Typical fault diagnosis method for rotary transformer

Abstract

The application discloses a typical fault diagnosis method of a resolver, comprising the following steps: 1) extracting envelope lines of two-way sine and cosine signals, and establishing a closed-loop cooperative system of an adaptive filtering algorithm and a phase-locked loop; 2) adopting an adaptive filtering parameter identification and estimation algorithm to realize online diagnosis of amplitude imbalance faults and DC bias faults; 3) according to vector inner product operation after exponential moving average algorithm smoothing processing, realizing diagnosis of incomplete orthogonal faults; 4) adopting a fault diagnosis method based on envelope line peak-to-peak value proportion calculation to realize diagnosis of envelope line oscillation faults; and 5) adopting a diagnosis method based on periodic fluctuation amplitude of d-axis component of a synchronous rotating coordinate system to realize diagnosis of high-order harmonic faults. The several fault diagnosis methods of the resolver proposed in the application are all realized by software, greatly reducing system fault diagnosis cost, constructing a resolver multi-fault parallel diagnosis system, and the proposed method can be applied to the new energy automobile driving field.

Description

Technical Field

[0001] This invention relates to the field of electric drive technology, and in particular to a method for diagnosing typical faults in rotary transformers. Background Technology

[0002] With the continuous development of science and technology and the economy, electric motors are increasingly used in industry, agriculture and daily life. To achieve stable operation of electric motors, the participation of position sensors is indispensable. As a type of electric motor position sensor, the rotary transformer has a stable and robust structure, strong environmental adaptability, low manufacturing cost and high detection accuracy, making it very suitable for application in electric motor control systems in various fields.

[0003] However, installation processes can lead to eccentricity in the rotary transformer, including stator eccentricity, rotor eccentricity, and mixed eccentricity. Furthermore, non-ideal conditions such as inter-turn short circuits during operation must be considered. These factors can cause typical faults in the rotary transformer, such as amplitude imbalance, imperfect quadrature, DC bias, envelope oscillation, and high-order harmonics. These typical faults can cause errors in rotor position determination, leading to unstable motor operation and, in severe cases, damage to components in the motor control system, resulting in industrial production safety issues. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a typical fault diagnosis method for rotary transformers, constructs a parallel diagnosis mechanism for multiple faults in rotary transformers, provides technical support for troubleshooting typical faults in rotary transformers, and reduces system costs.

[0005] The objective of this invention is achieved as follows: a typical fault diagnosis method for a rotary transformer, comprising the following steps:

[0006] 1) Extract the envelopes of the two sine and cosine signals, establish a closed-loop collaborative system of adaptive filtering algorithm and phase-locked loop, realize the estimation of electrical angle, and use this electrical angle as a reference, combined with the characteristics of the envelope itself, to complete the real-time diagnosis of various typical faults of the rotary transformer.

[0007] 2) An adaptive filtering parameter identification and estimation algorithm is adopted, and the estimated electrical angle is used as a reference to perform online diagnosis of amplitude imbalance faults and DC bias faults in the adaptive filtering model.

[0008] 3) Based on the vector inner product operation, the instantaneous inner product value between the sine and cosine envelopes is first calculated, and then the result is smoothed by the exponential moving average algorithm. The orthogonal deviation angle is further calculated, thereby realizing the online diagnosis of incomplete orthogonal faults.

[0009] 4) A fault diagnosis method based on the peak-to-peak ratio of the envelope is used to further extract the envelope peak information synchronized with the electrical angle using the estimated angle, take the modulus for comparison, construct an envelope amplitude inconsistency index, and diagnose the envelope oscillation fault.

[0010] 5) A diagnostic method based on the periodic fluctuation amplitude of the d-axis component of a synchronous rotating coordinate system is used to map the envelope features to the synchronous rotating coordinate system and diagnose high-order harmonic faults by analyzing the fluctuation characteristics of the direct axis component.

[0011] Furthermore, step 1) specifically includes: using peak sampling to obtain the envelope of the sine and cosine fault signals output from the secondary side of the rotary transformer; inputting the envelope into a single synchronous rotating coordinate system phase-locked loop to preliminarily estimate the electrical angle; constructing an adaptive filtering model to preliminarily estimate and eliminate the DC component contained in the signal; and coordinating with the aforementioned phase-locked loop to achieve the estimation of the electrical angle; and combining the characteristics of the envelope itself to achieve real-time diagnosis of various faults in the rotary transformer.

