Methods and systems for assessing the insulation aging of cable accessories

Abstract

This application provides a method and system for assessing the insulation aging of cable accessories. The method determines the internal degradation characteristic parameters of the target cable accessory through micro-vibration signals during the excitation process; determines the degradation gradient of the target cable accessory under hydrolytic aging effect based on the degradation characteristic parameters and the ambient humidity of the target cable accessory; determines the dielectric decay trend of the insulation aging of the target cable accessory during operation based on the degradation gradient and the electric field characteristics of the target cable accessory; determines the cumulative thermal fatigue loss of the target cable accessory due to temperature based on the coupling correlation between all monitored surface temperatures and the micro-vibration signals; and assesses the insulation state of the target cable accessory based on the dielectric decay trend and the cumulative thermal fatigue loss, obtaining an assessment index for the insulation aging of the target cable accessory. Using this method, the impact of internal micro-degradation propagation on the assessment of the insulation aging of the target cable accessory can be reduced.

Description

Technical Field

[0001] This application relates to the field of aging assessment technology, and more specifically, to a method and system for assessing the insulation aging of cable accessories. Background Technology

[0002] Aging assessment is a technical process that involves real-time monitoring and analysis of various physical and chemical parameters of equipment during operation to determine the degree of performance degradation and remaining lifespan, providing a scientific basis for equipment operation and maintenance strategy formulation, fault prediction, and safe and stable operation of the power grid.

[0003] As a key component connecting cables and equipment in power systems, cable accessories' insulation aging directly affects the reliability of power grid operation. Existing insulation aging assessment methods mostly rely on monitoring single physical quantities, such as dielectric response or temperature measurement, which cannot comprehensively reflect the aging mechanism of cable accessories under the combined effects of multiple factors (such as electric field, humidity, and temperature). Traditional contact testing requires power outage and disassembly of equipment, resulting in blind spots and the inability to track aging dynamics in real time. Although non-contact testing technology has made some progress, it lacks sensitivity to early micro-deterioration and minor local defects in the internal physical structure of insulation materials, which limits the accuracy and timeliness of aging state assessment. Therefore, how to reduce the impact of internal micro-deterioration expansion on the insulation aging of the target cable accessories has become a problem faced by the industry. Summary of the Invention

[0004] This application provides a method and system for assessing the insulation aging of cable accessories, which can reduce the impact of internal micro-deterioration propagation on the insulation aging of the target cable accessory being assessed.

[0005] In a first aspect, this application provides a method for evaluating the insulation aging of cable accessories, wherein an interdigital electrode assembly is pre-attached close to the surface of a target cable accessory, and an alternating excitation voltage is applied to the interdigital electrode assembly to induce a dielectric response in the target cable accessory. The method includes the following steps:

[0006] Micro-vibration signals of the target cable accessories during the excitation process are collected using piezoelectric vibration sensors;

[0007] Deterioration characteristic parameters inside the target cable accessory are extracted from the micro-vibration signal;

[0008] The insulation degradation state of the target cable accessory is analyzed by gradient analysis based on the degradation characteristic parameters and the ambient humidity of the target cable accessory to obtain the degradation gradient of the target cable accessory under the hydrolytic aging effect. Based on the degradation gradient and the electric field characteristics of the target cable accessory, the dielectric decay trend of the insulation aging of the target cable accessory during operation is determined.

[0009] The surface temperature of the target cable accessory is monitored by a temperature sensor, and the cumulative thermal fatigue loss of the target cable accessory due to temperature is determined based on the coupling correlation between all the monitored surface temperatures and the micro-vibration signal.

[0010] The insulation condition of the target cable accessory is assessed by evaluating the dielectric decay trend and the cumulative thermal fatigue loss, resulting in an evaluation index for the insulation aging of the target cable accessory.

[0011] In some embodiments, extracting degradation characteristic parameters of the target cable accessory from the micro-vibration signal specifically includes:

[0012] The micro-vibration signal is subjected to noise reduction processing to obtain the processed micro-vibration signal;

[0013] The degradation characteristic parameters inside the target cable accessory are determined based on the processed micro-vibration signal.

[0014] In some embodiments, gradient analysis of the insulation degradation state in the target cable accessory is performed based on the degradation characteristic parameters and the ambient humidity of the target cable accessory to obtain the degradation gradient of the target cable accessory under hydrolytic aging effect, specifically including:

[0015] Monitor the ambient humidity of the target cable accessories;

[0016] The insulation layer of the target cable accessory is divided into layers to obtain multiple insulation layers of the target cable accessory;

[0017] The defect degree of each insulation layer is determined based on the aforementioned degradation characteristic parameters;

[0018] The degradation gradient of the target cable accessory under hydrolytic aging effect is determined based on the defect degree of each insulation layer and the ambient humidity.

