A high-robustness electromagnetic coil insulation degradation state evaluation method

Abstract

This invention relates to a robust method for assessing the insulation degradation state of electromagnetic coils, comprising: injecting a small-amplitude high-frequency signal into the coil under test and acquiring its response signal; acquiring the current temperature signal of the coil under test using a temperature sensor or obtaining it based on non-invasive signal estimation; constructing an insulation health factor based on the high-frequency response signal of the coil; transforming the health factor at the current temperature into a health factor at a reference temperature using an insulation health factor mapping model; determining a monitoring threshold based on an electromagnetic coil health assessment model at the reference temperature; and finally, completing an accurate assessment of the insulation degradation state of the electromagnetic coil. This invention fully considers the interference of coil temperature on high-frequency electrical parameters. By introducing health factor mapping, it effectively improves the robustness of existing electromagnetic coil insulation degradation monitoring methods based on high-frequency electrical parameters. This is of great significance for avoiding unexpected downtime accidents caused by coil insulation failure and ultimately achieving predictive maintenance of industrial equipment.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic coil insulation life prediction, specifically a robust method for assessing the insulation degradation state of electromagnetic coils. Background Technology

[0002] In industrial production, production equipment and its core components inevitably age and degrade or even malfunction due to long-term operation, ultimately leading to serious problems such as decreased product quality and unexpected downtime. Therefore, accurate early detection of the health status of equipment and its core components is fundamental to avoiding accidents. Coils, as key components of energy conversion devices, have been widely used in various manufacturing sectors since Faraday discovered the principle of electromagnetic induction in the 19th century. Devices and systems utilizing this principle, such as robots, transformers, generators, motors, reactors, solenoid valves, circuit breakers, and relays, have been developed over the centuries. However, coils are subjected to multiple stresses—thermal, electrical, and mechanical—due to their long-term energized operation, leading to frequent insulation failures. Oak Ridge National Laboratory in the United States collected 10 years of solenoid valve failure data used in the safety protection systems of commercial nuclear power plants in the US. The results showed that over 50% of solenoid valve failures were related to the solenoid coil, with the main failure modes being coil short circuits and open circuits. In the application of low-voltage and high-voltage motors, winding insulation failures alone accounted for more than one-third of motor failures. For generators at the power source, research conducted by the International Electricity Council over several years showed that insulation problems caused more than half of generator failures. Unexpected equipment downtime and business shutdowns caused by equipment failures can result in huge economic losses, reduce productivity, and increase equipment repair time and costs. For example, losses in the offshore oil extraction industry due to motor failures can reach 4 million RMB per day. In conclusion, equipment with coils as its core component is not only widely used but also has a high failure rate, and the cascading consequences of its failures are extremely serious. Therefore, the application of fault diagnosis and failure prediction technologies for solenoid coils can not only help ensure the safe and reliable operation of equipment but also reduce maintenance costs and improve equipment utilization.

[0003] like Figure 10 As shown, the insulation degradation process of the electromagnetic coil is divided into two stages: early degradation and late degradation, with the occurrence of an inter-turn short-circuit fault as the dividing point.

[0004] Early degradation stage: The Joule heat generated after the electromagnetic coil is energized makes the coil high temperature. The high temperature causes the conductor (usually copper) to thermally expand, which in turn generates inter-turn compressive stress. Under the long-term action of thermal stress and compressive stress, the performance of the inter-turn insulation material (usually polymer material) continues to degrade and the insulation layer thickness continues to thin, eventually leading to an inter-turn short circuit fault. The degradation process of the coil in this stage is a slow process [5];

[0005] • Late Degradation Stage: After an inter-turn short-circuit fault occurs, the DC resistance of the electromagnetic coil decreases, the current increases, and the temperature rises rapidly, leading to the formation of a hot spot at the short-circuit point. Subsequently, the inter-turn short-circuit fault will rapidly spread from the hot spot, eventually causing the entire coil to fail completely. The degradation process of the coil in this stage is a rapid process.