[0012] Furthermore, step 2) specifically includes: using the electrical angle estimated in step 1) as a reference, identifying and estimating the parameters of two types of faults, amplitude imbalance and DC bias, in the constructed adaptive filtering model;

[0013] The model includes three parameters: w1, w2, and w3. w1 and w2 represent the amplitude of the sine and cosine envelope signals, respectively, while w3 represents the DC bias of the sine and cosine envelope signals. In an ideal state, the ratio of w1 to w2 (w1 / w2) of the rotary transformer is approximately 1, and the value of w3 is approximately 0. Whether an amplitude imbalance fault occurs is determined based on whether w1 / w2 deviates from the ideal parameter value, and the degree of amplitude imbalance fault is diagnosed based on the extent to which w1 / w2 deviates from the ideal parameter value. Similarly, whether a DC bias fault occurs is determined based on whether w3 deviates from the ideal parameter value, and the degree of DC bias fault is diagnosed based on the extent to which w3 deviates from the ideal parameter value.

[0014] Furthermore, step 3) specifically includes: calculating the instantaneous inner product of the sine and cosine envelopes, smoothing it using the exponential moving average algorithm, and obtaining the specific angle of orthogonal deviation through arcsine calculation. Ideally, this angle is approximately 0. Based on whether the angle of orthogonal deviation has an error compared to the ideal angle, it is determined whether an incomplete orthogonal fault has occurred, and the degree of incomplete orthogonal fault is diagnosed based on the magnitude of the error.

[0015] Furthermore, step 4) specifically includes: by detecting the zero-crossing point of the sine envelope, capturing two peaks of the cosine envelope within one period, and comparing the two peaks. Ideally, the ratio of their magnitudes is approximately 1. By comparing this ratio with the reference value under ideal conditions, it is determined whether an envelope oscillation fault has occurred, and the degree of envelope oscillation fault is diagnosed based on the magnitude of the error.

[0016] Furthermore, step 5) specifically includes: performing a Park transformation on the sine and cosine envelopes and mapping them to a synchronous rotating coordinate system for analysis; ideally, the direct axis component in the synchronous rotating coordinate system is approximately a constant value; judging whether a higher harmonic fault has occurred based on the fluctuation of the direct axis component, and diagnosing the degree of higher harmonic fault based on the magnitude of the fluctuation.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: 1) Starting from the envelope characteristics of the sine and cosine signals of the rotary transformer, corresponding diagnostic methods are constructed for five typical faults, namely amplitude imbalance, imperfect orthogonality, DC bias, envelope oscillation and higher harmonics, so as to realize the unified modeling and collaborative diagnosis of multiple faults.

[0018] 2) Based on peak sampling, single synchronous rotating coordinate system phase-locked loop, adaptive filtering modeling, vector inner product operation and peak comparison, etc., online time-domain calculation methods are used to complete a variety of typical fault diagnoses. This avoids the traditional frequency domain analysis methods based on fast Fourier transform or long-term data caching, significantly reducing the amount of computation and storage requirements. It is suitable for real-time operation in resource-constrained digital signal processors or embedded controllers.

[0019] 3) The adaptive filtering algorithm is used to perform online diagnosis of amplitude imbalance faults and DC bias faults in rotary transformers. It can maintain stable diagnostic performance even in the presence of noise, parameter drift or changes in operating conditions, thus improving the reliability of fault detection.

[0020] 4) This invention can not only identify the fault types that occur in the rotating transformer, but also quantify the degree of fault through model parameters, phase deviation or equivalent distortion, etc., providing a reliable basis for subsequent fault early warning and fault diagnosis improvement.

[0021] 5) The method described in this invention does not depend on the specific structural parameters or excitation method of the rotary transformer, and can be widely applied to signal processing and status detection systems of rotary transformers of different models and in different application scenarios. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0023] Figure 1 This is a schematic diagram of the rotary transformer structure of the present invention.

[0024] Figure 2 The waveform diagrams of sine and cosine signals and their envelopes under the fault-free state of the rotary transformer of the present invention are shown.