[0019] In some embodiments, determining the dielectric degradation trend of insulation aging of the target cable accessory during operation based on the degradation gradient and the electric field characteristics of the target cable accessory specifically includes:

[0020] Determine the electric field characteristics of the target cable accessories;

[0021] The electric field distortion region of the target cable accessory is determined based on the degradation gradient and the electric field characteristics;

[0022] Obtain the frequency domain dielectric response of the target cable accessory at different aging stages;

[0023] The dielectric attenuation trend of insulation aging of the target cable accessories during operation is determined based on the electric field distortion region and the frequency domain dielectric response under different aging degrees.

[0024] In some embodiments, determining the cumulative thermal fatigue loss of the target cable accessory due to temperature based on the coupling correlation between all monitored surface temperatures and the micro-vibration signals specifically includes:

[0025] The correlation analysis between all the monitored surface temperatures and the micro-vibration signal was performed to obtain the coupling correlation between all the monitored surface temperatures and the micro-vibration signal;

[0026] Determine the fluctuation characteristics of all monitored surface temperatures;

[0027] The cumulative thermal fatigue loss of the target cable accessory due to temperature is determined based on the coupling relationship and the fluctuation characteristics.

[0028] In some embodiments, the insulation condition of the target cable accessory is assessed by the dielectric decay trend and the cumulative thermal fatigue loss, and the resulting assessment index for the insulation aging of the target cable accessory specifically includes:

[0029] The dielectric aging characteristics of the insulation state of the target cable accessory are determined based on the dielectric decay trend.

[0030] The evaluation index of insulation aging of the target cable accessory is determined by the dielectric aging characteristics and the cumulative loss of thermal fatigue.

[0031] In some embodiments, the surface temperature of the target cable accessory is monitored by a non-contact infrared temperature sensor.

[0032] Secondly, this application provides a cable accessory insulation aging assessment system, comprising:

[0033] The acquisition module is used to acquire the micro-vibration signals of the target cable accessory during the excitation process using a piezoelectric vibration sensor;

[0034] The processing module is used to extract the degradation characteristic parameters inside the target cable accessory from the micro-vibration signal;

[0035] The processing module is further configured to perform gradient analysis on the insulation degradation state of the target cable accessory based on the degradation characteristic parameters and the ambient humidity of the target cable accessory, to obtain the degradation gradient of the target cable accessory under the hydrolytic aging effect, and to determine the dielectric decay trend of the insulation aging of the target cable accessory during operation based on the degradation gradient and the electric field characteristics of the target cable accessory.

[0036] The processing module is also used to monitor the surface temperature of the target cable accessory by a temperature sensor, and determine the cumulative thermal fatigue loss of the target cable accessory due to temperature based on the coupling correlation between all the monitored surface temperatures and the micro-vibration signal.

[0037] The execution module is used to perform an aging assessment of the insulation status of the target cable accessory based on the dielectric decay trend and the cumulative thermal fatigue loss, and to obtain an assessment index of the insulation aging of the target cable accessory.

[0038] Thirdly, this application provides a computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described cable accessory insulation aging assessment method.

[0039] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for evaluating the insulation aging of cable accessories.

[0040] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0041] The cable accessory insulation aging assessment method and system provided in this application firstly acquires micro-vibration signals of the target cable accessory during the excitation process using a piezoelectric vibration sensor; deterioration characteristic parameters inside the target cable accessory are extracted from the micro-vibration signals; gradient analysis of the insulation deterioration state in the target cable accessory is performed based on the deterioration characteristic parameters and the ambient humidity of the target cable accessory to obtain the deterioration gradient of the target cable accessory under the hydrolytic aging effect; based on the deterioration gradient and the electric field characteristics of the target cable accessory, the dielectric decay trend of the insulation aging of the target cable accessory during operation is determined; the surface temperature of the target cable accessory is monitored by a temperature sensor, and the cumulative thermal fatigue loss of the target cable accessory due to temperature is determined based on the coupling correlation between all monitored surface temperatures and the micro-vibration signals; the insulation state of the target cable accessory is assessed by the dielectric decay trend and the cumulative thermal fatigue loss to obtain the insulation aging assessment index of the target cable accessory.

[0042] Therefore, this application, in the process of assessing the insulation aging of cable accessories, accurately collects micro-vibration signals during the excitation process of the target cable accessories using piezoelectric vibration sensors. This allows for the sensitive capture of subtle vibration changes caused by the expansion of internal micro-deterioration. Deterioration characteristic parameters are extracted from these signals, and combined with environmental humidity for degradation gradient analysis. This effectively eliminates the interference of environmental factors on the extraction of degradation characteristics and clearly defines the hierarchical state of degradation development under hydrolytic aging effects. Based on the degradation gradient and electric field characteristics, the dielectric decay trend is determined, quantifying the impact of degradation expansion on insulation performance from the perspective of electrical performance changes, avoiding the one-sidedness of single vibration signal analysis. Simultaneously, by monitoring surface temperature with a temperature sensor and establishing a coupling correlation with the micro-vibration signals, the cumulative loss from thermal fatigue is accurately assessed, constructing a multi-dimensional assessment system covering mechanical vibration, environmental humidity, electric field characteristics, and temperature effects. This comprehensively and meticulously characterizes the internal micro-deterioration expansion process and its coupling mechanism with insulation aging, effectively reducing the impact of environmental variables and temperature stress interference factors on the assessment results during the degradation expansion process. Using the above scheme, the impact of internal micro-deterioration expansion on the insulation aging of the target cable accessories can be reduced. Attached Figure Description