[0006] Existing insulation health monitoring methods can be broadly categorized into two types: "inter-turn short-circuit fault detection" and "inter-turn insulation degradation monitoring." Since the current / magnetic field signals of the coil change after an inter-turn short-circuit fault occurs, "inter-turn short-circuit fault detection" can be achieved by detecting these signals. Inter-turn short-circuit fault detection methods have already been applied in practical engineering. Typical methods include: motor current analysis methods (MCSA) (e.g., FFT and its extensions, wavelet transform), negative sequence current methods, Park transform methods, machine learning methods (artificial neural networks, support vector machines), and detection methods based on induced electromotive force and leakage flux.

[0007] Since the application of the "inter-turn short-circuit fault detection method" presupposes that an inter-turn short-circuit fault has already occurred, at which point the electromagnetic coil has entered the late degradation stage. The inter-turn short-circuit fault will rapidly spread within the electromagnetic coil, leading to complete coil failure (for example, for a 15kW induction motor, the time from the occurrence of an inter-turn short-circuit fault to complete winding failure is less than 2 seconds). Therefore, the above method contributes limitedly to predictive maintenance and the development of overall maintenance plans. Thus, conducting insulation degradation monitoring research in the early insulation degradation stage, before an inter-turn short circuit occurs, is more practically significant for avoiding sudden failures, achieving predictive maintenance, and developing overall maintenance plans. Current research on insulation degradation monitoring generally uses the high-frequency electrical parameters of the coil as these parameters. Typical studies include using high-frequency impedance and high-frequency capacitance for degradation monitoring. However, high-frequency electrical parameters are not only related to the insulation health of the coil but also to the measurement temperature. Measuring the high-frequency electrical parameters of the same coil at different temperatures yields different results. Considering the significant differences in coil operating conditions during actual engineering practice, and the potential for continuous temperature changes, existing insulation degradation monitoring methods based on high-frequency electrical parameters are susceptible to interference from measurement temperature, resulting in a high false alarm rate. Therefore, this invention proposes a highly robust method for assessing the insulation degradation status of electromagnetic coils, effectively avoiding the influence of measurement temperature on the coil health status assessment results. This invention fully considers the impact of measurement temperature on high-frequency electrical parameters, constructs a health factor mapping model, and avoids the influence of ambient temperature on the detection results, thereby improving the accuracy of coil health status assessment. Summary of the Invention

[0008] To address the issue that existing methods for assessing coil health status do not consider the influence of temperature, this method employs a coil health factor mapping model. This model fully considers the impact of temperature on coil health factors and utilizes the mapping model to accurately identify coil health status under varying operating conditions (temperature changes). This invention not only detects the health status of coils under different temperature environments but also accurately identifies the severity of coil degradation, thus improving the accuracy and reliability of coil health status assessment in industrial settings.

[0009] The technical solution adopted by the present invention to achieve the above objectives is as follows:

[0010] A robust method for assessing the insulation degradation status of electromagnetic coils includes the following steps:

[0011] Data acquisition: Acquire the temperature of the electromagnetic coil under test and the high-frequency electrical response signal of the electromagnetic coil at different temperatures;

[0012] Health Factor Construction: Constructing the health factor HI at the current temperature based on high-frequency electrical response signals measure , used to characterize the health status of electromagnetic coils;

[0013] Health factor mapping: Based on the temperature of the electromagnetic coil under test, and according to the health factor mapping model, the health factor HI at the current temperature of the electromagnetic coil under test is mapped. measure Mapping to a reference temperature yields the health factor HI at that reference temperature. reference ;

[0014] Coil degradation threshold determination and health status assessment: Thresholds are determined based on health factors at a reference temperature. The health factor HI of the electromagnetic coil under test at the reference temperature is then used. reference Compared with the slight degradation state threshold HI at the reference temperature Slight degradation HI (threshold for severe degradation) Severe degradation and fault warning status threshold HI failure By comparison, the health status assessment of the coil under test is completed.

[0015] The temperature of the electromagnetic coil under test can be directly measured using a temperature sensor or obtained based on the coil current signal.

[0016] A high-frequency signal is injected into the electromagnetic coil under test using a high-frequency signal generator, and the high-frequency electrical response signal is collected.

[0017] The health factor is the high-frequency electrical response signal itself or its transformed quantity. The high-frequency electrical response signal itself includes: high-frequency impedance or parasitic capacitance; the transformed quantity includes resonant frequency or root mean square frequency.

