A detection method for monitoring the state of a primary and secondary fusion circuit breaker

Abstract

The present application belongs to the technical field of power monitoring, and discloses a detection method for monitoring the state of primary-secondary fusion circuit breaker, comprising: obtaining circuit breaker state data, including electromagnetic waveform data, harmonic response characteristics and temperature distribution gradient; obtaining circuit breaker electric field distribution fingerprint through nonlinear segmented harmonic analysis, constructing a multi-dimensional penetration feature matrix, and establishing a micro-scale electric-thermal coupling atlas; obtaining a nonlinear region situation table through impedance distortion analysis, obtaining a harmonic penetration curve through multi-frequency response analysis, and constructing a high-frequency harmonic penetration path spectrum; establishing a micro-region diagnosis algorithm, performing nonlinear impedance calibration, and generating a multi-level protection instruction sequence; adjusting the operating state of the circuit breaker, obtaining the circuit breaker medium steady-state index, and performing risk analysis to obtain a harmonic penetration early warning report; the present application realizes accurate identification and early warning of abnormal regions inside the circuit breaker, and improves the safe and stable operation ability of the primary-secondary fusion circuit breaker.

Description

Technical Field

[0001] This invention relates to the field of power monitoring technology, and more specifically, to a detection method for monitoring the status of a primary and secondary integrated circuit breaker. Background Technology

[0002] With the advancement of smart grid construction, integrated primary and secondary circuit breakers are widely used as a new type of intelligent power equipment. These circuit breakers highly integrate traditional primary equipment (current interruption section) and secondary equipment (measurement and control section) into a closed system, achieving miniaturization and intelligent functionality, effectively reducing installation and maintenance costs. However, in actual operating environments, especially in substations in high-humidity areas in the south and high-temperature-difference areas in the north, integrated primary and secondary circuit breakers face a rare phenomenon of "selective dielectric penetration attenuation." This phenomenon mainly manifests as follows: in specific areas inside the circuit breaker (primarily the interface between primary and secondary equipment), due to cyclical changes in temperature and humidity and electromagnetic interference, a unique dielectric attenuation occurs. Low-probability localized dielectric penetration paths, which are almost undetectable under normal operating conditions, can lead to the formation of a "nonlinear impedance region" inside the circuit breaker. This nonlinear impedance region is unique in that it exhibits normal impedance values ​​under standard test voltages and currents, and does not trigger conventional insulation monitoring alarms. However, when current passes through at specific frequencies (typically 5 to 7 times the harmonics of the power frequency), it shows a significant impedance reduction, generating additional heat points. These heat points are located at the interface between primary and secondary equipment, causing unexpected thermal stress on precision electronic components in the secondary circuit. This can lead to signal acquisition errors and control timing disorder, potentially causing circuit breaker protection logic failure or malfunction at critical operating moments.

[0003] In existing technologies, circuit breaker condition monitoring mainly focuses on conventional parameters such as mechanical characteristics, contact wear, and SF6 gas density, as well as the overall condition assessment of electrical insulation. However, these monitoring methods have the following shortcomings: conventional insulation monitoring uses fixed-frequency (usually power frequency or DC) testing, which cannot identify frequency-dependent nonlinear impedance problems; infrared thermal imaging detection is affected by the shielding of the casing and cannot effectively detect tiny hot spots at internal interfaces; partial discharge detection is not sensitive to initial nonlinear impedance regions that have not yet formed obvious discharges; due to the lack of effective detection methods, the industry currently mainly relies on regular comprehensive maintenance to deal with such problems, which is not only costly and inefficient, but also has a low recognition rate for established nonlinear impedance regions.

[0004] In view of this, the present invention proposes a detection method for monitoring the status of primary and secondary fusion circuit breakers to solve the above problems. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution: a detection method for monitoring the status of a primary and secondary fusion circuit breaker, comprising:

[0006] Step S1: Obtain circuit breaker status data, which includes electromagnetic waveform data, harmonic response characteristics, and temperature distribution gradient;

[0007] Step S2: Perform nonlinear segmented harmonic analysis on the electromagnetic waveform data to obtain the circuit breaker electric field distribution fingerprint; construct a multidimensional penetration feature matrix based on the harmonic response characteristics and the temperature distribution gradient; identify abnormal regions on the multidimensional penetration feature matrix to obtain the medium penetration probability field; establish a microscale electrothermal coupling spectrum based on the circuit breaker electric field distribution fingerprint and the medium penetration probability field.

[0008] Step S3: Based on the microscale electrothermal coupling spectrum, perform impedance distortion analysis to obtain a nonlinear region status table; perform multi-frequency response analysis on the dielectric parameters in the microscale electrothermal coupling spectrum to obtain harmonic penetration curves; based on the nonlinear region status table and the harmonic penetration curves, perform anomaly development trend analysis to obtain high-frequency harmonic penetration path spectra.

[0009] Step S4: Establish a micro-region diagnostic algorithm based on the high-frequency harmonic penetration path spectrum to obtain the dielectric state correction parameters; apply the dielectric state correction parameters to the real-time data of the circuit breaker to perform nonlinear impedance calibration to obtain the circuit breaker anomaly hot zone diagram; generate an intervention strategy based on the circuit breaker anomaly hot zone diagram to obtain a multi-level protection command sequence.

[0010] Step S5: Adjust the circuit breaker's operating status based on the multi-level protection command sequence to obtain the circuit breaker's medium steady-state index; perform risk analysis based on the circuit breaker's medium steady-state index to obtain a harmonic penetration early warning report.

[0011] The technical effects and advantages of the detection method for monitoring the status of primary and secondary integrated circuit breakers of the present invention are as follows:

[0012] This invention achieves accurate identification of the electric field distribution fingerprint and dielectric penetration probability field of circuit breakers through nonlinear piecewise harmonic analysis and the construction of a multidimensional penetration feature matrix. This enhances both the early detection capability of microscopic anomalies and the sensitivity of condition monitoring. By establishing microscale electrothermal coupling spectra and conducting multi-level analysis, the interaction between the electric and thermal fields inside the circuit breaker can be reflected in real time, enabling precise characterization of the nonlinear region and harmonic penetration paths, thus allowing for early identification of potential faults. A micro-region diagnostic algorithm based on high-frequency harmonic penetration path spectra enables precise location and quantitative analysis of abnormal thermal zones in circuit breakers, ensuring the reliability of diagnostic results and improving detection efficiency. The generation and implementation of multi-level protection command sequences enable intelligent adjustment of the circuit breaker's operating status, extending equipment lifespan while ensuring safe operation. Risk analysis based on the circuit breaker's dielectric steady-state index improves the ability to predict and respond to potential risks in circuit breakers. Through multi-level collaborative analysis from the nanoscale to the global scale, accurate monitoring and prediction of changes in the internal microstate of circuit breakers are achieved, enabling early detection and intervention of various abnormal states, and significantly improving the reliability and safety of circuit breaker operation. Attached Figure Description

[0013] Figure 1 This is a schematic diagram of a detection method for monitoring the status of a primary and secondary fusion circuit breaker according to the present invention;

[0014] Figure 2 This is a schematic diagram of a detection system for monitoring the status of a primary and secondary fusion circuit breaker according to the present invention. Detailed Implementation

[0015] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] Example 1

[0017] Please see Figure 1 As shown in the figure, this embodiment provides a detection method for monitoring the status of a primary and secondary integrated circuit breaker, comprising:

[0018] Step S1: Obtain circuit breaker status data, which includes electromagnetic waveform data, harmonic response characteristics, and temperature distribution gradient;

[0019] Step S2: Perform nonlinear piecewise harmonic analysis on the electromagnetic waveform data to obtain the circuit breaker electric field distribution fingerprint; construct a multidimensional penetration feature matrix based on harmonic response characteristics and temperature distribution gradient; identify abnormal regions on the multidimensional penetration feature matrix to obtain the medium penetration probability field; establish a microscale electrothermal coupling spectrum based on the circuit breaker electric field distribution fingerprint and the medium penetration probability field.

