Adaptive diagnosis method for inter-turn short circuit fault of double three-phase permanent magnet synchronous motor

Abstract

This invention relates to an adaptive diagnostic method for inter-turn short-circuit faults in a dual-phase three-phase permanent magnet synchronous motor, belonging to the field of motor fault diagnosis technology. By establishing a mathematical model and an adjustable model for inter-turn short-circuit faults in the dual-phase three-phase motor, and combining multi-phase motor space vector decoupling transformation, a short-circuit fault component is introduced into the harmonic subplane of the stator voltage equation. Fault characteristic values ​​are designed using the x-y current residual between the actual motor and the adjustable model. The fundamental amplitude is extracted as a fault severity feature through orthogonal Fourier transform. An observer based on the mapping relationship between the short-circuit current residual and the fault turns ratio is constructed. A model reference adaptive law for the piecewise PI regulator is used to dynamically adjust the PI parameters according to speed and load conditions, achieving adaptive feedback estimation of the short-circuit turns ratio. This improves the accuracy and real-time performance of fault feature extraction, simplifies the fault-tolerant algorithm and optimizes the disturbance observer parameter design, solves the diagnostic distortion problem caused by changes in operating conditions, and provides an optimized solution for motor monitoring.

Description

Technical Field

[0001] This invention belongs to the field of motor fault diagnosis technology, and relates to an adaptive diagnosis method for inter-turn short circuit faults in a dual three-phase permanent magnet synchronous motor. Background Technology

[0002] Dual three-phase permanent magnet synchronous motors are widely used in high-reliability applications due to their high efficiency, high power density, and strong fault tolerance. However, various faults are inevitable during motor operation, with inter-turn short-circuit faults being the most common type. Inter-turn short-circuit faults introduce a short-circuit loop, causing changes in the motor parameter matrix. The mathematical model of the motor during normal operation will introduce an additional short-circuit component, and the short-circuit current will also induce electromagnetic torque pulsation, resulting in a decrease in motor output efficiency. Therefore, real-time online diagnosis of the severity of inter-turn short-circuit faults is essential for dual three-phase motors.

[0003] Traditional inter-turn short-circuit fault diagnosis methods are susceptible to fluctuations in detection accuracy due to factors such as fault saliency and feature extraction frequency, making it difficult to maintain stable diagnostic accuracy. To address this issue, a novel diagnostic strategy is needed that ensures diagnostic accuracy remains unchanged regardless of operating conditions.

[0004] Several invention patents have been issued to address the issue of fluctuating diagnostic accuracy for inter-turn short-circuit faults in dual-phase three-phase permanent magnet synchronous motors (PMSMs) as the motor's operating conditions change. For example, patent CN118858934A discloses a method for diagnosing inter-turn short-circuit faults in PMSMs. This method establishes a mathematical model of the inter-turn short-circuit fault in a rotating coordinate system and analyzes the fault characteristics by comparing it with a normal motor model. However, when extracting fault characteristics and performing coordinate transformation and filtering, this method still needs to incorporate more advanced signal processing algorithms to improve the sensitivity and timeliness of fault diagnosis. Patent CN118826586A discloses a method for diagnosing and fault-tolerant control of inter-turn short-circuit faults in five-phase PMSMs. This method extracts fault characteristic information through a preset disturbance observer model and implements precise fault-tolerant control based on this information. However, regarding the fault characteristic information extraction method, this method still requires further research and improvement of the parameter design and stability analysis methods of the disturbance observer model to enhance the extraction accuracy and real-time performance of fault characteristic information.

[0005] The existing technology has the following drawbacks:

[0006] 1. Traditional inter-turn short circuit fault diagnosis methods are affected by factors such as fault salience and feature extraction frequency when estimating the fault severity. The detection accuracy is prone to fluctuation with changes in motor operating conditions, making it difficult to maintain stable diagnostic accuracy.

[0007] 2. Existing fault feature extraction methods have the problem of introducing more advanced signal processing algorithms to improve the sensitivity and timeliness of fault diagnosis.

