signal from the noise, and then removing the noise component through soft threshold or hard threshold processing, applying an adaptive filter to dynamically adjust the filter coefficients according to the statistical characteristics of the signal and noise to minimize the mean square error of the output signal, thereby effectively suppressing non-target signals. In the implementation process, the system first The collected signals are preprocessed, including removing DC components and linear trends, and then the FFT algorithm is applied for preliminary noise reduction. Then the wavelet transform is used to perform deeper noise reduction on the signal. During the filtering process, the system will monitor the filtering effect in real time, and automatically adjust the algorithm parameters such as the selection of wavelet basis and threshold size by comparing the signal quality before and after filtering to ensure the noise reduction effect while retaining the true characteristics of the target signal. The system will output the signal after noise reduction for subsequent feature extraction and analysis. Through the comprehensive application of these algorithms, the system can effectively eliminate non-target signals from complex backgrounds and improve the accuracy and efficiency of signal processing.

[0049] It should also be noted that normal values ​​include standard electrical parameters, mechanical performance indicators and environmental adaptability range of insulators. The process of confirming normal values ​​first involves in-depth research on insulator materials and production processes to establish their theoretical performance limits. Preferred Option 1: Historical data analysis, by collecting and analyzing a large amount of historical operating data of insulators, determine the performance fluctuation range under different working conditions, and use this as a reference for normal values; Preferred Option 2: Laboratory testing, subjecting insulator samples to a series of standard tests, such as withstand voltage testing, leakage current testing and mechanical strength testing, to obtain their performance indicators under ideal conditions; Third, on-site calibration, using high-precision testing equipment to conduct on-site calibration of insulators. The system uses actual measurements and adjusts the laboratory data in combination with environmental parameters (such as temperature, humidity, and pollution level) to determine the normal value under the actual working environment. During the implementation process, the system uses statistical process control (SPC) methods to monitor data distribution and defines the normal value range by calculating the mean, standard deviation, and control limits. For data points that exceed the control limits, the system will mark them and trigger further diagnostic processes. In order to adapt to different working environments and insulator types, the system has designed a self-learning mechanism that continuously collects field data and dynamically updates the normal value range to optimize detection accuracy. These steps and schemes not only ensure that the determination of normal values ​​is based on scientific methods, but also can adapt to changes in actual operating conditions.

[0050] It should also be noted that the preset algorithm rules specifically include the following preferred solutions: using a pattern recognition algorithm based on machine learning, establishing an insulator state recognition model by training a large number of data samples with known states, and the preferred algorithms include support vector machine (SVM) and random forest (RandomForest). These two algorithms can effectively process high-dimensional data and improve classification accuracy. The specific steps include data preprocessing, such as standardization and normalization, followed by feature selection and model training; in the model training stage, the system will use cross-validation methods to optimize model parameters to ensure the generalization ability of the model; for the identification of fault types, the convolutional neural network (CNN) algorithm in deep learning is used to automatically extract complex features from signal data and classify them through a multi-layer neural network. CNN The training process includes forward propagation and back propagation, and the weights of the network are adjusted through multiple iterations until the predetermined accuracy or number of iterations is reached. In order to dynamically adjust the signal acquisition threshold, the system adopts an adaptive threshold algorithm to automatically adjust the threshold according to the real-time statistical characteristics of the signal energy, such as the mean and standard deviation, monitor the signal energy distribution in real time, and periodically update the threshold parameters. In order to generate maintenance recommendations, the system adopts a decision tree algorithm to map the analysis results to specific maintenance operations based on preset logical rules. For example, when an internal breakdown is identified, the decision tree will output a high-risk mark and recommend immediate replacement. For surface contamination, cleaning or regular review is recommended. The design and implementation of algorithm rules ensure the accuracy and practicality of the test report, while reducing manual intervention and improving the level of automation.