[0020] Step S3: Based on the microscale electrothermal coupling spectrum, perform impedance distortion analysis to obtain the nonlinear region situation table; perform multi-frequency response analysis on the dielectric parameters in the microscale electrothermal coupling spectrum to obtain the harmonic penetration curve; based on the nonlinear region situation table and the harmonic penetration curve, perform anomaly development trend analysis to obtain the high-frequency harmonic penetration path spectrum.

[0021] Step S4: Establish a micro-region diagnostic algorithm based on the high-frequency harmonic penetration path spectrum to obtain the medium state correction parameters; apply the medium state correction parameters to the real-time data of the circuit breaker to perform nonlinear impedance calibration to obtain the circuit breaker anomaly hot zone diagram; generate intervention strategies based on the circuit breaker anomaly hot zone diagram to obtain a multi-level protection command sequence.

[0022] Step S5: Adjust the circuit breaker's operating status based on the multi-level protection command sequence to obtain the circuit breaker's medium steady-state index; perform risk analysis based on the circuit breaker's medium steady-state index to obtain a harmonic penetration early warning report.

[0023] First, a multi-frequency electromagnetic probe array is deployed, consisting of multiple probes with different frequency ranges, including low-frequency, medium-frequency, and high-frequency probes. The probe array adopts a uniformly distributed layout, arranged in a grid pattern in key parts of the circuit breaker, such as the contact area, the periphery of the arc-extinguishing chamber, and the main circuit, ensuring comprehensive monitoring of the circuit breaker's electromagnetic field distribution. A harmonic coupling detector uses FFT real-time analysis technology to perform harmonic analysis on the acquired electromagnetic signals, recording the superposition effect of multiple frequency harmonics as part of the electromagnetic waveform data. A micro-area temperature sensing network, composed of high-precision thermocouples and infrared sensors, is arranged inside the circuit breaker to ensure the capture of micro-area temperature changes. The sensor sensitivity is no less than 0.1℃, and the response time is controlled within 10ms to obtain transient temperature change characteristics. Harmonic response characteristics are acquired using a specially designed harmonic response recorder, capable of capturing the amplitude, phase, and coupling relationships between harmonics in real time. By comparing the harmonic response data with standard values, the recorder can identify abnormal harmonic combinations and their temporal evolution trends. The permeation-state transformation monitoring device employs a high-frequency capacitive sensing principle, detecting changes in medium characteristics by measuring minute variations in the medium's capacitance value. With a sampling rate of 50kHz, it can capture transient characteristics during rapid permeation. The interface-state abnormal waveform acquisition device focuses on electric field distortion at the interfaces of different media within the circuit breaker. Utilizing dual-frequency probe technology, it simultaneously monitors the reflection and transmission characteristics of power frequency and high-frequency signals at the interface, achieving a 16-bit sampling accuracy to ensure the detection of weak interface abnormal signals. Temperature distribution gradient acquisition utilizes a micro-thermal gradient scanner. Based on the principle of heat flux density measurement, this device achieves a scanning resolution of 0.5mm × 0.5mm and a temperature gradient measurement accuracy of ±0.05℃ / mm, accurately depicting the heat flow conduction path within the circuit breaker. The medium characteristic change detector monitors medium aging by measuring changes in parameters such as the dielectric constant and loss tangent. With a measurement frequency range of 10Hz to 1MHz, it enables comprehensive monitoring of medium characteristics at different frequencies. The heat transfer efficiency analysis device, based on a heat transfer model, calculates the heat transfer coefficient in different regions, analyzes the heat transfer characteristics inside the circuit breaker, and generates a three-dimensional temperature gradient distribution map using thermal imaging technology, providing basic data for subsequent analysis. Through the coordinated operation of these devices, a complete circuit breaker condition monitoring network is formed. The collected raw data, after preprocessing, forms three core data types: electromagnetic waveform data, harmonic response characteristics, and temperature distribution gradient, laying the data foundation for subsequent analysis and processing.

[0024] Preferably, step S2 includes:

[0025] Step S21: Perform multi-spectral decomposition on the electromagnetic waveform data to obtain the electromagnetic characteristic spectrum set; perform cross-coupling analysis on the electromagnetic characteristic spectrum set to obtain the electromagnetic spectrum dispersion characteristic analysis domain.

[0026] Step S22: Perform fast Fourier transform and spectral domain decomposition on the harmonic response characteristics to obtain multi-frequency response characteristics; perform spatiotemporal heat flux mapping on the temperature distribution gradient to obtain hot spot energy distribution map; construct a multi-dimensional permeation feature matrix based on the multi-frequency response characteristics and hot spot energy distribution map;

[0027] Step S23: Use the nonlinear piecewise harmonic decomposition algorithm to perform electric field scanning on the electromagnetic spectrum dispersion feature analysis domain to obtain the electric field distribution fingerprint of the circuit breaker;

[0028] Step S24: Use the anomaly region identification algorithm to perform probability analysis on the multidimensional permeation feature matrix to obtain the medium permeation probability field;

[0029] Step S25: Pre-set the electrothermal coupling basic framework, map the circuit breaker electric field distribution fingerprint and dielectric penetration probability field to the electrothermal coupling basic framework to form the initial electrothermal coupling prototype;

[0030] Step S26: Use multi-spectral coding technology to add time-varying characteristics to the initial electrothermal coupling prototype to obtain a dynamic electrothermal coupling body; perform virtual environment verification and calibration on the dynamic electrothermal coupling body to obtain a microscale circuit breaker electrothermal coupling spectrum.