[0008] 3. Existing disturbance observer models require further research and improvement in parameter design and stability analysis, which affects the accuracy and real-time performance of fault feature information extraction.

[0009] 4. Existing technologies lack adaptive observers for the short-circuit turns ratio of motors, making it impossible to extract the fundamental characteristic parameters of the short-circuit current online, and making it difficult to achieve closed-loop tracking estimation of the fault degree.

[0010] 5. Existing technologies lack model reference adaptive laws based on piecewise PI controllers, making it impossible to achieve adaptive feedback adjustment of the parameters to be estimated and ensuring that diagnostic accuracy is not affected by changes in motor operating conditions. Summary of the Invention

[0011] Existing technologies suffer from the problem that diagnostic accuracy fluctuates with changes in motor operating conditions, making it difficult to maintain stable diagnostic accuracy. Therefore, to address this issue, this invention provides an adaptive diagnostic method for inter-turn short-circuit faults in dual three-phase permanent magnet synchronous motors.

[0012] To achieve the above objectives, the present invention provides the following technical solution:

[0013] An adaptive diagnostic method for inter-turn short-circuit faults in a dual three-phase permanent magnet synchronous motor, characterized by comprising the following steps:

[0014] Step 1: Establish a mathematical model and an adjustable model for the inter-turn short-circuit fault condition of a dual-phase three-phase motor, and establish a fault model for the dual-phase three-phase motor according to the spatial vector decoupling transformation of the multi-phase motor.

[0015] Step 2: Introduce short-circuit fault components into the dq and xy harmonic subplanes of the stator voltage equation; and design characteristic values ​​that reflect the degree of short-turn faults by utilizing the xy current difference components between the real motor and the adjustable model.

[0016] Step 3: Establish an observer from the short-circuit current residual component to the fault turns ratio to design a feedback control law;

[0017] Step 4: Establish a model reference adaptive law based on a piecewise proportional-integral (PI) regulator to adaptively adjust the parameters to be estimated.

[0018] Furthermore, the A-phase fault in the dual three-phase motor fault model described in step 1 is represented by the following formula:

[0019]

[0020] Among them, u d For direct-axis voltage; u q The quadrature-axis voltage; u x u y For harmonic voltage; R s For stator resistance; i d For direct-axis current; i q For quadrature-axis current; i x i y For harmonic current; i F θ is the short-circuit current; θ is the synchronous electrical angle; ω is the synchronous angular velocity L. d It is a direct-axis inductor; L q For quadrature axis inductance; L z For stator leakage inductance; ψ f σ represents the permanent magnet flux linkage; σ represents the short-circuit fault turns ratio.

[0021] Furthermore, in the fault model of the dual three-phase motor, the u in phase A fault... x and u y Harmonic voltage is expressed by the following formula:

[0022]

[0023] In this context, the symbol "" represents the motor parameters of the adjustable model. The current estimated by the adjustable model;

[0024] The differential signal is represented by the following formula:

[0025]

[0026] Where, Δi x The x-axis current residual; Δi y The y-axis current residual is represented by d, where d is the differential sign.

[0027] The mapping relationship between the differential signal and the short-circuit turns ratio σ is obtained from formulas (1) to (3), and is expressed as follows:

[0028]

[0029] Furthermore, step 2 specifically includes:

[0030] Calculate the xy current difference components between the real motor and the adjustable model;

[0031] The feature extraction function of the fault current is simplified, and the primary component of the fault current is used as the object to design the feature value of the fault degree.

[0032] Based on the relevant conclusions of orthogonal Fourier transform, the amplitude information of the fundamental component in the xy current difference component is extracted as a feature value characterizing the degree of fault.

[0033] Furthermore, step 2 also includes:

[0034] Extract i according to the following relationship x Amplitude information of the fundamental component in the current residual:

[0035]

[0036] In the formula, A1 and A2 are the characteristic parameters of the orthogonal Fourier transform, and FI is the fault characteristic value;

[0037] in,

[0038]

[0039] In the formula, x1 is the subscript of the fundamental component, and k = 1, 2, 3, ...;

[0040] The FI response model references the adaptive system adjustment model to account for the input deviation of fault harmonic current between the actual motor and the model.