[0018] The health factor mapping model takes the health state of a coil as the object and is based on different temperatures T of the electromagnetic coil under test. measure = [t1, t2, ..., tn] and HI measure =[HI t1 HI t2 , ..., HI tn The correlation between the factors is used to establish a corresponding functional relationship model, and curve fitting is performed on it to obtain the fitting model parameters, thus completing the establishment of the health factor mapping model. The correlation includes linear, exponential, and logarithmic relationships.

[0019] The coil degradation threshold is determined as follows:

[0020] The health factor corresponding to a decrease of A% under the baseline temperature condition is taken as the threshold HI for a slightly degenerative state. Slight degradation The health factor corresponding to a decrease of B% in health factor is used as the threshold for severe degeneration (HI). Severe degradationThe health factor corresponding to a decrease of C% in health factor is used as the fault early warning state threshold HI. failure The coil degradation thresholds A, B, and C are determined based on the principle of cumulative damage. Their specific values ​​need to be set according to the evolution trend of the selected health factors in the insulation degradation process, where A < B < C.

[0021] The health status assessment specifically includes:

[0022] 1) When HI reference >HI Slight degradation When the test electromagnetic coil is in a healthy state, it is determined that the test electromagnetic coil is in a healthy state.

[0023] 2) When HI Severe degradation <HI reference ≤HI Slight degradation At that time, the electromagnetic coil under test was determined to be in a state of slight degradation;

[0024] 3) When HI failure <HI reference ≤HI Severe degradation When the test electromagnetic coil is in a severely degraded state, it is determined that the test electromagnetic coil is in a severely degraded state.

[0025] 4) When HI reference ≤HI failure When the test is initiated, the electromagnetic coil under test is determined to be in a fault warning state.

[0026] A robust electromagnetic coil insulation degradation status assessment system includes:

[0027] The data acquisition module is used to acquire the temperature of the electromagnetic coil under test and the high-frequency electrical response signal of the electromagnetic coil at different temperatures;

[0028] The health factor construction module is used to construct the health factor HI at the current temperature based on the high-frequency electrical response signal. measure , used to characterize the health status of electromagnetic coils;

[0029] The health factor mapping module is used to map the health factor HI at the current temperature of the electromagnetic coil under test, according to the health factor mapping model. measure Mapping to a reference temperature yields the health factor HI at that reference temperature. reference ;

[0030] The coil degradation threshold determination and health status assessment module is used to determine thresholds based on health factors at a reference temperature, and to evaluate the health factors HI of the electromagnetic coil under test at the reference temperature. reference Compared with the slight degradation state threshold HI at the reference temperature Slight degradation HI (threshold for severe degradation) Severe degradation and fault warning status threshold HI failureBy comparison, the health status assessment of the coil under test is completed.

[0031] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned robust method for assessing the degradation state of electromagnetic coil insulation.

[0032] A robust electromagnetic coil insulation degradation status assessment system includes a memory and a processor; the memory is used to store a computer program; the processor is used to implement the robust electromagnetic coil insulation degradation status assessment method when the computer program is executed.

[0033] The present invention has the following beneficial effects and advantages:

[0034] 1. This invention can monitor the insulation degradation status of electromagnetic coils online during equipment operation and provide insulation health information. Compared with traditional inter-turn short circuit fault diagnosis methods, it can detect early faults in coil insulation earlier, which is of great significance for realizing predictive maintenance of equipment.

[0035] 2. This invention fully considers the interference of temperature on diagnostic results in practical engineering applications, and introduces a health factor mapping model to map the original health factors to reference temperature conditions, thereby reducing the false alarm rate of the model and improving the robustness of the model. Attached Figure Description

[0036] Figure 1 This is a flowchart of the highly robust electromagnetic coil insulation degradation state assessment method of the present invention;

[0037] Figure 2 This is the accelerated fatigue testing process of the present invention;

[0038] Figure 3 This refers to the DC resistance data of the coil throughout its entire lifespan in this invention;

[0039] Figure 4 The impedance spectrum data of the coil under healthy conditions collected by this invention are obtained under different measurement temperature conditions.

