A method and system for rapidly evaluating the corona resistance performance of an enameled wire

Abstract

The application discloses a kind of methods and systems for quickly evaluating the test of corona resistance of enameled wire, it is related to motor insulation life evaluation and corona performance test technical field, including simulating the corona stress caused by frequency conversion motor operation to enameled wire, according to frequency band different excitation time and safety protection strategy are automatically matched;Based on different types of sensors, the analysis is carried out to enameled wire electric response signal;Signal multi-domain feature analysis is carried out, and the comprehensive corona tolerance of enameled wire is comprehensively evaluated.The method disclosed in the application constitutes a rigorous logic closed loop in modeling, perception and evaluation level: driven by real excitation model, combined with nonlinear response identification, and then fed back to test control through multi-domain feature score, effectively opening the key link in the whole process of enameled wire insulation corona performance evaluation, so as to build a kind of high authenticity, high robustness, quantifiable fast corona test method.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of motor insulation life evaluation and corona performance testing, in particular to a method and system for rapidly evaluating the corona resistance performance of enameled wire. BACKGROUND

[0002] With the development of motor systems towards high frequency, high speed and high power density, the wide application of variable frequency motors in industrial automation, rail transportation and new energy vehicles puts higher requirements on the reliability of motor winding insulation systems. As a key material for winding insulation, the corona discharge resistance of enameled wire under high frequency and high voltage conditions directly affects the stable operation and service life of the motor system. The existing corona test methods are mostly based on low frequency or constant voltage excitation, which cannot truly reflect the insulation breakdown mechanism under variable frequency conditions and cannot effectively characterize the partial discharge behavior caused by high frequency voltage fluctuations, so there is an urgent need for test methods with better engineering adaptability and diagnostic accuracy.

[0003] However, the current test technology still has many shortcomings in terms of excitation signal design, corona stress simulation, and insulation response detection. The existing methods mostly use constant amplitude or power frequency excitation signals, lack of detailed modeling of the electric field evolution of the insulation system under different frequency conditions, resulting in the inability to effectively simulate the transient corona stress in actual variable frequency motors. At the same time, most test systems do not integrate multiple types of electrical sensor models, cannot realize dynamic modeling and nonlinear feature recognition of sensor response, and ignore the amplitude modulation, phase drift and resonance enhancement phenomena in the response signal. In terms of signal analysis, traditional analysis methods generally use single-domain processing, which cannot integrate time domain, frequency domain and wavelet domain features, making it difficult to accurately identify and health assess the partial discharge pattern under complex multi-source interference. Therefore, the existing technology cannot build a complete "high frequency excitation-response modeling-multi-domain analysis-life evaluation" closed-loop test system, and it is also difficult to realize the rapid and accurate evaluation of the corona resistance of enameled wire under high frequency conditions. SUMMARY

[0004] In view of the above problems, the present application is proposed.

[0005] Therefore, the technical problem solved by the present application is that the existing enameled wire corona resistance performance test method has the problems of lack of frequency band dynamic adjustability of test excitation signal, incomplete modeling of sensor response mechanism, and how to realize high frequency excitation simulation and comprehensive evaluation of insulation performance under actual variable frequency conditions.

[0006] To solve the above technical problems, the application provides the following technical scheme: a method for rapidly evaluating the corona resistance performance test of enameled wire, which comprises simulating the corona stress caused by the operation of a variable frequency motor on enameled wire, automatically matching different excitation times and safety protection strategies according to frequency bands; analyzing the electrical response signals of enameled wire based on different types of sensors; performing multi-domain feature analysis of signals to comprehensively evaluate the corona resistance of enameled wire; the analysis of the electrical response signals of enameled wire comprises laying out multiple types of sensors, and calculating the current response signal based on the consistency of the nonlinear disturbance amplitude and the frequency; the multi-domain feature analysis comprises extracting wavelet energy, envelope energy and spectrum energy, fusing features to construct an insulation health score index and outputting corona resistance situation analysis.

[0007] As a preferred scheme of the method for rapidly evaluating the corona resistance performance test of enameled wire, wherein: the simulation of the corona stress caused by the operation of a variable frequency motor on enameled wire comprises calculating the high-frequency excitation voltage signal applied to the enameled wire test sample according to the action mechanism of the high-frequency stress in the variable frequency motor operating environment, simulating the dynamic corona stress field that the enameled wire bears in actual operation through the periodic sine excitation feature and the exponential decay characteristic decreasing with time.