[0041] Furthermore, step 3 specifically includes:

[0042] By applying a certain load torque TL to the tractor motor, after the motor runs to a stable speed, a short-circuit fault with a given turns ratio is introduced into phase A.

[0043] The residual between the x and y axis current signals of the real motor and the x and y axis current signals of the adjustable model is used to generate fault feature values ​​FI, which are then used as the adaptive law input of the observer.

[0044] Furthermore, step 4 specifically includes:

[0045] Collect motor speed and load information to determine in real time which segment range the current operating condition is in;

[0046] Select the appropriate PI control parameters to adjust the short-circuit turns ratio estimate.

[0047] Furthermore, the segmented PI controller in step 4 mainly includes:

[0048] Input: Current residual signal in the xy subspace between the adjustable model and the real motor;

[0049] At the output end, the estimated value of the short-circuit turns ratio;

[0050] The control law section consists of a segmented PI controller;

[0051] The control law section collects the motor speed and load signals, determines the segmented range of the current operating condition in real time, and selects the corresponding PI control parameters to adjust the short-turn ratio estimate.

[0052] Furthermore, the segmented PI controller divides the operating range within the boundary into grids and uses linear interpolation to determine the controller parameters for operating points in other grids, so as to maintain fault tracking under different operating conditions.

[0053] Compared with the prior art, the present invention provides an adaptive diagnosis method for inter-turn short-circuit faults in dual three-phase permanent magnet synchronous motors, which has the following beneficial effects:

[0054] 1. Improved diagnostic accuracy and reduced diagnostic error. This invention utilizes the current difference component between the real motor and the adjustable model to design a characteristic value that can reflect the degree of short-turn faults, and achieves adaptive feedback adjustment of the parameters to be estimated based on the model reference adaptive law of the segmented PI controller. Within the operating range of ±40% speed / load of the rated operating point of the controlled object, the diagnostic error of the fault degree is reduced by about 20 percentage points, solving the problem of diagnostic accuracy distortion caused by changes in motor operating conditions in the prior art;

[0055] 2. Improved the accuracy and real-time performance of fault feature information extraction. This invention simplifies the feature extraction function of fault current, selecting the primary component mainly contained in the fault current as the object to design feature values ​​characterizing the fault degree, thereby improving the accuracy and real-time performance of fault feature information extraction;

[0056] 3. The fault characteristic parameters of the mathematical model for inter-turn short-circuit faults in motors are enriched. This invention establishes a mathematical model and an adjustable model under inter-turn short-circuit fault conditions for dual-phase and three-phase motors. The fault model for dual-phase and three-phase motors is derived based on the spatial vector decoupling transformation of multi-phase motors, which enriches the fault characteristic parameters and improves the accuracy of fault diagnosis.

[0057] 4. Reduced complexity of fault-tolerant algorithms. This invention achieves adaptive feedback adjustment of the estimated parameters based on the model reference adaptive law of a piecewise proportional-integral (PI) regulator, without needing to diagnose the specific values ​​of the fault parameters, thus reducing the complexity of fault-tolerant algorithms;

[0058] 5. Improved parameter design and stability analysis of the disturbance observer model. This invention establishes a two-phase three-phase motor inter-turn short-circuit fault model based on real motor data using a finite element model, providing a theoretical basis for parameter design and stability analysis of the disturbance observer model.

[0059] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0060] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein:

[0061] Figure 1 This is a schematic diagram illustrating how the fault characteristic value FI changes with the degree of fault according to a specific embodiment of the present invention;

[0062] Figure 2 This is a schematic diagram illustrating the fault degree diagnosis of a specific embodiment of the present invention;

[0063] Figure 3 This is a schematic diagram of a model structure based on a piecewise PI controller according to a specific embodiment of the present invention;

[0064] Figure 4 This is a schematic diagram of the fault phase current waveform under a single-phase short-circuit fault condition according to a specific embodiment of the present invention;

[0065] Figure 5 This is a schematic diagram of the short-circuit current waveform under a single-phase short-circuit fault condition according to a specific embodiment of the present invention;

[0066] Figure 6 This is a schematic diagram of the fault harmonic plane current waveform under a single-phase short-circuit fault condition according to a specific embodiment of the present invention.