[0051] It should also be noted that the signal processing unit is used to reduce noise and extract features from the collected signals, and the insulation performance status is judged by analyzing the characteristic values, which improves the accuracy of the insulator status assessment. The data is preprocessed through the denoising function, and the efficient noise reduction algorithm eliminates non-target signals, reduces the interference of noise on signal analysis, and ensures the accuracy of feature extraction. The equipment extracts the time characteristics and frequency characteristics of the signal, including the change curve of the signal strength, duration and spectrum distribution. The extraction of these features provides rich information for the judgment of the insulator status. In the analysis stage, the extracted characteristic values ​​are compared with the preset reference standards, and the status of the target insulator is judged by the difference. This process is completed automatically, which greatly improves the detection efficiency. The processed signal characteristics are stored as data files for subsequent query and verification, which not only improves the traceability of the detection data, but also improves the accuracy and efficiency of the insulator status assessment, providing reliable technical support for the maintenance and repair of insulators.

[0052] S3: Generate a test report based on the analysis results, evaluate the potential risks of insulation performance and generate maintenance recommendations.

[0053] Furthermore, the detection report includes the integration of analysis data into the report after the equipment completes the signal analysis. The report content includes the information of the target insulator, the current status, fault characteristics and maintenance suggestions. The equipment generates a trend analysis chart based on the historical detection data to display the long-term change trajectory of the insulation performance. For the detected abnormal conditions, the report sorts the maintenance suggestions according to the fault risk priority. The report is sent to the remote management system in real time via wireless transmission, or is used by on-site maintenance personnel through the local storage of the equipment.

[0054] It should be noted that the test report also includes the equipment's assessment of potential risks to insulation performance in combination with the parameters of temperature, humidity, and wind speed in the environment where the target insulator is located.

[0055] In areas with higher humidity, the device performs a weighted assessment of the risk of surface contamination and generates cleaning recommendations in a prioritized manner.

[0056] In high-temperature areas, the system highlights the possibility of insulation material degradation and generates a replacement plan.

[0057] The device analyzes the historical inspection data of insulators and uses trend analysis to predict the speed of their performance degradation. If the insulator is expected to reach a critical value within a future inspection cycle, it is recommended to perform maintenance or replacement in advance. The maintenance recommendations are generated based on a dynamic evaluation model, and the generation logic is optimized through an external fault case library.

[0058] It should also be noted that a test report containing insulation status, fault type and maintenance recommendations is generated based on the analysis results, providing comprehensive and intuitive decision support for the maintenance and management of insulators. The report content not only includes the basic information, current status and fault characteristics of the target insulator, but also provides trend analysis charts based on historical detection data, showing the long-term change trajectory of insulation performance, which helps maintenance personnel understand the performance degradation trend of insulators and make more scientific maintenance decisions. For detected abnormal conditions, the report sorts the maintenance recommendations according to the fault risk priority, such as marking internal breakdown as high risk and recommending immediate replacement, while cleaning or re-inspection is recommended for surface contamination, ensuring the rational allocation of maintenance resources and prioritizing the most serious problems. The wireless transmission and local storage functions of the report enable maintenance personnel to obtain the test report in real time or on-site, improving the maintenance response speed, and combining environmental parameters to evaluate the potential risks of insulation performance, providing a more accurate basis for the generation of maintenance recommendations, effectively improving the level of intelligent maintenance management of insulators, and reducing the risk of power grid accidents caused by insulation failures.