[0008] As a preferred scheme of the method for rapidly evaluating the corona resistance performance test of enameled wire, wherein: the automatic matching of different excitation times and safety protection strategies comprises taking the center frequency of the high-frequency excitation voltage signal as the basis for judgment, dividing the overall excitation interval into different working condition ranges, taking the center frequency and response parameters as inputs, triggering the test logic path in different scenarios, and analyzing the dynamic response capability and corresponding safety closed-loop control mechanism in the test process through the interactive association of frequency band and time control strategy.

[0009] As a preferred scheme of the method for rapidly evaluating the corona resistance performance test of enameled wire, wherein: the analysis of the electrical response signals of enameled wire comprises installing different types of sensors around the measured enameled wire sample, synchronously collecting various response signals under the action of high-frequency excitation voltage, and each sensor generating amplitude and phase modulation effects according to structural features.

[0010] As a preferred scheme of the method for rapidly evaluating the corona resistance performance test of enameled wire, wherein: the analysis of the electrical response signals of enameled wire further comprises classifying the response signal state based on the local nonlinear response disturbance amplitude, and determining whether the internal oscillation frequency of the sensor and the center frequency of the excitation signal are completely consistent in the frequency coupling state identification.

[0011] As a preferred scheme of the method for testing the corona resistance of the enameled wire according to the application, wherein: the signal multi-domain feature analysis comprises extracting the frequency band energy to identify the corona interference frequency band in the wavelet domain of the current response signal, calculating the Hilbert envelope total energy in the time domain, and identifying the high-frequency characteristic energy distribution through STFT integration in the frequency domain.

[0012] As a preferred scheme of the method for testing the corona resistance of the enameled wire according to the application, wherein: the comprehensive evaluation of the corona resistance of the enameled wire comprises extracting the feature response strength of the sensor in the wavelet domain, the time domain and the frequency domain based on the signal multi-domain feature analysis result, reflecting the relative contribution degree of different sensors under the current test condition through the weight adjustment mechanism, and comprehensively evaluating the insulation state and the corona resistance level of the current enameled wire sample.

[0013] Another object of the application is to provide a system for testing the corona resistance of the enameled wire, which can analyze the electric response signal of the enameled wire based on different types of sensors, and solve the problem that the current testing technology for the corona resistance of the enameled wire has an incomplete modeling of the sensor response mechanism.

[0014] As a preferred scheme of the system for testing the corona resistance of the enameled wire according to the application, wherein: it comprises a stress simulation module, a signal analysis module and a corona resistance evaluation module; the stress simulation module is used for simulating the corona stress caused by the operation of the variable frequency motor on the enameled wire, and automatically matching different excitation time and safety protection strategies according to the frequency band; the signal analysis module is used for analyzing the electric response signal of the enameled wire based on different types of sensors; and the corona resistance evaluation module is used for signal multi-domain feature analysis and comprehensive evaluation of the corona resistance of the enameled wire.

[0015] A computer device comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to realize the steps of the method for testing the corona resistance of the enameled wire.

[0016] A computer readable storage medium stores a computer program, and the computer program is executed by a processor to realize the steps of the method for testing the corona resistance of the enameled wire.

[0017] The method for testing the corona resistance of the enameled wire provided by the application forms a rigorous logical closed loop in the modeling, sensing and evaluation levels: it is driven by a real excitation model, combined with nonlinear response identification, and then fed back to the test control through multi-domain feature scoring, effectively connecting the key links in the whole process of the insulation corona performance evaluation of the enameled wire, thereby constructing a high-realistic, high-robust and quantifiable fast corona test method. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0019] Figure 1 The overall flowchart of a method for quickly evaluating the corona resistance performance test of the enameled wire provided in Embodiment 1 of the present application.

[0020] Figure 2 The overall schematic diagram of a system for quickly evaluating the corona resistance performance test of the enameled wire provided in Embodiment 2 of the present application. DETAILED DESCRIPTION

[0021] In order to make the above objectives, characteristics and advantages of the present application more apparent and comprehensible, the specific embodiments of the present application will be described in detail below with reference to the drawings in the specification. Obviously, the described embodiments are only some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort should belong to the protection scope of the present application.