[0025] Figure 3 The waveform diagrams of sine and cosine signals and their envelopes under amplitude imbalance faults of the rotary transformer of this invention are shown.

[0026] Figure 4 The waveform diagrams of sine and cosine signals and their envelopes under incomplete orthogonal faults of the rotary transformer of this invention are shown.

[0027] Figure 5 The waveform diagrams of sine and cosine signals and their envelopes under DC bias faults of the rotary transformer of this invention are shown.

[0028] Figure 6 This invention presents sine and cosine signals and their envelope waveforms under an envelope oscillation fault in a rotary transformer.

[0029] Figure 7 The waveform diagrams of sine and cosine signals and their envelopes under high-order harmonic faults of the rotary transformer of this invention are shown.

[0030] Figure 8 This is a flowchart illustrating a typical fault diagnosis process for the rotary transformer of this invention. Detailed Implementation

[0031] 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.

[0032] A typical fault diagnosis method for a rotary transformer includes the following steps:

[0033] 1) Extract the envelopes of the two sine and cosine signals, establish a closed-loop collaborative system of adaptive filtering algorithm and phase-locked loop, realize the estimation of electrical angle, and use this electrical angle as a reference, combined with the characteristics of the envelope itself, to complete the real-time diagnosis of various typical faults of the rotary transformer.

[0034] The envelope of the sine and cosine fault signals output from the secondary side of the rotary transformer is obtained by peak sampling. The envelope is then input into a single synchronous rotating coordinate system phase-locked loop to preliminarily estimate the electrical angle. An adaptive filtering model is constructed to preliminarily estimate and eliminate the DC component contained in the signal. This model works in conjunction with the aforementioned phase-locked loop to estimate the electrical angle. Furthermore, by combining the characteristics of the envelope itself, real-time diagnosis of various faults in the rotary transformer is achieved.

[0035] 2) An adaptive filtering parameter identification and estimation algorithm is adopted, and the estimated electrical angle is used as a reference to perform online diagnosis of amplitude imbalance faults and DC bias faults in the adaptive filtering model.

[0036] Based on the electrical angle estimated in step 1), the parameters of two faults, amplitude imbalance and DC bias, are identified and estimated in the constructed adaptive filtering model.

[0037] The model includes three parameters: w1, w2, and w3. w1 and w2 represent the amplitude of the sine and cosine envelope signals, respectively, while w3 represents the DC bias of the sine and cosine envelope signals. In an ideal state, the ratio of w1 to w2 (w1 / w2) of the rotary transformer is approximately 1, and the value of w3 is approximately 0. Whether an amplitude imbalance fault occurs is determined based on whether w1 / w2 deviates from the ideal parameter value, and the degree of amplitude imbalance fault is diagnosed based on the extent to which w1 / w2 deviates from the ideal parameter value. Similarly, whether a DC bias fault occurs is determined based on whether w3 deviates from the ideal parameter value, and the degree of DC bias fault is diagnosed based on the extent to which w3 deviates from the ideal parameter value.

[0038] 3) Based on the vector inner product operation, the instantaneous inner product value between the sine and cosine envelopes is first calculated, and then the result is smoothed by the exponential moving average algorithm. The orthogonal deviation angle is further calculated, thereby realizing the online diagnosis of incomplete orthogonal faults.

[0039] The instantaneous inner product of the sine and cosine envelopes is calculated, smoothed by the exponential moving average algorithm, and then the specific angle of orthogonal deviation is obtained by arcsine operation. Ideally, this angle is about 0. Whether an incomplete orthogonal fault has occurred is determined by whether there is an error between the angle of orthogonal deviation and the ideal orthogonal angle, and the degree of incomplete orthogonal fault is diagnosed based on the magnitude of the error.

[0040] 4) A fault diagnosis method based on the peak-to-peak ratio of the envelope is used to further extract the envelope peak information synchronized with the electrical angle using the estimated angle, take the modulus for comparison, construct an envelope amplitude inconsistency index, and diagnose the envelope oscillation fault.

[0041] By detecting the zero-crossing point of the sine envelope, two peaks of the cosine envelope within one period are captured, and the two peaks are compared. Ideally, the ratio of their magnitudes is approximately 1. By comparing this ratio with the reference value under ideal conditions, it is possible to determine whether an envelope oscillation fault has occurred, and the degree of envelope oscillation fault can be diagnosed based on the magnitude of the error.