[0031] Specifically, the electromagnetic waveform data is first decomposed into multiple spectrometers, and then divided into three levels based on the observation scale: nanoscale, component scale, and global scale. At the nanoscale level, the focus is on the molecular arrangement of the medium and the microscopic distribution of the electric field, using high-frequency sampling data with a window size of 1024 points. At the component scale level, the focus is on the electromagnetic characteristics of individual components such as the arc-extinguishing chamber and contacts, using medium-frequency sampling data with a window size of 4096 points. At the global scale level, the focus is on the overall electromagnetic field distribution of the circuit breaker, using low-frequency sampling data with a window size of 8192 points. Within each level, multiple observation windows are set according to spatial location and the distribution of key components, forming a multi-level electromagnetic window set. Harmonic normalization is performed on the waveform data in the multi-level electromagnetic window set to ensure data comparability between different windows. First, spectral analysis is performed to extract the amplitude and phase of each harmonic. After extracting the power frequency and harmonic components, the amplitude is normalized, with the fundamental power frequency amplitude standardized to 1. The phase remains unchanged, but the unified reference point is the fundamental phase. After normalization, a normalized electromagnetic spectrum vector is obtained, containing normalized amplitude and relative phase information. Coupled-state analysis is performed on the normalized electromagnetic spectrum vector to identify the interaction relationships between different harmonics. Harmonics are defined. Harmonic waves Phase correlation between them: ;in and Harmonics Harmonic waves phase, Integer multiples (usually) The phase correlation between all harmonic pairs is calculated, forming an N×N phase correlation matrix (N being the harmonic order). The results of coupled-state analysis form an electromagnetic phase correlation set, describing the interaction relationships between harmonics. The normalized electromagnetic spectral vector and the electromagnetic phase correlation set are grouped according to observation levels, with each level containing spectral vectors and phase correlation information at a specific scale. At the nanoscale level, the focus is on the distribution characteristics of high-frequency components; at the component-scale level, the focus is on the distribution characteristics of mid-frequency components; and at the global scale level, the focus is on the distribution characteristics of low-frequency components. Through hierarchical grouping, a multi-scale electromagnetic characteristic spectral quantity set is formed, containing normalized spectral vectors and phase correlation information for each level, such as frequency, amplitude, phase, and energy distribution. Cross-coupling analysis is performed on the electromagnetic characteristic spectral quantity set to calculate the degree of mutual influence between different frequencies, and bispectral analysis is used to identify nonlinear coupling characteristics. Coupling coefficients are defined. Indicates the first The frequency and the first Coupling strength between frequencies: ;in, It is a bispectral density function. and The first The frequency and the first Electromagnetic characteristic spectral quantities at each frequency are calculated. The coupling coefficients between all frequency pairs are calculated, constructing an N×N coupling matrix (N being the number of frequency points). The main coupling modes are extracted using singular value decomposition, forming an electromagnetic spectral dispersion characteristic analysis domain. This domain reflects the distribution and coupling relationships of the circuit breaker's electromagnetic characteristics in the frequency domain. Fast Fourier Transform (FFT) and spectral decomposition are performed on the harmonic response characteristics, converting the time-domain harmonic response signal to the frequency domain for analysis. An improved FFT algorithm is used to perform a 2048-point FFT calculation on the sampled signal to obtain the spectral distribution. The spectrum is grouped by harmonic order, and the amplitude, phase, and time-varying characteristics of each harmonic are analyzed. Furthermore, Hilbert-Huang transform is used to extract the instantaneous frequency characteristics of the signal, revealing the dynamic characteristics of harmonics in the time and frequency domains, ultimately obtaining multi-frequency response characteristics. Spatiotemporal heat flux mapping is performed on the temperature distribution gradient, and a heat diffusion model is used for heat flux analysis, establishing a mapping relationship between the temperature gradient and heat flux density. Heat flux density is then calculated. With temperature gradient The relationship between them can be represented as: ;in The thermal conductivity coefficient matrix takes into account the anisotropic thermal conductivity characteristics of different materials within the circuit breaker. Hotspot regions are identified based on heat flux density; areas with heat flux density exceeding a preset hotspot threshold are marked as hotspot regions, generating a hotspot energy distribution map. This map includes information such as hotspot location, heat energy magnitude, and heat diffusion rate. A multidimensional permeation feature matrix is ​​constructed based on multi-frequency response characteristics and the hotspot energy distribution map, using tensor representation to build a high-dimensional matrix structure. The matrix dimensions include spatial location (x, y, z), frequency (f), temperature (T), and time (t), forming a 6-dimensional matrix. Matrix element values ​​represent normalized permeation feature values ​​at location (x, y, z), frequency f, and time t, ranging from 0 to 1, where 0 represents no permeation and 1 represents complete permeation. Principal component analysis is used to reduce the dimensionality of the high-dimensional matrix, simplifying subsequent computational complexity. A nonlinear piecewise harmonic decomposition algorithm is used to scan the electric field in the electromagnetic spectrum dispersion feature analysis domain. Based on adaptive piecewise processing and nonlinear decomposition principles, this algorithm can effectively identify anomalous features in the electric field distribution. First, a multi-frequency nonlinear Fourier transform is performed on the electromagnetic spectrum dispersion feature analysis domain. Unlike traditional Fourier transforms, this method uses a set of nonlinear basis functions to adapt to the complex electric field distribution characteristics inside the circuit breaker. The basis functions contain basic sinusoidal components and a nonlinear square term, described by three key parameters: harmonic frequency, initial phase, and nonlinear coefficient. The nonlinear coefficient directly reflects the nonlinear characteristics of the harmonics, which cannot be captured by conventional linear analysis. For each spatial point in the electromagnetic spectrum dispersion feature analysis domain, the projection value of its electric field time series onto each basis function is calculated. This process essentially measures the similarity between the electric field signal and each basis function. By adjusting the three parameters—frequency, phase, and nonlinear coefficient—the matching degree of the basis functions is optimized to minimize the error between the reconstructed signal and the original electric field signal. The fundamental frequency and harmonic components of the reconstructed signal are extracted to form a complete harmonic component set. Each harmonic component is described by three characteristic parameters: amplitude, phase, and nonlinear coefficient, providing rich feature information for subsequent analysis. Based on the harmonic component set, the interaction characteristics between harmonics are further analyzed, focusing on two aspects: phase relationship and energy distribution ratio. Harmonic correlation coefficients are defined to quantify the relationships between different harmonics. These coefficients consider the product of harmonic amplitudes, the cosine of the phase difference, and are normalized using the total energy. After calculating the correlation coefficients for all harmonic pairs, an correlation matrix is ​​constructed, the size of which depends on the harmonic order being analyzed. Simultaneously, the energy proportion of each harmonic is calculated, i.e., the ratio of each harmonic's energy to the total energy. The energy proportion reflects the importance of each harmonic in the overall electric field distribution. Using the correlation matrix and energy proportion, a harmonic characteristic correlation diagram is constructed, reflecting the unique characteristics of the circuit breaker's electric field distribution. Combined with spatial distribution information, initial electric field fingerprint data is formed, containing spatial coordinates and corresponding harmonic characteristic information.Eigenvector analysis (EVA) is applied to reduce the dimensionality of the initial electric field fingerprint data, thereby reducing data processing complexity. Principal component analysis (PCA) is used for dimensionality reduction, resulting in a compressed electric field eigenvector that significantly reduces data dimensionality while retaining the main features of the original data. An internal electric field response feature space for the circuit breaker is constructed, consisting of three dimensions: frequency, spatial, and response intensity. The frequency dimension includes the power frequency and its harmonics; the spatial dimension corresponds to the three-dimensional structure inside the circuit breaker; and the response intensity dimension reflects the distribution characteristics of the electric field intensity. In the feature space, each point represents the electric field response intensity at a specific location and frequency. The compressed electric field eigenvector is mapped into the feature space, and interpolation and smoothing are used to generate a continuous distribution field, forming the circuit breaker's electric field distribution fingerprint. This fingerprint contains characteristic information about the internal electric field distribution of the circuit breaker, including the electric field intensity distribution map, harmonic distribution characteristics, and anomaly point distribution, uniquely identifying the circuit breaker's electric field state. An anomaly region identification algorithm is used to perform probabilistic analysis on a multidimensional penetration feature matrix. This algorithm, based on clustering and statistical learning theories, can effectively identify abnormal regions in the matrix. Specifically, the DBSCAN density clustering algorithm is first used to cluster the data points in the matrix, identifying regions with inconsistent densities. Then, a Bayesian inference method is used to calculate the penetration probability of each region, constructing a probability distribution function. Among them, prior probability and The likelihood function is obtained based on historical data statistics. Fitting using a Gaussian mixture model Represents infiltration, This represents the observed characteristics. By calculating the penetration probability at each point, a continuous probability field distribution is generated, forming a medium penetration probability field. This probability field reflects the likelihood of medium penetration in various regions inside the circuit breaker. A pre-defined electrothermal coupling framework is established, which is a coupling model of the electric field and temperature field. The model includes three core components: electric field distribution, temperature distribution, and material properties. The coupling relationship between these three components is described by defining interaction equations. The circuit breaker's electric field distribution fingerprint and medium penetration probability field are mapped onto this framework, corresponding to the electric field distribution and material property components, forming an initial electrothermal coupling prototype. Multi-spectral coding technology is used to add time-varying characteristics to the initial electrothermal coupling prototype, encoding the electrothermal coupling state at different frequencies as a time-series evolution process. Wavelet packet transform is used to encode the time series, constructing a three-dimensional mapping relationship of frequency-time-feature. Different time sampling windows are set according to different harmonic frequencies: a long time window (approximately 200ms) is used for power frequency and low-order harmonics, while a short time window (approximately 20ms) is used for high-order harmonics, to balance time resolution and frequency resolution. By adding dynamic characteristics to the time dimension, the static electrothermal coupling prototype is transformed into a dynamic electrothermal coupling body, which can describe the changes in the electrothermal coupling state of the circuit breaker under different operating conditions. The dynamic electrothermal coupling body is validated and calibrated in a virtual environment, and a digital twin model of the circuit breaker based on a physical model is constructed to simulate the circuit breaker's operating state under various conditions. Monte Carlo method is used for parameter sensitivity analysis to determine key parameters and their degree of influence. Measured data are compared with model predictions, and the model parameters are optimized using the least squares method to control the root mean square error between the model output and the actual observation results within 5%. The validated and calibrated model forms a microscale electrothermal coupling map of the circuit breaker, which can accurately describe the electrothermal coupling state inside the circuit breaker at the microscale.