[0043] Figure 1 This is an exemplary flowchart of a cable accessory insulation aging assessment method according to some embodiments of this application;

[0044] Figure 2 This is a schematic diagram illustrating the connection between a cable accessory and a cable according to some embodiments of this application;

[0045] Figure 3 This is an exemplary flowchart illustrating the determination of degradation gradient according to some embodiments of this application;

[0046] Figure 4 This is a schematic diagram of the structure of a cable accessory insulation aging assessment system according to some embodiments of this application;

[0047] Figure 5 This is a schematic diagram of the structure of a computer device for implementing a cable accessory insulation aging assessment method according to some embodiments of this application. Detailed Implementation

[0048] To better understand the technical solution of this application, the technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0049] refer to Figure 1 The figure is an exemplary flowchart of a cable accessory insulation aging assessment method according to some embodiments of this application. The cable accessory insulation aging assessment method 100 mainly includes the following steps:

[0050] In some embodiments, the interdigital electrode assembly can be pre-attached close to the surface of the target cable accessory by using a non-metallic bracket to fix the interdigital electrodes (materials can be copper or aluminum), adjusting the electrode spacing according to the size of the cable accessory (typically 0.5-2cm), and attaching the interdigital electrode assembly close to the cable surface (spacing ≤1mm) to avoid damaging the insulation layer. Applying an alternating excitation voltage to the interdigital electrode assembly to excite the dielectric response of the target cable accessory can be achieved by using a function generator to output a sinusoidal alternating voltage with a frequency of 10Hz-100kHz (amplitude adjustable from 5-50V), which is then applied to the interdigital electrodes via a power amplifier to excite the dielectric response inside the cable accessory. Other methods can be used in other embodiments, which are not limited here.

[0051] In some embodiments, reference Figure 2 As shown, this figure is a schematic diagram of the connection between the cable accessory and the cable in some embodiments of this application, such as... Figure 2 The white part represents cable accessories, and the black part represents the cable itself. The cable accessories are used to connect, protect, seal, and insulate the cable.

[0052] In step 101, the micro-vibration signal of the target cable accessory during the excitation process is acquired by a piezoelectric vibration sensor.

[0053] In specific implementation, the micro-vibration signal of the target cable accessory during the excitation process can be acquired by using a piezoelectric vibration sensor in the following way: a piezoelectric accelerometer with high sensitivity and a wide frequency response range (such as a model with sensitivity ≥100mV / g and frequency response 0.5-10kHz) is selected and fixed to a key part of the target cable accessory (such as a stress cone or insulating tube) with a coupling agent. After applying an alternating excitation voltage to the interdigital electrode assembly, the insulating material of the cable accessory is made to vibrate slightly based on the electrostatic excitation principle, and the micro-vibration signal of the target cable accessory during the excitation process is acquired by the piezoelectric vibration sensor. Other acquisition methods can also be used in other embodiments, which are not limited here.

[0054] It should be noted that the micro-vibration signal in this application refers to the signal of the target cable accessory during micro-vibration during the excitation process, which can be used to analyze the internal state of the target cable accessory.

[0055] In step 102, the degradation characteristic parameters inside the target cable accessory are extracted from the micro-vibration signal.

[0056] In some embodiments, extracting the degradation characteristic parameters inside the target cable accessory from the micro-vibration signal can be achieved by the following steps:

[0057] The micro-vibration signal is subjected to noise reduction processing to obtain the processed micro-vibration signal;

[0058] The degradation characteristic parameters inside the target cable accessory are determined based on the processed micro-vibration signal.