[0042] 5) A diagnostic method based on the periodic fluctuation of the d-axis component in a synchronous rotating coordinate system is used to map the envelope features to the synchronous rotating coordinate system and diagnose high-order harmonic faults by analyzing the fluctuation characteristics of the direct-axis component.

[0043] Perform a Park transformation on the sine and cosine envelopes and map them to a synchronous rotating coordinate system for analysis. Ideally, the direct-axis components in the synchronous rotating coordinate system are approximately constant. Determine whether a higher harmonic fault has occurred based on the fluctuation of the direct-axis components, and diagnose the degree of higher harmonic fault based on the magnitude of the fluctuation.

[0044] like Figure 1 As shown, the stator and rotor structure of the reluctance rotary transformer studied in this invention has both the primary excitation winding and the secondary output winding wound on the stator. Its rotor has three pole pairs, meaning the motor detects three electrical angle cycles within each rotor cycle. Compared to a rotary transformer with one rotor pole pair, its position detection accuracy is higher. The two sine and cosine signals output from this rotary transformer are input to an analog-to-digital converter (ADC). After digital signal processing, five typical rotary transformer faults (amplitude imbalance fault, incomplete quadrature fault, DC bias fault, envelope oscillation fault, and high-order harmonic fault) are simulated and output through the ADC, providing a fault signal source for subsequent fault diagnosis.

[0045] like Figure 2 As shown, the sine and cosine signals and their envelopes under normal conditions of a rotary transformer are given. The signal frequency is approximately 5.19 kHz, and the peak-to-peak value of the envelope is approximately 2 V.

[0046] like Figure 3 As shown, the sine and cosine signals and their envelopes of the rotary transformer under amplitude imbalance fault are given in detail. Assuming the sine signal is normal, the cosine signal produces a fault with a gain of 1.5 times that of the normal case, realizing an amplitude imbalance fault in which the cosine signal has a gain of 1.5 times that of the sine signal.

[0047] like Figure 4 As shown, the sine and cosine signals and their envelopes under an incompletely orthogonal fault in a rotary transformer are presented in detail. It is assumed that the sine signal is normal, and the cosine signal changes by 30° relative to the normal condition. ° The hysteresis offset achieves a 60° phase difference between sine and cosine signals. ° The incomplete orthogonal fault.

[0048] like Figure 5 As shown, the sine and cosine signals and their envelopes under DC bias faults of a rotary transformer are given in detail. A 1V DC voltage is injected into the sine and cosine signals to achieve a DC bias fault with a 1V bias in the sine and cosine signals.

[0049] like Figure 6 As shown, the sine and cosine signals and their envelopes under the envelope oscillation fault of a rotary transformer are given in detail. It is assumed that the sine and cosine signals generate a gain of 2 times in the positive half-cycle of the envelope, while no gain is generated in the negative half-cycle, thus realizing a periodic oscillation fault in which the ratio of the positive and negative half-cycles of the sine and cosine signal envelope is 2.

[0050] like Figure 7 As shown, the sine and cosine signals and their envelopes under high-order harmonic faults of a rotary transformer are given in detail. 5% third harmonic, 1.5% fifth harmonic, and 0.5% seventh harmonic are injected into the normal sine and cosine signals, respectively, to achieve a high-order harmonic fault with a total harmonic distortion (THD) of 7%.

[0051] like Figure 8 The diagram shows the overall flowchart of a typical fault diagnosis method for a rotary transformer. First, the sine and cosine signals output from the secondary side of the rotary transformer are sampled, and the signal envelope features are extracted using a peak sampling method. A phase-locked loop (PLL) in a single synchronous rotating coordinate system is used to roughly estimate the electrical angle. Then, an adaptive parameter identification model is constructed to initially estimate and remove the DC component from the signal. This model is fed back to the PLL for continuous iteration, achieving accurate estimation of the electrical angle. Based on the accurately estimated electrical angle, online diagnosis of amplitude imbalance faults and DC bias faults is performed in the adaptive filtering model. By calculating the instantaneous cross-correlation coefficient between the sine and cosine envelopes, smoothing the signal, and then calculating the normalized cross-correlation coefficient, the orthogonal deviation angle is derived, enabling the diagnosis of incompletely orthogonal faults. Using the accurately estimated angle, the envelope peak information synchronized with the electrical angle is further extracted. The modulus is compared to construct an envelope amplitude inconsistency index for detecting envelope oscillation faults. Finally, the envelope features are mapped to a synchronous rotating coordinate system, and the fluctuation characteristics of the direct-axis components are analyzed to diagnose higher-order harmonic faults. The entire diagnostic process is based on the envelope characteristics and the accurate electrical angle estimated by the phase-locked loop, forming a typical fault diagnosis system for rotary transformers that involves multiple faults operating in parallel, independent of each other, and complementary to each other.