[0032] Preferably, step S3 includes:

[0033] Step S31: Extract impedance parameters from the microscale electrothermal coupling spectrum and construct a set of nonlinear impedance equations;

[0034] Step S32: Solve the nonlinear impedance equations to obtain the distribution law of the possible impedance of the circuit breaker and form a nonlinear region situation table;

[0035] Step S33: Perform time-domain and frequency-domain joint analysis on the dielectric parameters in the microscale electrothermal coupling spectrum to identify the coupling characteristics between electromagnetic conduction and heat transfer, and obtain the harmonic penetration curve;

[0036] Step S34: Align the nonlinear region situation table with the harmonic penetration curve in time and space, construct an anomaly development trend prediction method, and obtain the prediction reliability index;

[0037] Step S35: Based on the predicted reliability index, establish a critical penetration identification algorithm to detect the penetration region in the high-frequency harmonic path and obtain the evolution trajectory of the penetration region;

[0038] Step S36: Perform feature extraction and pattern recognition on the evolution trajectory of the infiltration region to obtain the high-frequency harmonic penetration path spectrum.

[0039] Specifically, impedance parameters, including resistance, inductance, and capacitance, are first extracted from the microscale electrothermal coupling spectrum. A network parameter identification algorithm is used to represent the internal circuit of the circuit breaker as an equivalent RLC network, with each micro-region corresponding to an RLC unit. For each region, its equivalent resistance, equivalent inductance, and equivalent capacitance are all functions of temperature. The resistance parameter changes linearly with temperature; that is, the resistance value at the reference temperature is multiplied by a temperature correction factor, which is determined by the product of the temperature difference and the temperature coefficient. Similarly, the inductance and capacitance parameters also adopt a linear temperature correction model, introducing the inductance temperature coefficient and capacitance temperature coefficient, respectively, to describe their variation with temperature. Based on the extracted parameters, a set of nonlinear impedance equations is constructed: ;in Represents temperature The equivalent resistance below, Represents temperature The equivalent inductance below, temperature The equivalent capacitance below, Angular frequency, The imaginary unit is used. A system of nonlinear impedance equations is solved. Due to the highly nonlinear nature of the equations, an iterative algorithm is used for numerical solution. First, the equations are discretized and converted into matrix form, including the impedance matrix, state variable matrix, and coefficient matrix. The Newton-Raphson iterative method is used to solve the equations. Each iteration updates the state variables by calculating the Jacobian matrix and function values. The iteration terminates when the relative error between two adjacent iterations is less than a preset error threshold. The solution is expressed as the impedance changing with frequency and temperature. Statistical analysis of the solutions yields the distribution pattern of the circuit breaker's potential impedance, forming a nonlinear region situation table. This situation table includes the impedance characteristics, nonlinearity, and trends of each region, providing data support for subsequent analysis. A joint time-domain and frequency-domain analysis is performed on the dielectric parameters in the microscale electrothermal coupling spectrum to identify the coupling characteristics between electromagnetic conduction and heat transfer. In the time domain, the trend of dielectric parameters changing with time is analyzed; in the frequency domain, the response characteristics of the parameters to signals of different frequencies are analyzed. Further analysis of the energy transfer characteristics during harmonic penetration is conducted. The penetration coefficient is defined as the ratio of the transmitted electric field to the incident electric field. By calculating the penetration coefficient at different frequencies, curves are plotted to form the harmonic penetration curve. This curve reflects the propagation characteristics of harmonics at various frequencies within the circuit breaker, providing a basis for identifying abnormal development trends. The nonlinear region situation table and the harmonic penetration curve are spatiotemporally aligned, and an abnormal development trend prediction method is constructed based on their correspondence. Data fusion technology is employed to integrate information from two data sources into a unified analytical framework. The comprehensive abnormality index is defined as the weighted sum of the normalized impedance value and the normalized penetration coefficient. The weighting coefficients are optimized using Bayesian estimation to achieve the best match between the prediction results and historical data. A prediction model is constructed based on the comprehensive abnormality index to predict the abnormal development trend at future moments, and the reliability index of the prediction results is calculated. The reliability index is the ratio of the standard deviation to the mean of the predicted value; a higher reliability index indicates a more reliable prediction result. Based on the prediction reliability index, a critical penetration identification algorithm is established to detect penetration areas in high-frequency harmonic paths. A critical reliability threshold is set for prediction. When the reliability index exceeds the threshold, the prediction result is accepted for subsequent analysis. For areas that meet the threshold condition, their permeability characteristics are further analyzed. The permeability state index is defined as the relative deviation between the actual penetration coefficient and the normal state penetration coefficient. When the permeability state index exceeds a preset threshold (usually 0.2), the area is considered to be in a permeable state. Time-series tracking is performed on all permeable areas, recording the changes in their location, size, and characteristics over time to form a permeable area evolution trajectory, which reflects the dynamic development characteristics of the permeation process.