[0022] Embodiment 1, refer to Figure 1 For an embodiment of the present application, a method for quickly evaluating the corona resistance performance test of the enameled wire is provided, which comprises:

[0023] S1: simulating the corona stress caused by the operation of the variable frequency motor on the enameled wire, and automatically matching different excitation time and safety protection strategies according to the frequency band.

[0024] Further, simulating the corona stress caused by the operation of the variable frequency motor on the enameled wire comprises calculating the high-frequency excitation voltage signal applied on the enameled wire test sample according to the action mechanism of the high-frequency stress in the variable frequency motor operation environment, simulating the dynamic corona stress field borne by the enameled wire in actual operation through the periodic sine excitation characteristics and the exponential decay characteristics decreasing with time.

[0025] It should be noted that automatically matching different excitation time and safety protection strategies comprises taking the center frequency of the high-frequency excitation voltage signal as the basis for judgment, dividing the overall excitation interval into different working condition ranges, taking the center frequency and the response parameter as inputs, triggering the test logic path in different scenarios, and analyzing the dynamic response capability in the test process and the corresponding safety closed-loop control mechanism through the interactive association of the frequency band and the time control strategy.

[0026] It should also be noted that a preferred scheme for calculating the high-frequency excitation voltage signal applied to the enameled wire test sample is represented as:

[0027]

[0028] wherein, is the time The high-frequency excitation voltage signal acting on the enameled wire winding is used to simulate the corona stress caused by the operation of the variable frequency motor on the enameled wire, is the set amplitude, is the time variable, representing the cumulative time from the start of excitation application, is the center frequency of the excitation voltage signal, is the damping coefficient of the excitation waveform.

[0029] It should also be noted that a preferred scheme of the safe closed-loop control mechanism specifically includes, when kHz, it means that the center frequency of the high-frequency excitation voltage signal is low, and the probability of exciting corona is small, which can be matched with long-time signal application and temperature rise control to observe the thermal aging process.

[0030] When kHz, it means that the center frequency of the high-frequency excitation voltage signal is close to the frequency range of industrial variable frequency equipment, and it is easy to excite local corona; cooperate with different types of electrical sensors to collect the response of the enameled wire current signal in the high-frequency excitation environment, and capture the characteristic waveform for subsequent health assessment.

[0031] When kHz, it means that the center frequency of the high-frequency excitation voltage signal is high, and the fluctuation is frequent, which is easy to excite surface corona; it may cause insulation penetration in a short time, and must be matched with time window control and safety relay protection to avoid enameled wire winding burning.

[0032] It should also be noted that by modeling and designing the high-frequency excitation voltage signal applied to the enameled wire sample, a sine periodic excitation superimposed with an exponential decay form is adopted, so that the signal not only has periodic fluctuation characteristics, but also can realize amplitude control with time, thereby accurately simulating the dynamic corona stress field of the variable frequency motor under different operating conditions. The modeling process fully considers the influence of excitation frequency on the sensitivity of corona triggering, and by extracting the center frequency of the signal as a classification basis, the overall test interval is divided into three typical working conditions of low frequency, medium frequency and high frequency, and combined with the preset frequency segment matching strategy, long-time application, sensor monitoring and protection control are called respectively. Especially in high-frequency working conditions, by introducing time window constraints and relay protection strategies, irreversible damage to the insulation system caused by high-energy excitation signals is effectively prevented.

[0033] S2: Based on different types of sensors, analyze the enameled wire response signal.

[0034] Further, different types of sensors are installed around the measured enameled wire sample, and various response signals are synchronously collected under the action of high-frequency excitation voltage. Each sensor produces amplitude and phase modulation effects according to structural characteristics.

[0035] It should be noted that the response signal state is graded based on the local nonlinear response disturbance amplitude, and in the frequency coupling state identification, it is determined whether the internal oscillation frequency of the sensor is completely consistent with the center frequency of the excitation signal.