[0052] Table 1 shows the detailed diagnostic results for amplitude imbalance faults in rotary transformers. Under amplitude imbalance fault conditions, four different levels of fault signals were sequentially input into the fault diagnosis system. The results show that the system can accurately identify the fault type under different fault levels. When the amplitude ratios are 1.5, 5, 9, and 18, the diagnosed fault levels are highly consistent with the preset values, with a maximum error of -1.3302, and the overall error is controlled within a small range.

[0053] Table 1 shows the fault diagnosis results of amplitude imbalance in the rotary transformer of the present invention.

[0054]

[0055] Table 2 shows the detailed results of incomplete orthogonal fault diagnosis for the rotary transformer. Under incomplete orthogonal fault conditions, four different levels of fault signals were sequentially input into the fault diagnosis system. The results show that the system performs well under incomplete orthogonal fault conditions with an orthogonal deviation angle of 15°. ° 30 ° 45 ° and 85 ° It can correctly identify the fault type in all situations. The orthogonal deviation angle obtained from the diagnosis is basically consistent with the preset value, with a maximum error not exceeding 1. ° Furthermore, as the severity of the fault increases, the overall error tends to decrease, reaching 85%. ° The time error does not exceed 0.1 ° ;

[0056] Table 2 shows the results of the incomplete orthogonal fault diagnosis of the rotary transformer of the present invention.

[0057]

[0058] Table 3 shows the detailed diagnostic results for DC bias faults in the rotary transformer. Under DC bias fault conditions, four different levels of fault signals were sequentially input into the fault diagnosis system. The system accurately determined the fault type when the DC components were -5 V, 1 V, 5 V, and 9 V. The diagnosed DC bias value deviated very little from the preset value, with a maximum error of less than 0.3 V. Even under a 1 V small signal injection condition, it maintained a high accuracy of approximately 0.01 V.

[0059] Table 3 shows the DC bias fault diagnosis results of the rotary transformer of the present invention.

[0060]

[0061] Table 4 shows the detailed diagnostic results for envelope oscillation faults in the rotary transformer. Under envelope oscillation fault conditions, four different levels of fault signals were sequentially input into the fault diagnosis system. The system correctly identified the fault type when the amplitude ratio of the positive and negative half-cycles of the envelope was 1.5, 5, 9, and 18. The diagnosed amplitude ratios were close to the preset values, with a maximum error not exceeding 0.7, and maintained stable output across a wide range of fault levels.

[0062] Table 4 shows the fault diagnosis results of the rotary transformer envelope oscillation in this invention.

[0063]

[0064] Table 5 shows the detailed results of high-order harmonic fault diagnosis for the rotary transformer. Under high-order harmonic fault conditions, four different levels of fault signals were sequentially input into the fault diagnosis system. The system accurately identified the fault type when the THD was 7%, 21.5%, 75%, and 140%. The diagnosed THD closely matched the preset value, with a maximum absolute error of no more than 1.52%, maintaining high accuracy even under high harmonic distortion conditions.

[0065] Table 5 shows the results of high-order harmonic fault diagnosis for the rotary transformer of the present invention.