[0040] Feature extraction and pattern recognition of the evolution trajectory of the infiltration region are performed. First, a time-series alignment algorithm is applied to process infiltration data at different frequencies. Since harmonic infiltration processes at different frequencies may have time delays and differences in development rates, these time-series data need to be aligned. A dynamic time warping algorithm is used to align the time-series data. This algorithm achieves time alignment by finding the optimal matching path between two time series. Specific steps include: defining the distance function: ;in Represents the sequence at time points and distance, For sequence At the point of time The value, For sequence At the point of time The value of the cumulative distance matrix is ​​calculated using dynamic programming. The cumulative distance matrix is ​​then backtracked to determine the optimal alignment path, and the time-series data is resampled and interpolated based on the alignment path. Alignment operations are performed on the penetration data at all frequencies to obtain a time-synchronized, normalized trajectory set, ensuring time consistency across different frequencies and facilitating subsequent pattern recognition. A penetration pattern classification system is constructed, classifying penetration patterns into four types based on the internal penetration mechanism and characteristics of circuit breakers: Phase penetration type: Characterized by abnormal harmonic phase changes, usually related to electric field distortion at the medium interface, characterized by a phase shift exceeding 20% ​​of the normal value. Amplitude amplification type: Characterized by abnormally increased harmonic amplitude, usually related to localized medium breakdown, characterized by an amplitude amplification exceeding 50% of the normal value. Energy accumulation type: Characterized by heat accumulation in a specific area, usually related to medium thermal aging, characterized by a temperature rise rate exceeding three times that of the surrounding area. Interface dissipation type: Characterized by abnormal energy dissipation at the interface, usually related to medium stratification or bubbles, characterized by an energy dissipation rate exceeding 30% of the normal value. The classification system establishes clear discrimination criteria, providing a theoretical foundation for subsequent penetration pattern identification. Based on historical operational data and theoretical physics analysis, penetration pattern types are labeled for the regularized trajectory set. Historical operational data comes from a long-term monitoring database of circuit breakers, containing numerous records of penetration events of known types. Theoretical physics analysis is based on electromagnetic field theory and materials science, combined with the structural characteristics of circuit breakers and the properties of the medium. A combination of expert systems and machine learning is used for pattern labeling. First, obvious pattern types are initially labeled according to expert rules. Then, supervised learning algorithms (such as random forests or SVMs) are used to classify the remaining difficult-to-determine trajectories. During the labeling process, key characteristic parameters of the trajectories are considered, such as phase change rate, amplitude growth curve, energy accumulation rate, and interface energy distribution. Through comprehensive labeling of the regularized trajectory set, penetration pattern classification data is obtained, including the pattern type and key characteristic parameters of each trajectory. Characteristic statistics for different penetration patterns are calculated, and the statistical characteristics of various penetration patterns are analyzed. Occurrence frequency: The number of occurrences of each type of penetration per unit time is statistically analyzed to reflect the prevalence of the penetration type. Penetration depth: Quantifies the degree of impact of penetration on the medium. For phase-permeable penetration, it is represented by the phase shift angle; for amplitude amplification, by the amplitude increase ratio; for energy accumulation, by the temperature rise; and for interface dissipation, by the energy dissipation rate. Duration: Statistically measures the duration of the penetration state, reflecting the stability and recovery capability of the penetration. By calculating these statistics, quantitative indicators for penetration modes are formed, providing data support for risk assessment of each penetration mode. Based on these quantitative indicators, response characteristic profiles are constructed, transforming the quantitative indicators into intuitive characteristic descriptions. Using a radar chart method, key indicators for each penetration mode are mapped to a multi-dimensional characteristic space, forming a unique mode characteristic profile.The profiling dimensions include penetration velocity, impact range, duration, resilience, risk level, and evolution trend. Based on the characteristic profiling, the penetration path characteristics at different harmonic frequencies are analyzed, including path geometry, propagation velocity, energy distribution, and main affected areas. The comprehensive analysis results are integrated into a high-frequency harmonic penetration path spectrum, which describes the propagation path, penetration characteristics, and development trend of harmonics inside the circuit breaker, providing a scientific basis for subsequent micro-area diagnosis and intervention strategy formulation.

[0041] Preferably, step S4 includes:

[0042] Step S41: Based on the high-frequency harmonic penetration path spectrum, construct a medium anomaly quantification method, calculate the penetration degree of each key parameter, and obtain the medium deviation parameter;

[0043] Step S42: Establish a micro-region diagnostic algorithm using a multi-parameter correction algorithm to convert the medium deviation parameters into medium state correction parameters;

[0044] Step S43: Establish a real-time data acquisition channel to obtain the micro-area status data stream of the physical circuit breaker, and apply the medium status correction parameter to calibrate the micro-area status data stream in real time to obtain the corrected status data;

[0045] Step S44: Reconstruct the current abnormal hot zone of the circuit breaker based on the corrected state data, and generate an abnormal hot zone map of the circuit breaker;

[0046] Step S45: Combine the industry fault knowledge base and equipment historical performance data to conduct a risk level assessment of the circuit breaker abnormal thermal map and obtain the assessed abnormal thermal map.

[0047] Step S46: Apply the multi-level protection theory to conduct an intervention requirement analysis on the assessed anomaly hot zone map and generate a multi-level protection instruction sequence.

