Permanent magnet synchronous motor fault diagnosis method and device based on zero sequence voltage signal

Abstract

This invention discloses a method and apparatus for fault diagnosis of permanent magnet synchronous motors based on zero-sequence voltage signals. The method includes: connecting a zero-sequence symmetrical resistor network to the input terminals of the three-phase stator windings of the permanent magnet synchronous motor; measuring the voltage difference between the neutral point of the three-phase windings and the neutral point of the zero-sequence resistor network to obtain a zero-sequence voltage signal; extracting the fundamental frequency amplitude as a fault indicator using Fast Fourier Decomposition based on the zero-sequence voltage signal, and comparing it with a set threshold to determine whether a static eccentricity fault or a stator inter-turn short-circuit fault exists; if the value is greater than the threshold, a negative d-axis current is applied to the permanent magnet synchronous motor to obtain the fault indicator under this operating condition, and the difference is calculated with the aforementioned fault indicator to obtain the fault indicator difference value; based on the fault indicator difference value, if the value is greater than 0, a static eccentricity fault is diagnosed; if the value is less than 0, a stator inter-turn short-circuit fault is diagnosed. This method can be used to diagnose and distinguish between static eccentricity faults and stator inter-turn short-circuit faults in permanent magnet synchronous motors.

Description

Technical Field

[0001] This application relates to the field of fault diagnosis of permanent magnet synchronous motors, specifically to a method and apparatus for fault diagnosis of permanent magnet synchronous motors based on zero-sequence voltage signals. Background Technology

[0002] Permanent magnet synchronous motors (PMSMs) possess advantages such as high efficiency, high power density, and ease of control, and are widely used in new energy power generation and electric drive fields. However, due to the complex coupling effects of electromagnetic, thermal, and mechanical stresses in the operating environment, the reliability of PMSMs is affected by various types of faults, which can even lead to safety accidents in severe cases. Among these, rotor static eccentricity faults and stator inter-turn short-circuit faults are common fault types. Therefore, the diagnosis of rotor static eccentricity faults and stator inter-turn short-circuit faults is of great significance. Among existing technologies, stator current analysis (MCSA) is one of the most commonly used methods for diagnosing eccentricity faults and stator inter-turn short-circuit faults, but there is currently no method specifically for distinguishing between static eccentricity faults and stator inter-turn short-circuit faults. Using detection coils can achieve the diagnosis and differentiation of various faults, but it is an invasive method with high implementation costs and maintenance difficulties. In addition, methods based on noise and vibration analysis have also been applied to diagnose eccentricity faults, but they are susceptible to interference. Summary of the Invention

[0003] The purpose of this application is to provide a method and apparatus for fault diagnosis of permanent magnet synchronous motors based on zero-sequence voltage signals, so as to solve the technical problem in the related art of being unable to distinguish between static eccentricity faults and stator inter-turn short-circuit faults.

[0004] According to a first aspect of the embodiments of this application, a fault diagnosis method for a permanent magnet synchronous motor based on a zero-sequence voltage signal is provided, comprising:

[0005] S1: Connect a zero-sequence symmetrical resistor network to the input terminals of the three-phase stator windings of the permanent magnet synchronous motor, and measure the voltage difference between the neutral point of the three-phase windings and the neutral point of the zero-sequence resistor network to obtain the zero-sequence voltage signal.

[0006] S2: Based on the zero-sequence voltage signal, use fast Fourier decomposition to extract the fundamental frequency amplitude as a fault indicator, and compare it with a set threshold to determine whether there is a static eccentricity fault or a stator inter-turn short circuit fault. If it is greater than the threshold, then execute S3.

[0007] S3: Given a negative d-axis current of the permanent magnet synchronous motor, obtain the fault index under this operating condition, and subtract it from the fault index in S2 to obtain the fault index difference value.

[0008] S4: Based on the difference in the fault indicators, if the value is greater than 0, it is diagnosed as a static eccentricity fault; if the value is less than 0, it is diagnosed as a stator inter-turn short circuit fault.