[0036] It should also be noted that the current response signal is expressed as:

[0037]

[0038] wherein, the current response signal collected by the i th sensor at time t is represented by , the gain is represented by , the sensor number is represented by , the local nonlinear response disturbance amplitude generated by the i th sensor in a high-frequency environment is represented by , the internal oscillation frequency unique to the i th sensor is represented by , and the initial phase offset corresponding to the i th sensor, which simulates the phase difference introduced by the sensor position layout or signal coupling delay, is represented by

[0039] When , it indicates that the response signal measured by the sensor is approximately linear, corresponding to good enameled wire insulation without corona interference; when , it indicates that the response signal measured by the sensor appears high-amplitude nonlinear oscillation and phase drift, representing the presence of partial discharge characteristic signals, and the structure or coating of the enameled wire may have defects or damage, which can be early warned by extracting envelope peak and energy characteristics; when , it indicates that the center frequency of the high-frequency excitation voltage signal coincides with the internal oscillation frequency, the response signal measured by the sensor appears amplification resonance effect, and the output signal will appear a maximum amplitude, which may cause false alarm, and such resonance needs to be suppressed by hardware or modeled and filtered in engineering.

[0040] ​​​​​It should also be noted that multiple types of sensors were placed around the enameled wire sample. Based on the structural parameters and response characteristics of each sensor, their output signals were collected under high-frequency excitation. A mathematical model was then developed to represent the response signal as a modulated version of the original excitation signal, taking into account three key factors: amplitude perturbation, phase shift, and frequency coupling. Furthermore, a perturbation amplitude metric was introduced for state classification. When the perturbation was zero, the insulation was considered intact, while when the perturbation amplitude exceeded a set threshold of 0.2, it was identified as evidence of partial discharge. Frequency consistency judgment logic was also implemented. If the sensor's internal oscillation frequency matched the center frequency of the excitation signal, it was identified as resonant amplification, requiring filtering or suppression to avoid false positives. A dynamic modeling framework tailored to the behavioral characteristics of different sensors was constructed, enabling accurate local identification and state classification of complex response signals such as current and electric fields. Furthermore, frequency matching logic enhanced the system's defense against false alarms such as resonant amplification, ensuring the credibility of the response data and the stability of the diagnostic results.

[0041] S3: Perform multi-domain signal feature analysis to comprehensively evaluate the enameled wire's comprehensive corona tolerance.

[0042] Furthermore, multi-domain feature analysis of the signal is performed, including extracting the frequency band energy of the current response signal in the wavelet domain to identify the partial discharge interference frequency band; calculating the total energy of the Hilbert envelope in the time domain; and identifying the high-frequency feature energy distribution through STFT integration in the frequency domain.

[0043] It should be noted that a preferred solution for extracting frequency band energy to identify the PD interference frequency band specifically includes analyzing wavelet energy characteristics, which can be expressed as:

[0044]

[0045] in, Indicates the The first sensor The wavelet energy of each frequency band is summarized to detect the corona discharge disturbance intensity of different frequency bands. Indicates the The sensor in the The first one brought by the small ball decomposition coefficients.

[0046] Calculate the total Hilbert envelope energy, expressed as:

[0047]

[0048] in, Indicates the The total Hilbert envelope energy of each sensor is mainly used to identify the transient excitation voltage signal and the corona pulse envelope. is the sampling time window length, Indicates the current response signal The result after Hilbert transform is the orthogonal complex dual part of the signal.

[0049] Calculate the local energy characteristics of the STFT spectrum, expressed as:

[0050]

[0051] in, For the The total spectrum energy of each sensor in the high frequency range is extracted based on the STFT Fourier window integration, which is used to reflect the corona signal intensity in the high frequency band. Indicates the Sensors at time The current response signal collected at the moment, the integration interval [ , Each frequency point in ] corresponds to an energy density, Represents the lowest frequency boundary for spectrum energy calculation, Denotes the highest frequency boundary for spectral energy calculation.

[0052] It should also be noted that the comprehensive evaluation of the comprehensive corona tolerance of the enameled wire includes extracting the characteristic response intensity of the sensor in the wavelet domain, time domain and frequency domain based on the multi-domain feature analysis results of the signal, and reflecting the relative contribution of different sensors under the current test conditions through the weight adjustment mechanism, so as to comprehensively evaluate the insulation status and corona tolerance level of the current enameled wire sample.