[0048] Specifically, a method for quantifying dielectric anomalies is first constructed based on high-frequency harmonic penetration path spectra to quantitatively assess the internal dielectric state of the circuit breaker. Key characteristic parameters, including penetration path length, penetration depth, penetration rate, and energy density, are extracted from the path spectrum and compared with normal state parameters to obtain dielectric deviation parameters. ;in For the first The value of the class parameter, For the first The normal state values ​​of the parameters are defined. Medium deviation parameters comprehensively reflect the abnormal state of the medium inside the circuit breaker, providing a basis for subsequent state correction. A micro-region diagnostic algorithm is established using a multi-parameter correction algorithm to transform the medium deviation parameters into medium state correction parameters. The multi-parameter correction algorithm is based on a physical model and statistical learning methods, considering both simple and complex nonlinear relationships between parameters. For simple nonlinear relationships, an M-power function is used as the parameter correction mapping function, where M is set based on actual conditions. For complex nonlinear relationships, a neural network model is used for parameter mapping. The neural network model contains three hidden layers, with 16, 32, and 16 nodes per layer, respectively. ReLU activation function and batch normalization layers are used, and the network parameters are trained using a backpropagation algorithm. Through the parameter mapping function, the medium deviation parameters are transformed into medium state correction parameters. These correction parameters reflect the degree of deviation and correction requirements of the medium state inside the circuit breaker, providing a foundation for real-time data calibration. A real-time data acquisition channel is established to obtain the micro-region state data stream of the physical circuit breaker. The acquisition channel includes a high-speed data acquisition unit, signal conditioning circuitry, and a data transmission network, with a sampling rate of no less than 50kHz and a resolution of no less than 16 bits, ensuring the capture of high-frequency harmonics and transient changes. The acquired data includes various physical quantities such as current, voltage, temperature, and dielectric parameters, forming a multi-dimensional real-time data stream. Dielectric state correction parameters are applied to calibrate the micro-region state data stream in real time; the calibration formula is: ;in, For measured values, Correction parameters for the corresponding medium state. The calibration coefficient ranges from [0.5, 2]. Real-time calibration yields corrected state data, reflecting the true internal state of the circuit breaker and eliminating measurement biases caused by dielectric anomalies. Based on the corrected state data, the current anomaly zone of the circuit breaker is reconstructed using heat flow analysis and an electrothermal coupling model. A thermal anomaly index is defined. ;in For position The temperature at that location For ambient temperature, The critical temperature is used. The thermal anomaly index at each point inside the circuit breaker is calculated to construct a thermal anomaly distribution field, and a continuous thermal zone distribution map is generated using spatial interpolation. Based on the magnitude of the thermal anomaly index, the thermal zones are divided into high anomaly zones (thermal anomaly index greater than 0.7), medium anomaly zones (thermal anomaly index within the interval (0.4, 7]), and low anomaly zones (thermal anomaly index within the interval (0.1, 0.4]). A three-dimensional visualization technique is used to generate an abnormal thermal zone map of the circuit breaker, visually displaying the hotspot distribution and abnormal areas inside the circuit breaker. A risk level assessment of the abnormal thermal zone map is performed by combining an industry fault knowledge base and historical equipment performance data. The industry fault knowledge base contains a large number of circuit breaker fault cases and corresponding thermal zone characteristics, while the historical equipment performance data records the operating history and abnormal events of specific circuit breakers. A rule-based and case-based hybrid reasoning method is used to analyze the similarity between current thermal zone characteristics and historical fault cases. ;in For current characteristics and historical cases in the first Differences in each dimension For historical cases in Standard deviation of each dimension For the first The weights of each dimension are considered. Based on the similarity analysis results, the risk level of the current hot zone is assessed and divided into four levels: emergency risk (red), high risk (orange), medium risk (yellow), and low risk (green). The risk level information is overlaid on the original hot zone map to form an assessed anomaly hot zone map, which visually displays the risk status of each area. Applying the multi-level protection theory, an intervention demand analysis is conducted on the assessed anomaly hot zone map. First, a multi-level protection framework is constructed, which includes three core layers: a harmonic suppression layer, a dielectric reinforcement layer, and an operational restriction layer, forming a deep defense system. The harmonic suppression layer, as the innermost layer of protection, directly addresses the harmonic penetration problem. Its functions include harmonic filtering, electromagnetic shielding, and waveform optimization, with the goal of reducing harmonic sources and propagation paths. The dielectric reinforcement layer, as the intermediate layer of protection, addresses the problem of abnormal dielectric conditions. Its functions include temperature control, humidity regulation, and dielectric regeneration, with the goal of improving the dielectric's resistance to penetration and self-recovery capabilities. The operation restriction layer, as the outermost layer of protection, addresses operational conditions and includes functions such as load limiting, operating frequency control, and maintenance plan adjustment. Its goal is to alleviate the operational pressure on circuit breakers and delay the development of anomalies. The anomaly hotspot map after evaluation is decomposed into multiple levels, mapping hotspot characteristics to each level within the multi-level protection framework. For the harmonic suppression layer, the focus is on harmonic distribution characteristics and penetration paths, analyzing the sources, frequency characteristics, and propagation laws of harmonics. For the dielectric reinforcement layer, the focus is on changes in dielectric parameters and temperature distribution, analyzing the degree of dielectric degradation, hotspot distribution, and recovery potential. For the operation restriction layer, the focus is on operating state parameters and load characteristics, analyzing operating frequency, load levels, and the operating environment. Through feature mapping, a protection requirement description is generated for each level, including protection objectives, key areas, and critical parameters, forming a layered protection requirement that provides a basis for subsequent protection parameter determination. A hierarchical linkage protection algorithm is used to determine the protection parameters for each level. This algorithm is based on a Bayesian network model and considers the causal relationships and linkage effects between levels. The probabilistic dependencies between the three layers of protection parameters are established. ;in , and These represent the inner layer protection parameters, middle layer protection parameters, and outer layer protection parameters, respectively. It is the conditional probability of the outer layer protection parameters given the middle layer protection parameters. It is the conditional probability of the middle layer protection parameters given the inner layer protection parameters. This refers to the prior probabilities of the inner layer's protection parameters. A conditional probability table is constructed based on historical data and expert knowledge to reflect the interactions between parameters. Using Bayesian inference, the optimal combination of protection parameters is calculated based on the current abnormal state to maximize the overall protection effect. Protection parameters include specific values ​​such as harmonic filtering thresholds, medium temperature control targets, and operating frequency limits. During parameter optimization, resource constraints and implementation feasibility are considered to ensure the protection scheme is truly feasible. Based on the optimization results, a multi-level linkage protection scheme is constructed, including protection measures and parameter settings for each level, as well as the linkage mechanism between levels, forming an inter-layer collaborative protection strategy. The inter-layer collaborative protection strategy is converted into a specific sequence of execution instructions, transforming abstract protection measures into executable operation instructions. For the harmonic suppression layer, instructions such as filter parameter settings and harmonic monitoring threshold adjustments are generated; for the medium reinforcement layer, instructions such as temperature control targets, humidity adjustment parameters, and medium treatment schemes are generated; for the operation restriction layer, instructions such as load limits, operating frequency limits, and maintenance plan adjustments are generated. The instruction sequence is ordered according to execution priority, with protection measures in high-risk areas executed first, and emergency protection measures taking precedence over routine protection measures. The instruction sequence also includes execution time, execution method, and effect feedback mechanism to ensure that protective measures can be effectively implemented and their effects evaluated in a timely manner. By transforming protection strategies into execution instruction sequences, a multi-level protection instruction sequence is formed, providing specific guidance for adjusting the circuit breaker's operating status, including various measures such as harmonic suppression, temperature control, and operational restrictions. The protection scheme is transformed into specific execution instructions, generating a multi-level protection instruction sequence to guide the adjustment of the circuit breaker's operating status.

[0049] Preferably, step S5 includes:

[0050] Step S51: Formulate a circuit breaker operation status adjustment scheme based on the multi-level protection command sequence, implement coordinated adjustment, and obtain the circuit breaker medium steady-state index;

[0051] Step S52: Conduct a stability assessment of the circuit breaker's medium steady-state index based on industry safety evaluation standards to obtain a steady-state maintenance capability score;

[0052] Step S53: Set risk thresholds based on steady-state maintenance capability scores, construct multi-level early warning strategies, and generate risk analysis results;

[0053] Step S54: Compile a harmonic penetration early warning report based on the risk analysis results, including penetration stability, risk level and development trend.

[0054] Specifically, a circuit breaker operation status adjustment plan is formulated based on a multi-level protection command sequence. For each circuit breaker model, operating environment, and load condition, the protection commands are translated into actual operational measures. The adjustment plan includes both hardware and software adjustments: hardware adjustments include physical measures such as adding harmonic filters, adjusting circuit breaker operating mechanism parameters, and replacing key components; software adjustments include non-physical measures such as modifying control parameters, optimizing protection strategies, and adjusting monitoring thresholds. Based on the importance of the circuit breaker and its impact on the system, the priority and timeline for adjustment implementation are determined, forming a phased implementation plan. Adjustments are implemented collaboratively according to the plan, with real-time monitoring and effect evaluation during the adjustment process, and dynamic adjustments to the plan as necessary. After the adjustment is completed, changes in the internal medium state of the circuit breaker are observed, and the medium steady-state index is calculated. ;in The dielectric anomaly index, The coefficient of variation of key parameters reflects the degree of parameter fluctuation. The medium steady-state index ranges from 0 to 1, with higher values ​​indicating more stable medium conditions. The stability of the circuit breaker's medium steady-state index is assessed in conjunction with industry safety evaluation standards, including those issued by organizations such as IEC, IEEE, and the State Grid Corporation of China. The current medium steady-state index is compared with the standard requirements to evaluate its compliance level. The standard compliance rate is defined. ;in The minimum steady-state index required by the standard is used. Based on the standard compliance rate and medium condition characteristics, the stability and reliability of the circuit breaker's medium condition are evaluated, with particular attention to the time evolution trend and environmental adaptability of the medium condition. Considering factors such as load changes, environmental impacts, and aging effects, the steady-state maintenance capability of the circuit breaker under various operating conditions is assessed, resulting in a steady-state maintenance capability score, categorized into four levels: excellent (90-100 points), good (75-89 points), average (60-74 points), and insufficient (below 60 points). Risk thresholds are set based on the steady-state maintenance capability score, with corresponding judgment criteria for different risk levels. For example, the emergency risk threshold is set at 60 points, the high risk threshold at 75 points, the medium risk threshold at 85 points, and the low risk threshold at 90 points. The risk level of the circuit breaker is determined based on the comparison between the score and the threshold. Based on the risk level and specific characteristics, a multi-level early warning strategy is constructed, including four levels: emergency intervention, operation restriction, enhanced monitoring, and routine monitoring. Each early warning level is equipped with corresponding response measures and resource allocation plans, forming a complete risk management scheme. A comprehensive analysis of the current status and future trends of the circuit breaker generates risk analysis results, including risk level, risk factors, and response recommendations, providing core content for subsequent early warning reports. Based on the risk analysis results, a harmonic penetration early warning report is compiled, comprising four core parts: Penetration Stability: Analyzing the penetration state and time stability of the medium inside the circuit breaker, including the degree, scope, and trend of penetration, as well as comparative analysis with historical data. Risk Level: Clearly identifying the current risk level of the circuit breaker, including overall risk and regional risk, accompanied by an intuitive risk heat map for quick identification of high-risk areas. Development Trend: Predicting the future development trend of the circuit breaker's status based on historical data and physical models, including short-term trends (1 to 7 days), medium-term trends (1 to 4 weeks), and long-term trends (1 to 6 months), providing a basis for maintenance planning. Response Recommendations: Providing specific response recommendations for the current risk status, including emergency measures, routine maintenance, and long-term improvement plans to ensure the safe operation of the circuit breaker. The early warning report adopts a standardized format, including text descriptions, data tables, and visualization charts, facilitating quick understanding and decision-making by relevant personnel. Harmonic penetration early warning reports provide a scientific basis for the operation, maintenance, and risk management of circuit breakers, ensuring the safe and stable operation of the power system.