[0009] Optionally, a zero-sequence symmetrical resistor network is connected to the input terminals of the three-phase stator windings of the permanent magnet synchronous motor, and the zero-sequence voltage signal is obtained by measuring the voltage difference between the neutral point of the three-phase windings and the neutral point of the zero-sequence resistor network, including the following sub-steps:

[0010] S11: Select the three resistors used in the zero-sequence symmetric resistor network;

[0011] S12: Connect one end of each of the three resistors directly to form the neutral point of the zero-sequence resistor network, and connect the other end to the input terminal of the three-phase stator winding of the permanent magnet synchronous motor.

[0012] S13: Connect the positive and negative terminals of the voltage sensor to the neutral point of the three-phase winding of the permanent magnet synchronous motor and the neutral point of the zero-sequence resistor network, respectively, and sample to obtain the zero-sequence voltage signal.

[0013] Optionally, based on the zero-sequence voltage signal, the fundamental frequency amplitude is extracted using Fast Fourier Decomposition as a fault indicator and compared with a set threshold to determine whether a static eccentricity fault or a stator inter-turn short-circuit fault exists, including the following sub-steps:

[0014] S21: Based on the rotor position signal from the permanent magnet synchronous motor position sensor, select the zero-sequence voltage signal of a complete mechanical cycle and perform fast Fourier decomposition to obtain the amplitude of each frequency harmonic.

[0015] S22: Determine the fundamental frequency based on the speed signal and the number of motor pole pairs, and extract the fundamental frequency amplitude from the amplitude of each frequency harmonic as a fault indicator;

[0016] S23: Compare the fault index with a set threshold. If it is less than the set threshold, it is determined that there is no static eccentricity fault or stator inter-turn short circuit fault. If it is greater than the set threshold, it is determined that there is a static eccentricity fault or stator inter-turn short circuit fault.

[0017] Optionally, given a negative d-axis current of the permanent magnet synchronous motor, the fault index under this operating condition is obtained, and the difference is calculated with the fault index in S2 to obtain the fault index difference value, including the following sub-steps:

[0018] S31: Given the negative d-axis current of the permanent magnet synchronous motor;

[0019] S32: Repeat steps S21 and S22 to obtain the fault indicators under the given negative d-axis current condition;

[0020] S33: Subtract the fault index described in S32 from the fault index described in S22 to obtain the fault index difference value.

[0021] According to a second aspect of the embodiments of this application, a fault diagnosis device for a permanent magnet synchronous motor based on a zero-sequence voltage signal is provided, characterized in that it includes:

[0022] The zero-sequence voltage sampling module is used to connect a zero-sequence symmetrical resistor network to the input terminals of the three-phase stator windings of a permanent magnet synchronous motor, and measure the voltage difference between the neutral point of the three-phase windings and the neutral point of the zero-sequence resistor network to obtain the zero-sequence voltage signal.

[0023] The judgment module is used to extract the fundamental frequency amplitude as a fault indicator based on the zero-sequence voltage signal using fast Fourier decomposition, and compare it with a set threshold to determine whether there is a static eccentricity fault or a stator inter-turn short circuit fault. If it is greater than the threshold, the difference module is executed.

[0024] The difference module is used to obtain the fault index under the given negative d-axis current of the permanent magnet synchronous motor, and to calculate the difference between the fault index in the judgment module to obtain the fault index difference value.

[0025] The diagnostic module is used to diagnose a static eccentricity fault based on the difference in the fault indicators. If the value is greater than 0, the fault is diagnosed as a stator inter-turn short circuit fault.

[0026] According to a third aspect of the embodiments of this application, an electronic device is provided, comprising:

[0027] One or more processors;

[0028] Memory, used to store one or more programs;

[0029] When the one or more programs are executed by the one or more processors, the one or more processors perform the method as described in the first aspect.

[0030] According to a third aspect of the embodiments of this application, a computer-readable storage medium is provided that stores computer instructions thereon, which, when executed by a processor, implement the steps of the method as described in the first aspect.