[0040] Figure 5 The impedance spectrum data for the entire life cycle under the reference temperature conditions collected in this invention;

[0041] Figure 6 This is a flowchart of the health factor mapping model of the present invention;

[0042] Figure 7 The health factors of the coil under different temperature conditions of the present invention;

[0043] Figure 8The health factor under the reference temperature conditions of the coil in this invention;

[0044] Figure 9 This is a comparison chart showing the evaluation results of whether the coil measuring temperature of 50°C in this invention uses the health factor mapping model.

[0045] Figure 10 This diagram illustrates the early and late insulation degradation stages of the electromagnetic coil of the present invention. Detailed Implementation

[0046] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings and embodiments. 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 protection scope of the present invention.

[0047] This invention provides a robust method for assessing the insulation degradation state of electromagnetic coils, such as... Figure 1 The diagram shown is a flowchart of the method of this invention. To verify the effectiveness of the proposed method, the following experiments were designed and completed:

[0048] Step 1: Data Collection

[0049] To verify the effectiveness of the method of this invention, an accelerated degradation test was designed and implemented. A typical transformer primary electromagnetic coil (insulation material: polyester fiber, rated power: 25W), widely used in practical engineering, was selected for the accelerated degradation test. Based on... Figure 2 The process involved conducting accelerated fatigue testing. The transformer was overloaded to 3.6 times its rated power (90W) by adding a load to its output terminal, and then placed in an 80°C thermal aging constant-temperature test chamber for an accelerated period of 8 hours. The accelerated test was terminated when the DC resistance of the transformer's primary coil showed a significant decrease. Figure 3 As shown, the DC resistance drops significantly to 0.7218Ω in the 7th cycle, indicating that the coil has short-circuited at this point. To ensure that no inter-turn short circuit has occurred in the coil, impedance data from the first 5 cycles are selected for analysis.

[0050] During the accelerated testing, the sample was removed after a power outage every 8 hours and allowed to stand for 12 hours before impedance measurement began. Specifically, the sample was placed in a temperature-controlled chamber, and the primary coil impedance of the transformer was measured using a high-precision impedance analyzer at 10 temperature levels: 25℃, 30℃, 35℃, 40℃, 45℃, 50℃, 55℃, 60℃, 65℃, and 70℃, with a frequency range of 20Hz-1MHz. This resulted in the construction of a historical dataset Q, where Q = [Q...]. 25 Q30 Q 35 Q 40 ,...Q 70 ,

[0051]

[0052] Where T = 25, 30, 35, 40, 45, 50, 55, 60, 65, 70 are temperature values; k0...k m The number of accelerated degradation cycles experienced by the coil, k0 represents the healthy state without degradation experiments, k i This represents the degradation state of the coil after i accelerated degradation cycles, k m The coil has undergone m degradation cycles, and the cycle preceding the failure occurs, i.e., the end of the coil's lifespan; f1...f n The sampling frequency for the coil impedance data is Z(T, k1, f). n ) represents the coil in its first degradation cycle at a temperature of T℃, corresponding to f n Impedance value at frequency.

[0053] Based on the data obtained from the accelerated testing, the effectiveness of the proposed method for assessing the insulation degradation state of electromagnetic coils was verified. The reference temperature was set to 25°C, and a coil health assessment model was constructed based on this temperature. The effectiveness of the method was verified by comparing the health assessment results before and after mapping using impedance data at different measurement temperatures. Figure 4 As shown, the impedance data of the coil under healthy conditions at different measurement temperatures are presented; Figure 5 Impedance data under different degradation states at the reference temperature are presented. The specific evaluation process is as follows:

[0054] Step 2: Construction of Health Factors

[0055] The RMS characteristic of the high-frequency impedance data acquired in step 1 is extracted as a health factor characterizing the coil's health status, denoted as HI, and used to assess the coil's health. The RMS calculation formula is as follows:

[0056]

[0057] Where L is the length of the high-frequency impedance data in the 20Hz-1MHz frequency band, and Z1 is the high-frequency electrical response signal.