[0059] Example 2, reference Figure 2, which is an embodiment of the present invention, provides an inductive suspension ceramic insulator zero value detection method. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0060] First, six representative insulator samples were selected, marked as X1 to X6, which cover different materials, structures and application scenarios. In order to simulate the actual operating environment, the test was carried out in an indoor climate-controlled laboratory, which can accurately control the temperature and humidity. The test steps are as follows: sample preparation, each insulator sample was installed on a dedicated test rack to ensure that the connection end was aligned with the signal receiving unit of the sensing component and maintained a fixed distance. System initialization, start the monitoring system, perform self-test to ensure that all components are working properly, and the system's built-in environmental sensor begins to record the initial temperature and humidity data; signal acquisition, the system starts to collect electrical and optical signals, and the initial acquisition sensitivity is the preset medium level. The built-in filtering function of the signal receiving unit is immediately activated to eliminate background noise; environmental change simulation, the laboratory environmental control system gradually adjusts the temperature and humidity to simulate the change from standard environment (25°C, 45%RH) to extreme environment (40°C, 80%RH); dynamic Adjustment: As environmental parameters change, the system automatically monitors signal strength and noise level, and dynamically adjusts the acquisition threshold through a built-in algorithm. When humidity rises and signal strength decreases, the system increases acquisition sensitivity to ensure the capture of effective signals. Data recording: The system records the adjusted signal strength, noise level, acquisition threshold and other parameters in real time, and transmits the data to the central processing unit. User interaction: The system provides real-time feedback on the signal reception status to the test operator through the display screen, and the operator adjusts the position of the sensing component based on the feedback to optimize signal reception. Repeated tests: Under each environmental condition, the system repeatedly collects signals three times to ensure data reliability and repeatability. Data analysis: After the acquisition is completed, the signal processing unit is used to reduce noise and extract features from the data, and the status of the insulator is determined by comparing the feature values ​​with the preset standards. Report generation: Based on the analysis results, the system generates a test report containing insulation status, fault type and maintenance recommendations, and sends it to the management terminal via a wireless network. Figure 2 This is a sample diagram of insulator zero value detection. It can be obtained from the experimental results that the present invention can effectively adjust the acquisition sensitivity according to environmental changes, ensure the stability and reliability of signal acquisition, and has superiority and innovation.

[0061] Example 3, reference Figure 3 , as an embodiment of the present invention, provides an inductive suspension ceramic insulator zero value detection system, including a sensitivity adjustment module, a signal processing and analysis module, and a detection report generation module.

[0062] The sensitivity adjustment module is used to collect electrical signals and optical signals at both ends of the insulator through the sensing component, and adjust the collection sensitivity in real time to adapt to environmental changes; the signal processing and analysis module is used to use the signal processing unit to reduce noise and extract features of the collected signals, and judge the insulation performance status by analyzing the characteristic values; the test report generation module is used to generate a test report containing insulation status, fault type and maintenance recommendations based on the analysis results.

[0063] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0064] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0065] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0066] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0067] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for detecting zero value of an inductive suspension ceramic insulator, characterized in that: include: The electrical and optical signals at both ends of the insulator are collected through the sensing components, and the collection sensitivity is adjusted in real time to adapt to environmental changes; The signal processing unit is used to reduce noise and extract features from the collected signals, and the insulation performance status is determined by analyzing the characteristic values; Generate a test report based on the analysis results, evaluate the potential risks of insulation performance and generate maintenance recommendations.

2. The method for detecting zero value of an inductive suspension ceramic insulator according to claim 1, characterized in that: The collecting of electrical signals and optical signals at both ends of the insulator by means of the sensing component includes aligning the sensing component with the connection end of the insulator through the signal receiving unit, receiving and capturing the electrical signals and optical signals, and using the adjustment function to enable the device to adapt to different installation angles and environmental conditions. The device removes noise signals generated by surrounding interference sources through the filtering function and collects valid data. During the collection process, the device sends a prompt message of the signal reception status to the user through the feedback mechanism, and the user adjusts the collection position for detection based on the prompt message. During the collection process, the device continuously monitors the signal quality and dynamically adjusts the receiving parameters.

3. The method for detecting zero value of an inductive suspension ceramic insulator according to claim 2, characterized in that: The real-time adjustment of the acquisition sensitivity to adapt to environmental changes includes a built-in automatic adjustment function of the device, which dynamically optimizes the signal acquisition threshold by monitoring the surrounding signal strength and background noise level; When the target signal collected is strong, the device automatically reduces the receiving sensitivity to avoid signal overload; When the target signal is weak or the background noise is high, the device increases sensitivity to accurately capture the effective signal; In extreme environments, when humidity is high or noise is loud, the device further optimizes signal reception efficiency through real-time adjustments to environmental data and provides a manual adjustment function, allowing users to manually adjust the sensitivity parameters of signal acquisition according to specific working conditions.