[0031] The technical solutions provided by the embodiments of this application may include the following beneficial effects:

[0032] As can be seen from the above embodiments, this application connects a zero-sequence symmetrical resistor network to the input terminals of the three-phase stator windings of a permanent magnet synchronous motor. The voltage difference between the neutral point of the three-phase windings and the neutral point of the zero-sequence resistor network is measured to obtain a zero-sequence voltage signal. Based on the zero-sequence voltage signal, a Fast Fourier Transform (FFT) is used to extract the fundamental frequency amplitude as a fault indicator, which is then compared with a set threshold to determine whether a static eccentricity fault or a stator inter-turn short-circuit fault exists. If the value is greater than the threshold, a negative d-axis current is applied to the permanent magnet synchronous motor to obtain the fault indicator under this condition. The difference between the fault indicator and the values ​​obtained in the aforementioned steps is calculated to obtain the fault indicator difference value. If the fault indicator difference value is greater than 0, a static eccentricity fault is diagnosed; if the fault indicator difference value is less than 0, a stator inter-turn short-circuit fault is diagnosed. The fault diagnosis method proposed in this application overcomes the technical problem that static eccentricity faults and stator inter-turn short-circuit faults have the same fault characteristics and are difficult to distinguish, thus achieving the technical effect of accurately diagnosing and distinguishing the two types of faults. It also has advantages such as being non-invasive, easy to implement, and capable of online diagnosis.

[0033] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0034] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0035] Figure 1 This is a flowchart illustrating a fault diagnosis method for a permanent magnet synchronous motor based on a zero-sequence voltage signal, according to an exemplary embodiment.

[0036] Figure 2 V is shown according to an exemplary embodiment. 0,m Measurement diagram.

[0037] Figure 3 This is a model of a 10-pole, 9-slot surface-mounted permanent magnet synchronous motor according to an exemplary embodiment.

[0038] Figure 4 It is the zero-sequence voltage waveform under rated operating conditions, in a healthy state, under static eccentricity fault, and under stator inter-turn short-circuit fault, as illustrated in an exemplary embodiment.

[0039] Figure 5 It is the zero-sequence voltage spectrum of the rated operating condition under healthy state, static eccentricity fault, and stator inter-turn short circuit fault obtained by Fourier decomposition according to an exemplary embodiment.

[0040] Figure 6 These are fault index values ​​for static eccentricity fault and stator inter-turn short circuit fault under operating conditions with d-axis current of 0A and -4A, as shown in an exemplary embodiment.

[0041] Figure 7 This is a block diagram illustrating a fault diagnosis device for a permanent magnet synchronous motor based on a zero-sequence voltage signal, according to an exemplary embodiment. Detailed Implementation

[0042] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0043] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0044] Figure 1 This is a flowchart illustrating a method for fault diagnosis and differentiation of a permanent magnet synchronous motor based on a zero-sequence voltage signal, according to an exemplary embodiment. Figure 1 As shown, the method may include the following steps:

[0045] S1: Connect a zero-sequence symmetrical resistor network to the input terminals of the three-phase stator windings of the permanent magnet synchronous motor, and measure the voltage difference between the neutral point of the three-phase windings and the neutral point of the zero-sequence resistor network to obtain the zero-sequence voltage signal. This includes the following sub-steps:

[0046] S11: Select the three resistors used in the zero-sequence symmetric resistor network;

[0047] Specifically, in this embodiment, the resistance value of the zero-sequence symmetrical resistor network is selected as 30kΩ, which is much larger than the phase resistance value of the permanent magnet synchronous motor. This is beneficial to reduce the interference of motor-side factors on the zero-sequence voltage measurement.

[0048] S12: Connect one end of the three resistors directly to form the neutral point of the zero-sequence resistor network, and connect the other end to the input terminal of the three-phase stator winding of the permanent magnet synchronous motor.

[0049] S13: Connect the positive and negative terminals of the voltage sensor to the neutral point of the three-phase winding of the permanent magnet synchronous motor and the neutral point of the zero-sequence resistor network, respectively, and sample to obtain the zero-sequence voltage signal. The zero-sequence voltage signal is not affected by the high-frequency common-mode voltage on the inverter side.

[0050] S2: Based on the zero-sequence voltage signal, use Fast Fourier Decomposition to extract the fundamental frequency amplitude as a fault indicator, and compare it with a set threshold to determine whether there is a static eccentricity fault or a stator inter-turn short circuit fault. If it is greater than the threshold, proceed to S3, which includes the following sub-steps:

[0051] S21: Based on the rotor position signal from the permanent magnet synchronous motor position sensor, select the zero-sequence voltage signal of a complete mechanical cycle and perform fast Fourier decomposition to obtain the amplitude of each frequency harmonic.