[0066]

[0067] The above description of the embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. It should be noted that those skilled in the art can make several improvements and modifications to the present invention without departing from the principles of the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

Claims

1. A method for diagnosing typical faults in a rotary transformer, characterized in that, Includes the following steps: 1) Extract the envelopes of the two sine and cosine signals, establish a closed-loop collaborative system of adaptive filtering algorithm and phase-locked loop, realize the estimation of electrical angle, and use this electrical angle as a reference, combined with the characteristics of the envelope itself, to complete the real-time diagnosis of various typical faults of the rotary transformer. 2) An adaptive filtering parameter identification and estimation algorithm is adopted, and the estimated electrical angle is used as a reference to perform online diagnosis of amplitude imbalance faults and DC bias faults in the adaptive filtering model. 3) Based on the vector inner product operation, the instantaneous inner product value between the sine and cosine envelopes is first calculated, and then the result is smoothed by the exponential moving average algorithm. The orthogonal deviation angle is further calculated, thereby realizing the online diagnosis of incomplete orthogonal faults. 4) A fault diagnosis method based on the peak-to-peak ratio of the envelope is used to further extract the envelope peak information synchronized with the electrical angle using the estimated angle, take the modulus for comparison, construct an envelope amplitude inconsistency index, and diagnose the envelope oscillation fault. 5) A diagnostic method based on the periodic fluctuation amplitude of the d-axis component of a synchronous rotating coordinate system is used to map the envelope features to the synchronous rotating coordinate system and diagnose high-order harmonic faults by analyzing the fluctuation characteristics of the direct axis component.

2. The method for diagnosing typical faults in a rotary transformer according to claim 1, characterized in that, Step 1) specifically includes: using peak sampling to obtain the envelope of the sine and cosine fault signals output from the secondary side of the rotary transformer; inputting the envelope into a single synchronous rotating coordinate system phase-locked loop to preliminarily estimate the electrical angle; constructing an adaptive filtering model to preliminarily estimate and eliminate the DC component contained in the signal; and coordinating with the aforementioned phase-locked loop to achieve the estimation of the electrical angle. In combination with the characteristics of the envelope itself, real-time diagnosis of various faults of the rotary transformer is achieved.

3. The method for diagnosing typical faults in a rotary transformer according to claim 1, characterized in that, Step 2) specifically includes: using the electrical angle estimated in step 1) as a reference, identifying and estimating the parameters of two types of faults, amplitude imbalance and DC bias, in the constructed adaptive filtering model. The model includes three parameters: w1, w2, and w3. w1 and w2 represent the amplitude of the sine and cosine envelope signals, respectively, while w3 represents the DC bias of the sine and cosine envelope signals. In an ideal state, the ratio of w1 to w2 (w1 / w2) is approximately 1, and the value of w3 is approximately 0. Whether w1 / w2 deviates from the ideal parameter value is used to determine whether an amplitude imbalance fault has occurred, and the degree of deviation of w1 / w2 from the ideal parameter value is used to diagnose the degree of amplitude asymmetry fault. Similarly, whether w3 deviates from the ideal parameter value is used to determine whether a DC bias fault has occurred, and the degree of deviation of w3 from the ideal parameter value is used to diagnose the degree of DC bias fault.

4. The method for diagnosing typical faults in a rotary transformer according to claim 1, characterized in that, Step 3) specifically includes: calculating the instantaneous inner product of the sine and cosine envelopes, smoothing it using the exponential moving average algorithm, and obtaining the specific angle of orthogonal deviation through arcsine calculation. Ideally, this angle is about 0. Based on whether there is an error between the angle of orthogonal deviation and the ideal angle, it is determined whether an incomplete orthogonal fault has occurred, and the degree of incomplete orthogonal fault is diagnosed based on the magnitude of the error.

5. The method for diagnosing typical faults in a rotary transformer according to claim 1, characterized in that, Step 4) specifically includes: by detecting the zero-crossing point of the sine envelope, capturing two peaks of the cosine envelope within one period, and comparing the two peaks. Ideally, the ratio of their magnitudes is about 1. By comparing this ratio with the reference value under ideal conditions, it is determined whether an envelope oscillation fault has occurred, and the degree of envelope oscillation fault is diagnosed based on the magnitude of the error.

6. The method for diagnosing typical faults in a rotary transformer according to claim 1, characterized in that, Step 5) specifically includes: performing a Park transformation on the sine and cosine envelopes and mapping them to a synchronous rotating coordinate system for analysis; ideally, the direct axis component in the synchronous rotating coordinate system is approximately a constant value; judging whether a higher harmonic fault has occurred based on the fluctuation of the direct axis component, and diagnosing the degree of higher harmonic fault based on the magnitude of the fluctuation.

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