[0058] Step 3: Health Factor Mapping

[0059] Based on the health factor mapping model, the health factor (HI) at the current temperature of the coil under test is... measure ) converted into health factors (HI) at a reference temperature referenceThe process of establishing the health factor mapping model is as follows: Figure 6 As shown:

[0060] Based on such Figure 4 The high-frequency impedance data of the novel coil sample under different temperature conditions are used to construct a health factor mapping model. Based on the aforementioned health factor construction method, HI is constructed respectively, yielding HI. measure =[HI t1 HI t2 , ..., HI tn By observing different temperatures T] measure = [t1, t2, ..., n] and HI measure The correlation between these factors necessitates the selection of an appropriate mapping model function type. The relationships between health factors at different temperatures are shown below. Figure 7 As shown, the data exhibits a linear distribution; therefore, the following linear mapping model is established:

[0061]

[0062] Among them, T reference The reference temperature (i.e., T) reference =25), T measure For measuring the temperature of the coil, HI measure HI is the health factor of the coil under the measured temperature conditions. reference The health factor is the coil reference temperature condition.

[0063] Based on health factors at different temperatures, linear curve fitting was performed using Matlab software to determine the fitting model parameters α = -35.53 and β = -126.97, thus establishing a health factor mapping model.

[0064] Finally, the reliability of the mapping model is verified through error analysis. Figure 8 The health factor under the reference temperature condition of the coil has an absolute error MAE of 69.57 and a relative error MAPE of 0.0018. This indicates that the established mapping model has high accuracy.

[0065] Step 4: Determination of coil insulation degradation threshold and health status assessment

[0066] Based on such Figure 5 The insulation degradation threshold is determined using impedance spectral data over the entire lifespan at a reference temperature. The health factor corresponding to a 50% decrease in health factor at the reference temperature is defined as the threshold for a slight degradation state (HI). Slight degradation The threshold for severe degeneration (HI) is defined as the health factor corresponding to an 80% decrease in health factor. Severe degradationTo minimize the occurrence of sudden failures, the health factor corresponding to a 95% decrease in health factor is defined as the failure warning state threshold HI. failure .

[0067] After determining the coil insulation degradation threshold, the health index HI of the coil under test at the reference temperature is used. reference Compared with the slight degradation state threshold HI at the reference temperature Slight degradation HI (threshold for severe degradation) Severe degradation and fault warning status threshold HI failure The health status assessment of the coil under test is achieved through comparison, using the following comparison method:

[0068] 1) When HI reference >HI Slight deradation The coil under test is determined to be in a healthy state.

[0069] 2) When HI Sever degradation <HI reference ≤HI Slight degradation The coil under test was determined to be in a state of slight degradation.

[0070] 3) When HI failure <HI reference ≤HI Severe degradation The coil under test was determined to be in a severely degraded state.

[0071] 4) When HI reference ≤HI failure The coil under test is determined to be in a fault warning state.

[0072] Thus, a coil health assessment model under reference temperature conditions was established.

[0073] To verify the effectiveness of the proposed method, impedance data under different measurement temperature conditions will be used to compare the health assessment results before and after using the mapping model.

[0074] Taking the coil impedance data measured at 50℃ as an example, such as Figure 9 The blue line represents health factors in different degradation states without using the health factor mapping model; the yellow line represents health factors in different degradation states at the reference temperature after using the health factor mapping model. Comparative evaluation results show that high-frequency electrical parameters are affected by temperature, leading to a high false alarm rate as the unmapped health factors cannot accurately assess the coil degradation state. However, after mapping using the health factor mapping model, the temperature influence is removed, allowing for accurate identification of the severity of coil degradation. For example, in cycle 5, the health factors before mapping were still in a slightly degraded state, while in reality (after mapping), they were in a fault warning state. Therefore, the highly robust electromagnetic coil insulation degradation state assessment method proposed in this invention improves the accuracy and reliability of electromagnetic coil health state assessment.

Claims

1. A robust method for assessing the insulation degradation state of electromagnetic coils, characterized in that, Includes the following steps: Data acquisition: Acquire the temperature of the electromagnetic coil under test and the high-frequency electrical response signal of the electromagnetic coil at different temperatures; Health Factor Construction: Constructing the health factor HI at the current temperature based on high-frequency electrical response signals measure , used to characterize the health status of electromagnetic coils; Health factor mapping: Based on the temperature of the electromagnetic coil under test, and according to the health factor mapping model, the health factor HI at the current temperature of the electromagnetic coil under test is mapped. measure Mapping to a reference temperature yields the health factor HI at that reference temperature. reference ; Coil degradation threshold determination and health status assessment: Thresholds are determined based on health factors at a reference temperature. The health factor HI of the electromagnetic coil under test at the reference temperature is then used. reference Compared with the slight degradation state threshold HI at the reference temperature Slightdegradation HI (threshold for severe degradation) Severedegradation and fault warning status threshold HI failure By comparison, the health status assessment of the coil under test is completed.