[0052] Specifically, in this embodiment, the motor is a 10-pole, 9-slot surface-mounted permanent magnet synchronous motor, such as... Figure 3 As shown, the rotor position angle corresponding to one complete mechanical cycle is 1800° electrical degrees. The zero-sequence voltage waveforms under healthy conditions, static eccentricity faults, and stator inter-turn short-circuit faults under one complete mechanical cycle are as follows: Figure 4 As shown. Under healthy conditions, the average air gap length is 1 mm. A static eccentricity fault is defined as the rotor's geometric center and rotation center simultaneously shifting 0.5 mm along the x-axis. A stator inter-turn short-circuit fault short-circuits 20 turns out of the 180 turns in phase A winding, with a short-circuit resistance of 0.1 Ω. The motor operates under rated conditions at a speed of 500 rpm and a phase current amplitude of 4 A.

[0053] S22: Determine the fundamental frequency based on the speed signal and the number of motor pole pairs, and extract the fundamental frequency amplitude from the amplitude of each frequency harmonic as a fault indicator;

[0054] Specifically, in this embodiment, the motor has 5 pole pairs, a rated operating speed of 500 rpm, and a calculated fundamental frequency of 41.67 Hz. The Fourier decomposition results are as follows: Figure 5 As shown, the fault index values ​​under healthy condition, static eccentricity fault, and stator inter-turn short circuit fault are 0V, 1.36V, and 0.86V, respectively. Both static eccentricity fault and stator inter-turn short circuit fault will produce three-phase imbalance characteristics in permanent magnet synchronous motors with rotating asymmetrical windings, resulting in the appearance of a fundamental frequency component in the zero-sequence voltage. Therefore, extracting the fundamental frequency amplitude from the zero-sequence voltage signal as a fault index can effectively diagnose these two types of faults.

[0055] S23: Compare the fault index with a set threshold. If it is less than the set threshold, it is determined that there is no static eccentricity fault or stator inter-turn short circuit fault. If it is greater than the set threshold, it is determined that there is a static eccentricity fault or stator inter-turn short circuit fault.

[0056] Specifically, in this embodiment, the threshold is set to 0.5V, such as... Figure 5 As shown by the threshold line, the fault indicator value in the healthy state is 0V, which is less than the threshold. Therefore, according to... Figure 1The fault diagnosis flowchart shown determines whether there is a static eccentricity fault or a stator inter-turn short circuit fault. If the fault index value is greater than 0.5V under both static eccentricity fault and stator inter-turn short circuit fault, then it is determined that there is a static eccentricity fault or a stator inter-turn short circuit fault.

[0057] S3: Given a negative d-axis current of the permanent magnet synchronous motor, obtain the fault index under this operating condition, and subtract it from the fault index described in step S2 to obtain the fault index difference value; including the following sub-steps:

[0058] S31: Given the negative d-axis current of the permanent magnet synchronous motor;

[0059] Specifically, according to the process Figure 1 Given a d-axis current of -4A, the motor operates under the condition of a -4A d-axis current. Since both static eccentricity faults and stator inter-turn short-circuit faults generate fundamental frequency components in the zero-sequence voltage signal, they cannot be distinguished. The negative d-axis current proposed in this application provides the conditions for subsequent calculation of fault index differences to distinguish between the above two types of faults.

[0060] S32: Repeat steps S21 and S22 to obtain the fault index under the given negative d-axis current condition.

[0061] Specifically, the fault index Ind' under static eccentricity fault is 1.82V, and the fault index Ind' under stator inter-turn short circuit fault is 0.71V.

[0062] S33: Subtract the fault index described in S32 from the fault index described in S22 to obtain the fault index difference value.

[0063] Specifically, under static eccentricity fault conditions, the fault index difference Δ = Ind' - Ind = 1.82V - 1.36V = 0.46V; under stator inter-turn short-circuit fault conditions, the fault index difference Δ = Ind' - Ind = 0.71V - 0.86V = -1.5V. Under a given negative d-axis current condition, the fault index for static eccentricity fault increases due to changes in core saturation, so the fault index difference is greater than 0. However, the fault index for stator inter-turn short-circuit fault decreases due to a decrease in short-circuit current, so the fault index difference is less than 0.