[0053] It should also be noted that a preferred method for comprehensively evaluating the comprehensive corona tolerance of enameled wire includes comprehensively calculating the insulation health score index based on wavelet energy summary, Hilbert envelope total energy and spectrum total energy, which is expressed as:

[0054]

[0055] in, It is an insulation health score indicator, which indicates the comprehensive corona tolerance of the enameled wire sample under the current test state. represents the total number of deployed sensors, For the The weighting coefficients of the sensors, Number the historical enameled wire samples. Indicates the number of historical enameled wire samples, For the The sensitivity adjustment weight of the residual of the historical enameled wire samples to the current scoring result, Indicates the current output and The error term of the health score between the enameled wire samples, is a residual penalty term regularization coefficient, preventing overfitting, is a spectrum suppression factor, adjusting the interference of high-frequency noise or peak energy.

[0056] When , the insulation state of the current enameled wire sample is determined to be a serious degradation state, triggering a high-risk warning, and the test needs to be terminated immediately or the enameled wire sample needs to be replaced; when , the insulation state of the current enameled wire sample is determined to be a moderate degradation state, and a periodic retest, load reduction or continuous monitoring mode is adopted, and the current enameled wire sample is marked as a key object of attention; when , the insulation state of the current enameled wire sample is determined to be a healthy and stable state, and the enameled wire has good corona resistance and can be continuously operated without intervention.

[0057] It should also be noted that the collected electrical response signals are subjected to multi-dimensional feature extraction, including: decomposition coefficient energy in wavelet domain, envelope total energy in time domain, and high-frequency integral energy in frequency domain. Subsequently, the above features are input into the scoring function in combination with the weighting coefficients of each sensor and the spectrum suppression factor to calculate a unified insulation health score index. Further, a historical residual adjustment term and a regularization factor are integrated to prevent overfitting, and an exponential function mapping mechanism is introduced to convert the scoring result into a remaining life prediction value. The scoring result can trigger different test decision paths, such as continuous operation, stage monitoring or immediate replacement. A scoring model is established, which is driven by multi-source data, integrates feature parameters and adjusts historical residuals, to comprehensively evaluate and objectively quantify the insulation state of enameled wire, has strong expansibility and engineering feasibility, and can support real-time decision making and maintenance strategy formulation in production or experimental environment.

[0058] Embodiment 2, refer to Figure 2 , provides a system for quickly evaluating the corona resistance performance test of enameled wire, including a stress simulation module, a signal analysis module and a corona resistance evaluation module.

[0059] The stress simulation module is used to simulate the corona stress caused by the operation of the variable frequency motor on the enameled wire, and automatically matches different excitation times and safety protection strategies according to the frequency band; the signal analysis module is used to analyze the electrical response signals of the enameled wire based on different types of sensors; and the corona resistance evaluation module is used to perform multi-domain feature analysis of the signals and comprehensively evaluate the comprehensive corona resistance of the enameled wire.

[0060] If the functions are implemented in software, the functions can be stored in or implemented as one or more instructions or code on a computer-readable medium. Computer-readable media include both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage medium can be any available medium that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, or twisted pair, then the coaxial cable, fiber optic cable, or twisted pair are included in the definition of medium. Disk and disc, as used herein, include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), and Blu-Ray® disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0061] In other words, like a human driver of a vehicle, an autonomous vehicle can be programmed to follow traffic laws and to make decisions based on its environment. For example, an autonomous vehicle can be programmed to follow a speed limit, to stop at a stop sign, to yield to a pedestrian, to merge onto a highway, to change lanes, to park, and so on. In some embodiments, an autonomous vehicle can be programmed to follow traffic laws and to make decisions based on its environment using a machine learning algorithm. For example, an autonomous vehicle can be programmed to follow a speed limit, to stop at a stop sign, to yield to a pedestrian, to merge onto a highway, to change lanes, to park, and so on using a machine learning algorithm.

[0062] In other words, like a human driver of a vehicle, an autonomous vehicle can be programmed to follow traffic laws and to make decisions based on its environment. For example, an autonomous vehicle can be programmed to follow a speed limit, to stop at a stop sign, to yield to a pedestrian, to merge onto a highway, to change lanes, to park, and so on. In some embodiments, an autonomous vehicle can be programmed to follow traffic laws and to make decisions based on its environment using a machine learning algorithm. For example, an autonomous vehicle can be programmed to follow a speed limit, to stop at a stop sign, to yield to a pedestrian, to merge onto a highway, to change lanes, to park, and so on using a machine learning algorithm.