[0059] In specific implementation, in the post-processing stage, high-frequency noise (>5kHz) and low-frequency baseline drift (<0.5kHz) in the micro-vibration signal are removed by setting a threshold (such as soft thresholding) to obtain the denoised time-domain signal. Then, a moving average filter is used to smooth the denoised time-domain signal, with a window size of 10-20 sampling points to further eliminate random interference. The signal obtained after smoothing is used as the processed micro-vibration signal. In the feature extraction stage, the kurtosis value of the processed micro-vibration signal is calculated in the time domain. Kurtosis values ​​exceeding 5 are considered anomalous kurtosis values. When the kurtosis value exceeds 5, impact vibration is identified, corresponding to a degradation propagation event. The processed signal is then processed using a fast Fourier transform. The processed micro-vibration signal is converted to the frequency domain, and the energy proportion of the dominant frequency and its harmonics in this frequency domain is extracted. When the degradation extends, the energy proportion of high-frequency components (>2kHz) usually increases by more than 20%, and each energy proportion that increases by more than 20% is regarded as an abnormal energy proportion. In the time-frequency domain, wavelet packet decomposition (WPD) is used to decompose the signal into different frequency bands (e.g., 8 frequency bands), and the energy entropy of each frequency band is calculated. This entropy value can reflect the degree of disorder in the distribution of signal components at different frequencies, and can effectively capture the complex vibration change characteristics during the degradation extension process. The set of all abnormal kurtosis values, all abnormal energy proportions, and all energy entropies is used as the degradation characteristic parameters inside the target cable accessory. Other extraction methods can also be used in other embodiments, which are not limited here.

[0060] It should be noted that the degradation characteristic parameters in this application represent the abnormal characteristics of the expansion of internal defects in the target cable accessories, and can be used to analyze the internal degradation of the target cable accessories.

[0061] In step 103, the insulation degradation state of the target cable accessory is analyzed by gradient analysis based on the degradation characteristic parameters and the ambient humidity of the target cable accessory to obtain the degradation gradient of the target cable accessory under the hydrolytic aging effect. Based on the degradation gradient and the electric field characteristics of the target cable accessory, the dielectric decay trend of the insulation aging of the target cable accessory during operation is determined.

[0062] In some embodiments, reference Figure 3 As shown, this figure is an exemplary flowchart for determining the degradation gradient in some embodiments of this application. In this embodiment, the degradation gradient of the insulation in the target cable accessory is analyzed based on the degradation characteristic parameters and the ambient humidity of the target cable accessory. The degradation gradient of the target cable accessory under the hydrolytic aging effect can be obtained by the following steps:

[0063] First, in step 1031, the ambient humidity of the target cable accessories is monitored;

[0064] Secondly, in step 1032, the insulation layer of the target cable accessory is split into multiple insulation layers to obtain multiple insulation layers of the target cable accessory;

[0065] Then, in step 1033, the defect degree of each insulation layer is determined according to the degradation characteristic parameters;

[0066] Subsequently, in step 1034, the degradation gradient of the target cable accessory under hydrolytic aging effect is determined based on the defect degree of each insulation layer and the ambient humidity.

[0067] It should be noted that the hydrolytic aging and degradation characteristic parameters of the target cable accessory insulation material exhibit an environment-damage coupling mechanism. Humidity accelerates the hydrolysis reaction of the target cable accessory insulation material, leading to molecular chain breakage and material embrittlement, which in turn triggers the initiation and expansion of internal micro-degradation. The dynamic evolution of degradation changes the mechanical properties of the material (such as stiffness and damping), causing regular changes in the time-domain impact (kurtosis, peak factor), frequency-domain high-frequency energy distribution (>2kHz), and time-frequency energy entropy characteristics of the micro-vibration signal. Therefore, the degree of abnormality of vibration characteristics (degradation characteristic parameters) and the intensity of the effect of humidity environment together reflect the degree of delamination aging damage of the insulation material (i.e., degradation gradient).

[0068] In specific implementation, firstly, a capacitive humidity sensor is used to monitor the ambient humidity around the target cable accessory in real time, with the data sampling frequency set to 1 time / minute. Then, based on the insulation layer thickness and aging pattern of the target cable accessory, the insulation layer is divided into multiple layers at equal intervals (e.g., each layer is 2mm). Each of the divided layers is used as an insulation layer, where the insulation layer represents the layer of the additional insulation layer of the target cable. In other embodiments, other methods can be used for division, which are not limited here.

[0069] In specific implementation, the defect degree of each insulation layer can be determined according to the degradation characteristic parameters in the following way: the kurtosis, high-frequency energy ratio, and energy entropy in the degradation characteristic parameters are input into a pre-trained random forest regression model (the model is trained using vibration data samples containing different degrees of degradation, and feature selection and node splitting are performed using the Gini index). The degradation probability of each insulation layer is output by the random forest regression model, and each degradation probability is used as the defect degree of the corresponding insulation layer. The defect degree represents the parameter value of the defect degree of each insulation layer in the target cable accessory. Other methods can also be used to determine the defect degree in other embodiments, which are not limited here.