[0064] S4: Based on the fault index difference, if the value is greater than 0, it is diagnosed as a static eccentricity fault; if the value is less than 0, it is diagnosed as a stator inter-turn short circuit fault. This includes the following sub-steps:

[0065] Specifically, for a static eccentricity fault with a fault index difference Δ > 0, according to Figure 1The fault diagnosis flowchart shown indicates a static eccentricity fault. For stator inter-turn short circuit faults, the fault index difference Δ < 0 indicates a stator inter-turn short circuit fault. Effective differentiation can be achieved based on the difference in fault indices between static eccentricity faults and stator inter-turn short circuit faults under negative d-axis current conditions.

[0066] As can be seen from the above embodiments, this application connects a zero-sequence symmetrical resistor network to the input terminals of the three-phase stator windings of a permanent magnet synchronous motor. The voltage difference between the neutral point of the three-phase windings and the neutral point of the zero-sequence resistor network is measured to obtain a zero-sequence voltage signal. Based on the zero-sequence voltage signal, a Fast Fourier Transform (FFT) is used to extract the fundamental frequency amplitude as a fault indicator, which is then compared with a set threshold to determine whether a static eccentricity fault or a stator inter-turn short-circuit fault exists. If the value is greater than the threshold, a negative d-axis current is applied to the permanent magnet synchronous motor to obtain the fault indicator under this condition. The difference between the fault indicator and the values ​​obtained in the aforementioned steps is calculated to obtain the fault indicator difference value. If the fault indicator difference value is greater than 0, a static eccentricity fault is diagnosed; if the fault indicator difference value is less than 0, a stator inter-turn short-circuit fault is diagnosed. The fault diagnosis method proposed in this application overcomes the technical problem that static eccentricity faults and stator inter-turn short-circuit faults have the same fault characteristics and are difficult to distinguish, thus achieving the technical effect of accurately diagnosing and distinguishing the two types of faults. It also has advantages such as being non-invasive, easy to implement, and capable of online diagnosis.

[0067] Corresponding to the aforementioned embodiments of the permanent magnet synchronous motor fault diagnosis method based on zero-sequence voltage signal, this application also provides embodiments of a permanent magnet synchronous motor fault diagnosis device based on zero-sequence voltage signal.

[0068] Figure 7 This is a block diagram illustrating a fault diagnosis device for a permanent magnet synchronous motor based on a zero-sequence voltage signal, according to an exemplary embodiment. (Refer to...) Figure 7 The device includes:

[0069] Zero-sequence voltage sampling module 1 is used to connect a zero-sequence symmetrical resistor network to the input terminal of the three-phase stator winding of a permanent magnet synchronous motor, and measure the voltage difference between the neutral point of the three-phase winding and the neutral point of the zero-sequence resistor network to obtain the zero-sequence voltage signal.

[0070] Judgment module 2 is used to extract the fundamental frequency amplitude as a fault indicator based on the zero-sequence voltage signal using fast Fourier decomposition, and compare it with a set threshold to determine whether there is a static eccentricity fault or a stator inter-turn short circuit fault. If it is greater than the threshold, the difference module is executed.

[0071] The difference module 3 is used to obtain the fault index under this working condition by giving a negative d-axis current of the permanent magnet synchronous motor, and to subtract it from the fault index in the judgment module to obtain the fault index difference value.

[0072] The diagnostic module 4 is used to diagnose a static eccentricity fault based on the difference in the fault indicators. If the value is greater than 0, it is diagnosed as a stator inter-turn short circuit fault.

[0073] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0074] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0075] Accordingly, this application also provides an electronic device, including: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the above-described method for fault diagnosis of permanent magnet synchronous motors based on zero-sequence voltage signals.

[0076] Accordingly, this application also provides a computer-readable storage medium storing computer instructions thereon, which, when executed by a processor, implement the fault diagnosis method for permanent magnet synchronous motors based on zero-sequence voltage signals as described above.

[0077] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this application are indicated by the claims.