4. The method for detecting zero value of an inductive suspension ceramic insulator according to claim 3, characterized in that: The method of using the signal processing unit to perform noise reduction and feature extraction on the collected signal includes: after the device receives the signal, using the noise reduction function to pre-process the data, eliminating non-target signals through an efficient noise reduction algorithm, and the device extracts the time characteristics and frequency characteristics of the signal, including the change curve of the signal strength, the duration and the spectrum distribution. In the analysis stage, the device compares the extracted characteristic values ​​with the preset reference standard, and determines the state of the target insulator through the difference. All processing of the whole process is automatically completed by the device, and the processed signal characteristics are stored as a data file for subsequent query and verification.

5. The method for detecting zero value of an inductive suspension ceramic insulator according to claim 4, characterized in that: The determining of the insulation performance status by analyzing the characteristic value includes the device determining whether the insulation performance of the target insulator is within a normal range by comparing and analyzing the amplitude, spectrum characteristics and duration of the collected signal; When the signal strength exceeds the normal value and lasts for a short time, the system determines that the insulator may have internal breakdown; When the spectrum distribution shows periodic peaks accompanied by weak signal fluctuations, it is judged to be performance degradation caused by surface contamination; After completing the status analysis, the equipment stores the abnormal characteristics in the defect database and generates corresponding risk level labels. It uses preset algorithm rules to automatically complete the analysis process without the operator providing additional input. The analysis results are directly output as the basis for insulator maintenance and repair.

6. The method for detecting zero value of an inductive suspension ceramic insulator according to claim 5, characterized in that: The detection report includes the integration of analysis data into the report after the equipment completes the signal analysis. The report content includes the information of the target insulator, the current status, fault characteristics and maintenance suggestions. The equipment generates a trend analysis chart based on the historical detection data to display the long-term change trajectory of the insulation performance. For the detected abnormal conditions, the report sorts the maintenance suggestions according to the fault risk priority. The report is sent to the remote management system in real time via wireless transmission, or is used by on-site maintenance personnel through the local storage of the equipment.

7. The method for detecting zero value of an inductive suspension ceramic insulator according to claim 6, characterized in that: The test report also includes an evaluation of the potential risk of insulation performance by the equipment in combination with the parameters of temperature, humidity and wind speed of the environment where the target insulator is located; In areas with high humidity, the device performs a weighted assessment of the risk of surface contamination and generates cleaning recommendations in a prioritized manner; In high-temperature areas, the system highlights the possibility of insulation material aging and generates a replacement plan; The device analyzes the historical inspection data of insulators and uses trend analysis to predict the speed of their performance degradation. If the insulator is expected to reach a critical value within a future inspection cycle, it is recommended to perform maintenance or replacement in advance. The maintenance recommendations are generated based on a dynamic evaluation model, and the generation logic is optimized through an external fault case library.

8. A system using the zero value detection method of an inductive suspension ceramic insulator according to any one of claims 1 to 7, characterized in that: It includes sensitivity adjustment module, signal processing and analysis module, and detection report generation module; The sensitivity adjustment module is used to collect electrical signals and optical signals at both ends of the insulator through the sensing component, and adjust the collection sensitivity in real time to adapt to environmental changes; The signal processing and analysis module is used to use the signal processing unit to perform noise reduction and feature extraction on the collected signal, and to determine the insulation performance status by analyzing the characteristic value; The test report generation module is used to generate a test report including insulation status, fault type and maintenance suggestions according to the analysis results.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for zero value detection of an inductive suspension ceramic insulator according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for zero-value detection of an inductive suspension ceramic insulator according to any one of claims 1 to 7 are implemented.

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