[0070] In specific implementation, the degradation gradient of the target cable accessory under hydrolytic aging effect, based on the defect degree of each insulation layer and the ambient humidity, can be determined in the following way: A humidity acceleration factor is calculated based on a hydrolytic aging kinetic model (introducing humidity as a key parameter into the activation energy calculation). The defect degree of each insulation layer is then weighted and fused with the humidity acceleration factor (e.g., defect degree weight 0.7, humidity acceleration factor weight 0.3) to obtain the defect degree of each insulation layer after weighted fusion. A continuous degradation gradient curve from the surface to the interior of the insulation layer is generated using an interpolation algorithm (e.g., cubic spline interpolation) combined with the defect degree of each insulation layer after weighted fusion. This continuous degradation gradient curve is used as the degradation gradient of the target cable accessory under hydrolytic aging effect. Other methods can also be used in other embodiments, which are not limited here.

[0071] It should be noted that the degradation gradient in this application represents the gradient of the degree of degradation of the target cable accessory under the hydrolytic aging effect. It can be used to visually present the distribution of the insulation degradation state of the cable accessory under the hydrolytic aging effect, which is convenient for analyzing the insulation state of the target cable accessory.

[0072] In some embodiments, determining the dielectric degradation trend of insulation aging of the target cable accessory during operation based on the degradation gradient and the electric field characteristics of the target cable accessory can be achieved by the following steps:

[0073] Determine the electric field characteristics of the target cable accessories;

[0074] The electric field distortion region of the target cable accessory is determined based on the degradation gradient and the electric field characteristics;

[0075] Obtain the frequency domain dielectric response of the target cable accessory at different aging stages;

[0076] The dielectric attenuation trend of insulation aging of the target cable accessories during operation is determined based on the electric field distortion region and the frequency domain dielectric response under different aging degrees.

[0077] It should be noted that the dielectric decay trend of insulation aging of the target cable accessories is determined by the spatiotemporal coupling effect of the material degradation degree and electric field distribution. The degradation gradient reflects the aging damage state at different depths of the insulation layer (such as micro-degradation density and moisture content), while electric field characteristics (such as electric field intensity distribution and partial discharge) can accelerate or inhibit the aging process. The aging rate is faster in high electric field regions (such as stress cone tips), forming a positive feedback mechanism of "damage-electric field enhancement-accelerated degradation". Therefore, by combining the spatial distribution of degradation gradient and the temporal evolution characteristics of electric field, the decay law of dielectric parameters over time (i.e., dielectric decay trend) can be analyzed.

[0078] In specific implementation, the electric field characteristics of the target cable accessory can be determined in the following way: obtain the electric field distribution of the target cable accessory under normal operating conditions from the database corresponding to the target cable accessory, and extract the electric field characteristics of the target cable accessory (such as the location of the maximum field strength and the electric field strength distribution curve) from the electric field distribution based on the field strength statistical characteristic calculation method. The electric field characteristics represent the point electric field characteristics of the target cable accessory during operation. Other methods can also be used to determine the electric field characteristics in other embodiments, which are not limited here.

[0079] In practice, determining the electric field distortion region of the target cable accessory based on the degradation gradient and the electric field characteristics can be achieved in the following way: A three-dimensional electric field simulation model is established using finite element analysis software, combining the geometric structure, material parameters (dielectric constant, conductivity), and operating voltage conditions of the target cable accessory. The degradation gradient and electric field characteristics are imported into this three-dimensional electric field simulation model. The current electric field distribution is output through this three-dimensional electric field simulation model. Since insulation degradation leads to changes in the dielectric properties of the material, resulting in a redistribution of the electric field, a threshold judgment method is used (setting the region where the electric field intensity change exceeds 10% as the distortion region). The electric field distribution is compared with the electric field distribution of the target cable accessory under normal operating conditions. The region where the electric field strength in the current electric field distribution exceeds 10% of the corresponding battery strength in the electric field distribution of the target cable accessory under normal operating conditions is defined as the electric field distortion region of the target cable accessory. The electric field distortion region indicates an area in the target cable accessory where there is an electromagnetic anomaly. Extensive practice in the field of power equipment insulation monitoring shows that a 10% change in electric field strength is a common reference threshold for distinguishing between normal operating conditions and early defects. Other methods may be used to determine this in other embodiments, which are not limited here.

[0080] The frequency domain dielectric response of the target cable accessory at different aging stages can be obtained by means of accelerated aging tests in the laboratory. The frequency domain dielectric response represents the dielectric characteristics (such as dielectric constant and dielectric loss) of the target cable accessory at different frequencies. Other methods can also be used in other embodiments, which are not limited here.