[0078] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A fault diagnosis method for permanent magnet synchronous motors based on zero-sequence voltage signals, characterized in that, include: S1: Connect a zero-sequence symmetrical resistor network to the input terminals of the three-phase stator windings of the permanent magnet synchronous motor, and measure the voltage difference between the neutral point of the three-phase windings and the neutral point of the zero-sequence resistor network to obtain the zero-sequence voltage signal. S2: Based on the zero-sequence voltage signal, use fast Fourier decomposition to extract the fundamental frequency amplitude as a fault indicator, and compare it with a set threshold to determine whether there is a static eccentricity fault or a stator inter-turn short circuit fault. If it is greater than the threshold, then execute S3. S3: Given a negative d-axis current of the permanent magnet synchronous motor, obtain the fault index under this operating condition, and subtract it from the fault index in S2 to obtain the fault index difference value. S4: Based on the difference in the fault indicators, if the value is greater than 0, it is diagnosed as a static eccentricity fault; if the value is less than 0, it is diagnosed as a stator inter-turn short circuit fault.

2. The method according to claim 1, characterized in that, A zero-sequence symmetrical resistor network is connected to the input terminals of the three-phase stator windings of a permanent magnet synchronous motor. The zero-sequence voltage signal is obtained by measuring the voltage difference between the neutral point of the three-phase windings and the neutral point of the zero-sequence resistor network, including the following sub-steps: S11: Select the three resistors used in the zero-sequence symmetric resistor network; S12: Connect one end of each of the three resistors directly to form the neutral point of the zero-sequence resistor network, and connect the other end to the input terminal of the three-phase stator winding of the permanent magnet synchronous motor. S13: Connect the positive and negative terminals of the voltage sensor to the neutral point of the three-phase winding of the permanent magnet synchronous motor and the neutral point of the zero-sequence resistor network, respectively, and sample to obtain the zero-sequence voltage signal.

3. The method according to claim 1, characterized in that, Based on the zero-sequence voltage signal, the fundamental frequency amplitude is extracted using Fast Fourier Decomposition as a fault indicator and compared with a set threshold to determine whether a static eccentricity fault or a stator inter-turn short-circuit fault exists. This includes the following sub-steps: S21: Based on the rotor position signal from the permanent magnet synchronous motor position sensor, select the zero-sequence voltage signal of a complete mechanical cycle and perform fast Fourier decomposition to obtain the amplitude of each frequency harmonic. S22: Determine the fundamental frequency based on the speed signal and the number of motor pole pairs, and extract the fundamental frequency amplitude from the amplitude of each frequency harmonic as a fault indicator; S23: Compare the fault index with a set threshold. If it is less than the set threshold, it is determined that there is no static eccentricity fault or stator inter-turn short circuit fault. If it is greater than the set threshold, it is determined that there is a static eccentricity fault or stator inter-turn short circuit fault.

4. The method according to claim 3, characterized in that, Given a negative d-axis current of the permanent magnet synchronous motor, obtain the fault index under this operating condition, and subtract it from the fault index in S2 to obtain the fault index difference value. This includes the following sub-steps: S31: Given the negative d-axis current of the permanent magnet synchronous motor; S32: Repeat steps S21 and S22 to obtain the fault indicators under the given negative d-axis current condition; S33: Subtract the fault index described in S32 from the fault index described in S22 to obtain the fault index difference value.

5. A fault diagnosis device for permanent magnet synchronous motors based on zero-sequence voltage signals, characterized in that, include: The zero-sequence voltage sampling module is used to connect a zero-sequence symmetrical resistor network to the input terminals of the three-phase stator windings of a permanent magnet synchronous motor, and measure the voltage difference between the neutral point of the three-phase windings and the neutral point of the zero-sequence resistor network to obtain the zero-sequence voltage signal. The judgment module is used to extract the fundamental frequency amplitude as a fault indicator based on the zero-sequence voltage signal using fast Fourier decomposition, and compare it with a set threshold to determine whether there is a static eccentricity fault or a stator inter-turn short circuit fault. If it is greater than the threshold, the difference module is executed. The difference module is used to obtain the fault index under the given negative d-axis current of the permanent magnet synchronous motor, and to calculate the difference between the fault index in the judgment module to obtain the fault index difference value. The diagnostic module is used to diagnose a static eccentricity fault based on the difference in the fault indicators. If the value is greater than 0, the fault is diagnosed as a stator inter-turn short circuit fault.

6. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-4.

7. A computer-readable storage medium storing computer instructions thereon, characterized in that, When executed by the processor, this instruction implements the steps of the method as described in any one of claims 1-4.

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