[0063] It should be understood that portions of the present application can be implemented in hardware, software, firmware, or combinations thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, implementation can be with any or a combination of the following technologies, which are all well known in the art: a discrete logic circuit having logic gates for implementing logic functions upon an application of data signals, an application specific integrated circuit having appropriate combinational logic gates, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be understood that the above-described embodiments are merely given as examples of the technical solution of the present application and are not to be interpreted in a limiting manner, and that for persons skilled in the art, modifications or equivalent replacements can be made to the technical solution of the present application without departing from the spirit and scope of the present application, and all such modifications or equivalent replacements shall be encompassed in the scope of the claims of the present application.

Claims

1. A method for quickly evaluating the corona resistance of enameled wire, characterized in that: include: Simulate the corona stress caused by variable frequency motor operation on enameled wire, and automatically match different excitation times and safety protection strategies according to the frequency band; Analyze the electrical response signal of enameled wire based on different types of sensors; Perform multi-domain signal feature analysis to comprehensively evaluate the enameled wire's comprehensive corona tolerance; The analysis of the electrical response signal of the enameled wire includes deploying multiple types of sensors and calculating the current response signal based on the consistency of the nonlinear disturbance amplitude and frequency; The multi-domain feature analysis includes extracting wavelet energy, envelope energy and spectrum energy, fusing the features to construct insulation health score indicators and outputting corona tolerance analysis; The simulation of the corona stress caused by the operation of the variable frequency motor on the enameled wire includes calculating the high-frequency excitation voltage signal applied to the enameled wire test sample based on the action mechanism of the high-frequency stress in the operating environment of the variable frequency motor, and simulating the dynamic corona stress field borne by the enameled wire during actual operation through the periodic sinusoidal excitation characteristics and the exponential decay characteristics that decrease over time; The automatic matching of different excitation times and safety protection strategies includes using the center frequency of the high-frequency excitation voltage signal as a judgment basis, dividing the overall excitation range into different operating ranges, using the center frequency and response parameters as inputs, triggering the test logic path under different scenarios, and analyzing the dynamic response capability of the test process and the corresponding safety closed-loop control mechanism through the interaction between the frequency segment and the timing control strategy; The multi-domain feature analysis of the signal includes extracting frequency band energy of the current response signal in the wavelet domain to identify the partial discharge interference frequency band; calculating the total energy of the Hilbert envelope in the time domain; and identifying the high-frequency feature energy distribution through STFT integration in the frequency domain.

2. The method for rapidly evaluating the corona resistance of enameled wire according to claim 1, wherein: The analysis of the electrical response signal of the enameled wire includes installing different types of sensors around the enameled wire sample to be tested, and synchronously collecting various response signals under the action of high-frequency excitation voltage. Each sensor produces amplitude and phase modulation effects according to its structural characteristics.

3. The method for rapidly evaluating the corona resistance of enameled wire according to claim 2, wherein: The analysis of the electrical response signal of the enameled wire further includes grading the response signal state based on the local nonlinear response disturbance amplitude, and in the frequency coupling state identification, determining whether the internal oscillation frequency of the sensor is completely consistent with the center frequency of the excitation signal.

4. The method for rapidly evaluating the corona resistance of enameled wire according to claim 1, wherein: The comprehensive evaluation of the comprehensive corona tolerance of the enameled wire includes extracting the characteristic response intensity of the sensor in the wavelet domain, time domain and frequency domain based on the multi-domain characteristic analysis results of the signal, reflecting the relative contribution of different sensors under the current test conditions through a weight adjustment mechanism, and comprehensively evaluating the insulation state and corona tolerance level of the current enameled wire sample.

5. A system using the method for rapidly evaluating the corona resistance of enameled wire according to any one of claims 1 to 4, characterized in that: Including stress simulation module, signal analysis module, corona tolerance assessment module; The stress simulation module is used to simulate the corona stress caused by the operation of the variable frequency motor on the enameled wire, and automatically matches different excitation times and safety protection strategies according to the frequency band; The signal analysis module is used to analyze the electrical response signal of the enameled wire based on different types of sensors; The corona tolerance evaluation module is used to perform multi-domain feature analysis of signals and comprehensively evaluate the comprehensive corona tolerance of the enameled wire.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for rapidly evaluating the corona resistance performance of an enameled wire according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for rapidly evaluating the corona resistance performance of an enameled wire according to any one of claims 1 to 4 are implemented.

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