[0081] In specific implementation, determining the dielectric attenuation trend of insulation aging of the target cable accessory during operation based on the electric field distortion region and the frequency domain dielectric response under different aging degrees can be achieved in the following way: After processing the characteristic parameters (such as maximum field strength and field strength gradient) of the electric field distortion region and the frequency domain dielectric response under different aging degrees (removing outliers) using data cleaning in signal processing technology, the processed characteristic parameters of the electric field distortion region and the frequency domain dielectric response under different aging degrees are obtained. A multiple linear regression algorithm is used to construct a multiple linear regression model between the characteristic parameters of the electric field distortion region and the frequency domain dielectric response under different aging degrees, and this model is then implemented using Allan... The Nius equation is used to modify the parameters in the multiple linear regression model, and the modified multiple linear regression model is used as a time-varying dielectric decay model. The characteristic parameters of the processed electric field distortion region and the frequency domain dielectric response under different aging degrees are substituted into the time-varying dielectric decay model. The time-varying dielectric decay model is used to predict the dielectric parameter change trend of the insulation aging of the target cable accessory at different time periods during operation. All dielectric parameter change trends are arranged in chronological order according to the corresponding time periods, and the resulting sequence is used as the dielectric decay trend of the insulation aging of the target cable accessory during operation. Other methods can be used to determine the dielectric decay trend in other embodiments, which are not limited here.

[0082] It should be noted that the dielectric attenuation trend in this application represents the trend of insulation aging attenuation over time during the operation of the target cable accessory. It can be used to predict the aging status of the target cable accessory in advance, so as to take corresponding measures in advance.

[0083] In step 104, the surface temperature of the target cable accessory is monitored by a temperature sensor, and the cumulative thermal fatigue loss of the target cable accessory due to temperature is determined based on the coupling correlation between all the monitored surface temperatures and the micro-vibration signal.

[0084] In specific implementation, the surface temperature of the target cable accessory can be monitored by a temperature sensor in the following way: the temperature sensor can be a non-contact infrared temperature sensor, which can be installed directly above the cable accessory at a distance of 5-10 cm from the accessory surface, and the surface temperature of the target cable accessory can be monitored by the non-contact infrared temperature sensor; wherein, the surface temperature represents the surface temperature of the target cable accessory during operation. In this embodiment, the surface temperature of the target cable accessory is monitored during the time period of detection; in other embodiments, other monitoring methods can also be used, which are not limited here.

[0085] In some embodiments, determining the cumulative thermal fatigue loss of the target cable accessory due to temperature based on the coupling correlation between all monitored surface temperatures and the micro-vibration signals can be achieved through the following steps:

[0086] The correlation analysis between all the monitored surface temperatures and the micro-vibration signal was performed to obtain the coupling correlation between all the monitored surface temperatures and the micro-vibration signal;

[0087] Determine the fluctuation characteristics of all monitored surface temperatures;

[0088] The cumulative thermal fatigue loss of the target cable accessory due to temperature is determined based on the coupling relationship and the fluctuation characteristics.

[0089] It should be noted that the micro-vibration signal contains information on the mechanical deformation of the material caused by thermal expansion and contraction and relaxation of internal stress (such as interface slippage and local deterioration propagation). Temperature changes will cause differences in the thermal expansion coefficient of the material, which will lead to internal stress concentration and thus generate micro-vibration. Conversely, the accumulation of mechanical damage (such as the initiation of deterioration) will change the heat conduction path of the material and affect the temperature distribution. Therefore, the cumulative thermal fatigue loss of the target cable accessory due to temperature can be determined based on the coupling relationship between surface temperature and micro-vibration signal.

[0090] In specific implementation, this application performs correlation analysis on all monitored surface temperatures and the micro-vibration signal to obtain the coupling correlation between all monitored surface temperatures and the micro-vibration signal. This can be achieved in the following way: based on the timestamp, all monitored surface temperatures and micro-vibration signals are strictly aligned to obtain temperature-vibration aligned data. Abnormal data points with misaligned or missing timestamps are removed. The physical coupling strength between temperature and vibration is calculated using a cross-correlation function. The calculated coupling strength is used as a quantitative expression of the coupling correlation. The coupling correlation characterizes the bidirectional physical interaction between temperature and micro-vibration signal, which will not be elaborated here.

[0091] In specific implementation, the fluctuation characteristics of all monitored surface temperatures can be determined in the following way: the amplitude and rate of temperature change of all monitored surface temperatures are calculated using the sliding window method (with a window size of 10 sampling points); the dominant frequency of temperature fluctuations in all monitored surface temperatures is obtained using Fourier transform; and wavelet transform is used to decompose all monitored surface temperatures to extract fluctuation components at different time scales. The combination of temperature change amplitude, rate of change, dominant frequency, and fluctuation components at different time scales is used as the temperature fluctuation characteristics, wherein the temperature fluctuation characteristics represent the degree of fluctuation of the surface temperature of the target cable accessory. Other methods can also be used in other embodiments, which are not limited here.