2. The method for assessing the insulation degradation state of an electromagnetic coil according to claim 1, characterized in that, The temperature of the electromagnetic coil under test can be directly measured using a temperature sensor or obtained based on the coil current signal.

3. The method for assessing the insulation degradation state of an electromagnetic coil according to claim 1, characterized in that, A high-frequency signal is injected into the electromagnetic coil under test using a high-frequency signal generator, and the high-frequency electrical response signal is collected.

4. The method for assessing the insulation degradation state of an electromagnetic coil according to claim 1, characterized in that, The health factor is the high-frequency electrical response signal itself or its transformed quantity. The high-frequency electrical response signal itself includes: high-frequency impedance or parasitic capacitance; the transformed quantity includes resonant frequency or root mean square frequency.

5. The method for assessing the insulation degradation state of an electromagnetic coil according to claim 1, characterized in that, The health factor mapping model takes the health state of a coil as the object and is based on different temperatures T of the electromagnetic coil under test. measure = [t1, t2, ..., tn] and HI measure =[HI t1 HI t2 , ..., HI tn The correlation between the factors is used to establish a corresponding functional relationship model, and curve fitting is performed on it to obtain the fitting model parameters, thus completing the establishment of the health factor mapping model. The correlation includes linear, exponential, and logarithmic relationships.

6. The method for assessing the insulation degradation state of an electromagnetic coil according to claim 1, characterized in that, The coil degradation threshold is determined as follows: The health factor corresponding to a decrease of A% under the baseline temperature condition is taken as the threshold HI for a slightly degenerative state. Slightdegradation The health factor corresponding to a decrease of B% in health factor is used as the threshold for severe degeneration (HI). Severedegradation The health factor corresponding to a decrease of C% in health factor is used as the fault early warning state threshold HI. failure A, B, and C are coil degradation thresholds, where A < B < C.

7. The method for assessing the insulation degradation state of an electromagnetic coil according to claim 1, characterized in that, The health status assessment specifically includes: 1) When HI reference >HI Slightdegradation When the test electromagnetic coil is in a healthy state, it is determined that the test electromagnetic coil is in a healthy state. 2) When HI Severedegradation <HI reference ≤HI Slightdegradation At that time, the electromagnetic coil under test was determined to be in a state of slight degradation; 3) When HI failure <HI reference ≤HI Severedegradation When the test electromagnetic coil is in a severely degraded state, it is determined that the test electromagnetic coil is in a severely degraded state. 4) When HI reference ≤HI failure When the test is initiated, the electromagnetic coil under test is determined to be in a fault warning state.

8. A highly robust electromagnetic coil insulation degradation status assessment system, characterized in that, include: The data acquisition module is used to acquire the temperature of the electromagnetic coil under test and the high-frequency electrical response signal of the electromagnetic coil at different temperatures; The health factor construction module is used to construct the health factor HI at the current temperature based on the high-frequency electrical response signal. measure , used to characterize the health status of electromagnetic coils; The health factor mapping module is used to map the health factor HI at the current temperature of the electromagnetic coil under test, according to the health factor mapping model. measure Mapping to a reference temperature yields the health factor HI at that reference temperature. reference ; The coil degradation threshold determination and health status assessment module is used to determine thresholds based on health factors at a reference temperature, and to evaluate the health factors HI of the electromagnetic coil under test at the reference temperature. reference Compared with the slight degradation state threshold HI at the reference temperature Slightdegradation HI (threshold for severe degradation) Severedegradation and fault warning status threshold HI failure By comparison, the health status assessment of the coil under test is completed.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements a highly robust method for assessing the insulation degradation state of electromagnetic coils as described in any one of claims 1-7.

10. A highly robust electromagnetic coil insulation degradation status assessment system, characterized in that, It includes a memory and a processor; the memory is used to store a computer program; the processor is used to implement, when executing the computer program, a highly robust method for assessing the insulation degradation state of an electromagnetic coil as described in any one of claims 1-7.

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