[0055] This embodiment achieves accurate identification of the electric field distribution fingerprint and dielectric penetration probability field of the circuit breaker through nonlinear piecewise harmonic analysis and the construction of a multidimensional penetration feature matrix. This improves the early detection capability of microscopic anomalies and enhances the sensitivity of condition monitoring. By establishing a microscale electrothermal coupling spectrum and performing multi-level analysis, the interaction between the electric and thermal fields inside the circuit breaker can be reflected in real time. This enables precise characterization of the nonlinear region and harmonic penetration paths, allowing for early identification of potential faults. A micro-region diagnostic algorithm based on high-frequency harmonic penetration path spectra enables precise location and quantitative analysis of abnormal thermal zones in the circuit breaker, ensuring the reliability of diagnostic results and improving detection efficiency. The generation and implementation of multi-level protection command sequences enable intelligent adjustment of the circuit breaker's operating status, extending equipment lifespan while ensuring safe operation. Risk analysis based on the circuit breaker's dielectric steady-state index improves the ability to predict and respond to potential risks in the circuit breaker. Through multi-level collaborative analysis from the nanoscale to the global scale, accurate monitoring and prediction of changes in the internal microstate of circuit breakers are achieved, enabling early detection and intervention of various abnormal states, and significantly improving the reliability and safety of circuit breaker operation.

[0056] Example 2

[0057] Please see Figure 2 As shown, for parts not described in detail in this embodiment, please refer to the description in Embodiment 1. A detection system for monitoring the status of primary and secondary fused circuit breakers is provided, including:

[0058] Data acquisition module: Acquires circuit breaker status data, including electromagnetic waveform data, harmonic response characteristics, and temperature distribution gradient;

[0059] Data parsing module: Performs nonlinear piecewise harmonic analysis on electromagnetic waveform data to obtain the circuit breaker electric field distribution fingerprint; constructs a multidimensional penetration feature matrix based on harmonic response characteristics and temperature distribution gradient; identifies abnormal regions in the multidimensional penetration feature matrix to obtain the medium penetration probability field; establishes a microscale electrothermal coupling spectrum based on the circuit breaker electric field distribution fingerprint and the medium penetration probability field.

[0060] Anomaly Trend Analysis Module: Based on the microscale electrothermal coupling spectrum, impedance distortion analysis is performed to obtain the nonlinear region situation table; multi-frequency response analysis is performed on the dielectric parameters in the microscale electrothermal coupling spectrum to obtain the harmonic penetration curve; based on the nonlinear region situation table and harmonic penetration curve, anomaly development trend analysis is performed to obtain the high-frequency harmonic penetration path spectrum.

[0061] The condition calibration module establishes a micro-region diagnostic algorithm based on the high-frequency harmonic penetration path spectrum to obtain the medium condition correction parameters; it applies the medium condition correction parameters to the real-time data of the circuit breaker to perform nonlinear impedance calibration to obtain the circuit breaker anomaly hot zone diagram; and it generates intervention strategies based on the circuit breaker anomaly hot zone diagram to obtain a multi-level protection command sequence.

[0062] Risk Analysis Module: Adjusts the circuit breaker's operating status based on a multi-level protection command sequence to obtain the circuit breaker's medium steady-state index; performs risk analysis based on the circuit breaker's medium steady-state index to obtain a harmonic penetration early warning report; the modules are connected via wired and / or wireless means to achieve data transmission between modules.

[0063] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0064] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0065] In the description of this invention, it should be understood that the terms "first," "second," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance.

[0066] In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0067] In the description of this invention, "several" means one or more, and "a large number" means two or more.

[0068] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0069] All formulas in this manual are dimensionless and calculated numerically. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0070] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A detection method for monitoring the status of a primary and secondary integrated circuit breaker, characterized in that, include: Step S1: Obtain circuit breaker status data, which includes electromagnetic waveform data, harmonic response characteristics, and temperature distribution gradient; Step S2: Perform nonlinear segmented harmonic analysis on the electromagnetic waveform data to obtain the circuit breaker electric field distribution fingerprint; construct a multidimensional penetration feature matrix based on the harmonic response characteristics and the temperature distribution gradient; identify abnormal regions on the multidimensional penetration feature matrix to obtain the medium penetration probability field; establish a microscale electrothermal coupling spectrum based on the circuit breaker electric field distribution fingerprint and the medium penetration probability field. Step S3: Based on the microscale electrothermal coupling spectrum, perform impedance distortion analysis to obtain a nonlinear region status table; perform multi-frequency response analysis on the dielectric parameters in the microscale electrothermal coupling spectrum to obtain harmonic penetration curves; based on the nonlinear region status table and the harmonic penetration curves, perform anomaly development trend analysis to obtain high-frequency harmonic penetration path spectra. Step S4: Establish a micro-region diagnostic algorithm based on the high-frequency harmonic penetration path spectrum to obtain the dielectric state correction parameters; apply the dielectric state correction parameters to the real-time data of the circuit breaker to perform nonlinear impedance calibration to obtain the circuit breaker anomaly hot zone diagram; generate an intervention strategy based on the circuit breaker anomaly hot zone diagram to obtain a multi-level protection command sequence. Step S5: Adjust the circuit breaker's operating status based on the multi-level protection command sequence to obtain the circuit breaker's medium steady-state index; perform risk analysis based on the circuit breaker's medium steady-state index to obtain a harmonic penetration early warning report.

2. The detection method for monitoring the status of a primary and secondary integrated circuit breaker according to claim 1, characterized in that, The methods for obtaining the circuit breaker status data include: Deploy a multi-frequency electromagnetic probe array, harmonic coupling detector, and micro-area temperature sensing network to collect electromagnetic waveform data of the circuit breaker; install a harmonic response recorder, a permeation state transformation monitoring device, and an interface state abnormal waveform collector to collect harmonic response characteristics; configure a micro-thermal zone gradient scanner, a medium property change detector, and a heat flow conduction efficiency analysis device to collect temperature distribution gradients.