[0092] In specific implementation, the cumulative thermal fatigue loss of the target cable accessory due to temperature, based on the coupling correlation and the fluctuation characteristics, can be determined in the following way: The damage caused by a single temperature fluctuation is calculated based on the linear cumulative damage theory combined with the fluctuation characteristics. A canonical correlation analysis algorithm is used to project the temperature variable and vibration variable into two sets of orthogonal low-dimensional spaces. By maximizing the correlation coefficient between the two sets of projections, the maximum correlation feature pair (u1, v1) between temperature and micro-vibration signal is found, and the second largest correlation feature pair (u2, v2) is extracted sequentially until the correlation coefficient of the correlation feature pair is lower than a set threshold (e.g., 0.1). Finally, a quantitative correlation model between temperature and micro-vibration signal is established based on the extracted correlation feature pairs. The damage caused by a single temperature fluctuation is weighted and corrected based on this quantitative correlation model combined with the coupling correlation. The damage caused by all temperature fluctuations is accumulated, and the accumulated damage is used as the cumulative thermal fatigue loss of the target cable accessory. Other methods can also be used in other embodiments, which are not limited here.

[0093] It should be noted that the cumulative thermal fatigue loss in this application represents the cumulative loss of thermal fatigue on the target cable accessory, which can be used to analyze the relationship between the target cable accessory and temperature, and facilitate the reduction of the influence of temperature on the insulation condition of the target cable accessory.

[0094] In step 105, the insulation condition of the target cable accessory is evaluated by the dielectric attenuation trend and the cumulative thermal fatigue loss to obtain the evaluation index of insulation aging of the target cable accessory.

[0095] In some embodiments, the insulation condition of the target cable accessory is assessed by evaluating its insulation aging based on the dielectric decay trend and the cumulative thermal fatigue loss. The resulting assessment index for the insulation aging of the target cable accessory can be achieved through the following steps:

[0096] The dielectric aging characteristics of the insulation state of the target cable accessory are determined based on the dielectric decay trend.

[0097] The evaluation index of insulation aging of the target cable accessory is determined by the dielectric aging characteristics and the cumulative loss of thermal fatigue.

[0098] In specific implementation, firstly, a grey prediction model combined with dielectric attenuation trend is used to predict the attenuation trend of future dielectric parameters, obtaining future dielectric parameters for different time periods. Then, the dielectric parameters in the initial state are retrieved from the database corresponding to the target cable accessory. The deviation of each future dielectric parameter from the initial state dielectric parameter is calculated, such as deviation = |(current dielectric parameter − initial dielectric parameter) / initial dielectric parameter|. Each deviation is then used as a dielectric aging characteristic of the insulation state of the target cable accessory. Here, the dielectric aging characteristic represents the dielectric aging feature of the target cable accessory. The aging degree of dielectric parameters in the insulation state is characterized by a larger deviation in the ratio, and the higher the corresponding value of the dielectric aging characteristic. Secondly, the analytic hierarchy process is used to construct a judgment matrix of dielectric aging characteristics and cumulative thermal fatigue loss. By calculating the eigenvectors and the maximum eigenvalue of the matrix, the weight coefficients of the two are determined. The dielectric aging characteristics, cumulative thermal fatigue loss and their corresponding weights are linearly weighted and summed, that is, the evaluation index = dielectric aging characteristic weight × dielectric aging characteristic + cumulative thermal fatigue loss weight × cumulative thermal fatigue loss. The value obtained by the weighted sum is used as the evaluation index of insulation aging of the target cable accessory.

[0099] It should be noted that the evaluation index in this application represents the parameter value of the degree of insulation aging of the target cable accessories during operation, and can be used to provide a comprehensive quantitative basis for predicting the dynamic life of insulation aging.

[0100] It should be noted that the insulation aging status of the target cable accessory can be assessed using the evaluation index, namely: determining the evaluation range of the insulation aging status of the target cable accessory; judging the evaluation index based on the evaluation range; if the evaluation index is less than the lower limit of the evaluation range, the insulation aging status of the target cable accessory is judged to be in a good state; if the evaluation index is within the evaluation range, the insulation aging status of the target cable accessory is judged to be in a warning state; if the evaluation index is greater than the upper limit of the evaluation range, the insulation aging status of the target cable accessory is judged to be in a warning state, and the judgment result is transmitted to the monitoring station of the target cable accessory, and the monitoring station issues a signal of the corresponding insulation aging status so that relevant departments can take corresponding countermeasures.

[0101] Additionally, it should be noted that the evaluation range can be set according to the specific requirements of the target cable accessory. For example, if the target cable accessory is located in an area with a large current, the evaluation range can be set in a high range. If the target cable accessory is located on a branch line, the evaluation range can be set in a low range. In other embodiments, such as when the target cable accessory is located in the main transmission channel, the evaluation range can be set in a high range, thereby improving the safety of the target cable accessory.

[0102] In another aspect, in some embodiments, this application provides a cable accessory insulation aging assessment system, with reference to... Figure 4 The figure is a schematic diagram of the structure of a cable accessory insulation aging assessment system according to some embodiments of this application. The cable accessory insulation aging assessment system 400 includes: a data acquisition module 401, a processing module 402, and an execution module 403, which are described below:

[0103] Acquisition module 401, in this application, is mainly used to acquire the micro-vibration signal of the target cable accessory during the excitation process through a piezoelectric vibration sensor;

[0104] Processing module 402, in this application, is used to extract the degradation characteristic parameters inside the target cable accessory from the micro-vibration signal;

[0105] It should be noted that the processing module 402 in this application is also used to perform gradient analysis on the insulation degradation state of the target cable accessory based on the degradation characteristic parameters and the ambient humidity of the target cable accessory, to obtain the degradation gradient of the target cable accessory under the hydrolytic aging effect, and to determine the dielectric decay trend of the insulation aging of the target cable accessory during operation based on the degradation gradient and the electric field characteristics of the target cable accessory.

[0106] Additionally, it should be noted that the processing module 402 in this application is also used to monitor the surface temperature of the target cable accessory by a temperature sensor, and to determine the cumulative thermal fatigue loss of the target cable accessory due to temperature based on the coupling relationship between all the monitored surface temperatures and the micro-vibration signal.

[0107] The execution module 403 in this application is mainly used to perform an aging assessment of the insulation status of the target cable accessory by means of the dielectric attenuation trend and the cumulative loss of thermal fatigue, and to obtain an assessment index of the insulation aging of the target cable accessory.

[0108] In addition, this application also provides a computer device, the computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described cable accessory insulation aging assessment method.

[0109] In some embodiments, reference Figure 5 The figure is a schematic diagram of the structure of a computer device for implementing a cable accessory insulation aging assessment method according to some embodiments of this application. The cable accessory insulation aging assessment method in the above embodiments can be implemented through... Figure 5 The computer device shown is used to implement this, and the computer device 500 includes at least one processor 501, a communication bus 502, a memory 503, and at least one communication interface 504.

[0110] Processor 501 can be a general-purpose central processing unit (CPU) or an application-specific integrated circuit (ASIC).

[0111] The communication bus 502 can be used to transmit information between the aforementioned components.

[0112] Memory 503 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. Memory 503 may exist independently and be connected to processor 501 via communication bus 502. Memory 503 may also be integrated with processor 501.

[0113] The memory 503 stores program code for executing the scheme of this application, and its execution is controlled by the processor 501. The processor 501 executes the program code stored in the memory 503. The program code may include one or more software modules. The method used in the above embodiments can be implemented by the processor 501 and one or more software modules in the program code in the memory 503.

[0114] Communication interface 504 uses any transceiver-like device to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0115] In a specific implementation, as one example, a computer device may include multiple processors, each of which may be a single-core (single CPU) processor or a multi-core (multi CPU) processor. Here, a processor may refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0116] The aforementioned computer device can be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device can be a desktop computer, a portable computer, a network server, a handheld digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. This application does not limit the type of computer device.

[0117] In addition, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for evaluating the insulation aging of cable accessories.

[0118] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0119] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

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The method of claim 1, wherein, The aging evaluation index of the insulation of the target cable accessory is obtained by aging evaluation of the insulation state of the target cable accessory according to the dielectric attenuation trend and the cumulative loss of thermal fatigue. The dielectric aging feature of the insulation state of the target cable accessory is determined according to the dielectric attenuation trend. The aging evaluation index of the insulation of the target cable accessory is obtained by aging evaluation of the insulation state of the target cable accessory according to the dielectric attenuation trend and the cumulative loss of thermal fatigue.

7. The method of claim 1, wherein, The surface temperature of the target cable accessory is monitored by a non-contact infrared temperature sensor.

8. A cable accessory insulation ageing assessment system, characterised in that, The method comprises the steps of: The micro-vibration signal of the target cable accessory during excitation is collected by a piezoelectric vibration sensor. The degradation feature parameter inside the target cable accessory is extracted from the micro-vibration signal. The insulation degradation state of the target cable accessory is gradient-analyzed according to the degradation feature parameter and the environmental humidity of the target cable accessory, so as to obtain the degradation gradient of the target cable accessory under the hydrolytic aging effect, and the dielectric attenuation trend of the insulation aging of the target cable accessory during operation is determined based on the degradation gradient and the electric field characteristics of the target cable accessory. The surface temperature of the target cable accessory is monitored by a temperature sensor, and the cumulative loss of thermal fatigue of the target cable accessory is determined according to the coupling correlation between all the monitored surface temperatures and the micro-vibration signal. The aging evaluation index of the insulation of the target cable accessory is obtained by aging evaluation of the insulation state of the target cable accessory according to the dielectric attenuation trend and the cumulative loss of thermal fatigue.

9. A computer device, comprising: The computer device comprises a memory and a processor, the memory stores a code, and the processor is configured to acquire the code and execute the cable accessory insulation aging evaluation method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 9. The computer program is executed by the processor to realize the cable accessory insulation aging evaluation method according to any one of claims 1 to 7.

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