3. The detection method for monitoring the status of a primary and secondary integrated circuit breaker according to claim 1, characterized in that, Step S2 includes: Step S21: Perform multi-spectral decomposition on the electromagnetic waveform data to obtain an electromagnetic characteristic spectrum set; perform cross-coupling analysis on the electromagnetic characteristic spectrum set to obtain an electromagnetic spectrum dispersion feature analysis domain; Step S22: Perform fast Fourier transform and spectral domain decomposition on the harmonic response characteristics to obtain multi-frequency response characteristics; perform spatiotemporal heat flux mapping on the temperature distribution gradient to obtain a hotspot energy distribution map; construct a multi-dimensional permeation feature matrix based on the multi-frequency response characteristics and the hotspot energy distribution map; Step S23: Use a nonlinear piecewise harmonic decomposition algorithm to perform an electric field scan on the electromagnetic spectrum dispersion feature analysis domain to obtain the electric field distribution fingerprint of the circuit breaker; Step S24: Use the anomaly region identification algorithm to perform probability analysis on the multidimensional permeation feature matrix to obtain the medium permeation probability field; Step S25: Preset the electrothermal coupling basic framework, and map the circuit breaker electric field distribution fingerprint and the medium penetration probability field to the electrothermal coupling basic framework to form an initial electrothermal coupling prototype; Step S26: Use multi-spectral coding technology to add time-varying characteristics to the initial electrothermal coupling prototype to obtain a dynamic electrothermal coupling body; perform virtual environment verification and calibration on the dynamic electrothermal coupling body to obtain a microscale circuit breaker electrothermal coupling spectrum.

4. The detection method for monitoring the status of a primary and secondary integrated circuit breaker according to claim 3, characterized in that, The electromagnetic waveform data is subjected to multispectral decomposition to obtain a set of electromagnetic characteristic spectra, including: Electromagnetic waveform data is layered into multiple levels according to three observation levels: nanoscale, component scale, and overall scale, to obtain a multi-level electromagnetic window set. The waveform data in the multi-level electromagnetic window set is subjected to harmonic normalization processing to obtain a standardized electromagnetic spectrum vector. Coupled-state analysis is performed on the standardized electromagnetic spectrum vectors to obtain the electromagnetic phase correlation set; The standardized electromagnetic spectrum vector and the electromagnetic phase correlation set are grouped according to the observation level to form an electromagnetic characteristic spectrum set.

5. The detection method for monitoring the status of a primary and secondary integrated circuit breaker according to claim 3, characterized in that, The electromagnetic spectrum dispersion feature analysis domain is scanned using a nonlinear piecewise harmonic decomposition algorithm to obtain the circuit breaker's electric field distribution fingerprint, including: Multi-frequency nonlinear Fourier transform is performed on the electromagnetic spectrum dispersion feature analysis domain to extract the power frequency and higher-order harmonic components, thus obtaining the harmonic component set; Calculate the phase relationship and energy distribution ratio between harmonic components, construct a harmonic characteristic correlation diagram, and obtain the initial data of electric field fingerprint; The initial data of the electric field fingerprint is reduced in dimensionality by applying eigenvector analysis to obtain a compressed electric field eigenvector. Construct the internal electric field response feature space of the circuit breaker, and map the compressed electric field feature vector to the feature space to form the electric field distribution fingerprint of the circuit breaker.

6. The detection method for monitoring the status of a primary and secondary integrated circuit breaker according to claim 1, characterized in that, Step S3 includes: Step S31: Extract impedance parameters from the microscale electrothermal coupling spectrum and construct a set of nonlinear impedance equations; Step S32: Solve the nonlinear impedance equations to obtain the distribution law of the possible impedance of the circuit breaker and form a nonlinear region situation table; Step S33: Perform time-domain and frequency-domain joint analysis on the dielectric parameters in the microscale electrothermal coupling spectrum to identify the coupling characteristics between electromagnetic conduction and heat transfer, and obtain the harmonic penetration curve; Step S34: Align the nonlinear region situation table with the harmonic penetration curve in time and space to construct an anomaly development trend prediction method and obtain the prediction reliability index; Step S35: Based on the predicted reliability index, establish a critical penetration identification algorithm to detect the penetration region in the high-frequency harmonic path and obtain the evolution trajectory of the penetration region; Step S36: Perform feature extraction and pattern recognition on the evolution trajectory of the permeation region to obtain the high-frequency harmonic penetration path spectrum.

7. The detection method for monitoring the status of a primary and secondary integrated circuit breaker according to claim 6, characterized in that, Feature extraction and pattern recognition are performed on the evolution trajectory of the infiltration region to obtain the high-frequency harmonic penetration path spectrum, including: A time-series alignment algorithm is applied to the evolution trajectory of the infiltration region to align the infiltration change sequences at different frequencies, thereby obtaining a normalized trajectory set. A classification system for penetration modes is constructed, including phase-penetrating, amplitude-amplified, energy-accumulating, and interface-dissipating types. Based on historical operational data and theoretical physics analysis, the penetration mode type is labeled for the regularized trajectory set to obtain penetration mode classification data. Calculate the characteristic statistics of different infiltration modes, including frequency of occurrence, infiltration depth and duration, to obtain quantitative indicators of infiltration modes; Based on the quantitative indicators of the penetration mode, a response characteristic profile is constructed to form a high-frequency harmonic penetration path spectrum.

8. The detection method for monitoring the status of a primary and secondary integrated circuit breaker according to claim 1, characterized in that, Step S4 includes: Step S41: Based on the high-frequency harmonic penetration path spectrum, construct a medium anomaly quantification method, calculate the penetration degree of each key parameter, and obtain the medium deviation parameter; Step S42: Establish a micro-region diagnostic algorithm using a multi-parameter correction algorithm to convert the medium deviation parameters into medium state correction parameters; Step S43: Establish a real-time data acquisition channel to acquire the micro-area status data stream of the physical circuit breaker, and apply the medium status correction parameters to calibrate the micro-area status data stream in real time to obtain corrected status data; Step S44: Reconstruct the current abnormal hot zone of the circuit breaker based on the corrected state data, and generate an abnormal hot zone map of the circuit breaker; Step S45: Combine the industry fault knowledge base and equipment historical performance data to conduct a risk level assessment of the circuit breaker abnormal thermal map, and obtain the assessed abnormal thermal map. Step S46: Apply the multi-level protection theory to perform intervention requirement analysis on the evaluated anomaly hot zone map and generate a multi-level protection instruction sequence.

9. The detection method for monitoring the status of a primary and secondary integrated circuit breaker according to claim 8, characterized in that, Applying multi-level protection theory, an intervention requirement analysis is performed on the assessed anomaly hotspot map to generate a multi-level protection instruction sequence, including: A multi-layered protection framework is constructed, encompassing a harmonic suppression layer, a dielectric reinforcement layer, and an operational restriction layer; The evaluated anomaly thermal map is decomposed into multiple levels and mapped to each level in the multi-level protection framework to obtain the layered protection requirements. By using a hierarchical linkage protection algorithm to determine the protection parameters of each level, a multi-level linkage protection scheme is constructed, resulting in an inter-layer collaborative protection strategy. The inter-layer collaborative protection strategy is converted into a specific sequence of execution instructions to generate a multi-level protection instruction sequence.

10. The detection method for monitoring the status of a primary and secondary integrated circuit breaker according to claim 1, characterized in that, Step S5 includes: Step S51: Based on the multi-level protection command sequence, formulate a circuit breaker operation status adjustment scheme, implement coordinated adjustment, and obtain the circuit breaker medium steady-state index; Step S52: Evaluate the stability of the medium steady-state index of the circuit breaker in accordance with industry safety evaluation standards to obtain a steady-state maintenance capability score; Step S53: Set a risk threshold based on the steady-state maintenance capability score, construct a multi-level early warning strategy, and generate risk analysis results; Step S54: Based on the risk analysis results, compile a harmonic penetration early warning report, including penetration stability, risk level and development trend.

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