[0067] Figure 7 This is a schematic diagram of the fault electromagnetic torque under a single-phase short-circuit fault condition according to a specific embodiment of the present invention.

[0068] Figure 8 This is a schematic diagram illustrating the diagnostic accuracy of traditional diagnostic methods as the operating conditions of a motor with minor faults change.

[0069] Figure 9 This is a schematic diagram illustrating the diagnostic accuracy of traditional diagnostic methods as the operating conditions of a motor undergo severe faults.

[0070] Figure 10 This is a schematic diagram illustrating the diagnostic accuracy of a specific embodiment of the present invention as the operating conditions of a motor with minor faults change.

[0071] Figure 11 This is a schematic diagram illustrating the diagnostic accuracy of a specific embodiment of the present invention as the operating conditions of a motor undergo severe fault changes. Detailed Implementation

[0072] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0073] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0074] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0075] This invention proposes an adaptive diagnostic method for inter-turn short-circuit faults in a dual three-phase permanent magnet synchronous motor. By establishing an adaptive observer for the short-circuit turns ratio of the motor, the fundamental characteristic parameters of the short-circuit current can be extracted online, achieving closed-loop tracking estimation of the fault severity, thus ensuring that the diagnostic accuracy is unaffected by changes in motor operating conditions. The method mainly includes the following steps:

[0076] Step 1: To estimate the severity of inter-turn short-circuit faults in the motor, a mathematical model and an adjustable model under inter-turn short-circuit fault conditions for the dual three-phase motor must first be established. The fault model for the dual three-phase motor is derived based on the Vector Space Decomposition (VSD) transformation of the multi-phase motor. The A-phase fault is represented by the following formula:

[0077]

[0078] Among them, u d For direct-axis voltage; u q The quadrature-axis voltage; u xu y For harmonic voltage; R s For stator resistance; i d For direct-axis current; i q For quadrature-axis current; i x i y For harmonic current; i F θ is the short-circuit current; θ is the synchronous electrical angle; ω is the synchronous angular velocity L. d It is a direct-axis inductor; L q For quadrature axis inductance; L z For stator leakage inductance; ψ f σ represents the permanent magnet flux linkage; σ represents the short-circuit fault turns ratio.

[0079] Step 2: According to formula (1), the inter-turn short-circuit fault introduces short-circuit fault components in both the dq and xy harmonic subplanes of the stator voltage equation. Therefore, by utilizing the xy current difference component between the actual motor and the adjustable model, characteristic values ​​that can reflect the degree of inter-turn short-circuit faults can be designed.

[0080] The superscript symbol "" represents the motor parameters of the adjustable model. The current is estimated by the adjustable model; by rewriting the last two terms in the above formula (1), we can obtain the following formula:

[0081]

[0082] The differential signal can then be expressed by the following formula:

[0083]

[0084] Where, Δi x The x-axis current residual; Δi y The y-axis current residual is represented by d, where d is the differential sign.

[0085] Substituting equations (2)-(3) into equation (1), the mapping relationship between the differential signal and the short-circuit turns ratio σ can be expressed as the following formula:

[0086]

[0087] When the fault resistance remains constant, the effective value of the short-circuit current monotonically increases with the change in the fault turns ratio under any operating condition of the motor. Therefore, the fault turns ratio of the adjustable model will converge synchronously with the short-circuit current, that is: This is the short-circuit turns ratio estimated for the adjustable model of the motor.

[0088] Step 3: By designing a suitable feedback control law, an observer can be established to measure the short-circuit current residual component to the fault turns ratio, i.e., when Δi x →0, Δi y →0,

[0089] Considering the complexity of the analytical expression for short-circuit current, the feature extraction function for fault current can be simplified to some extent. Short-circuit current mainly includes odd harmonic components such as the first, third, fifth, and seventh harmonics of the motor. The third harmonic component is primarily caused by stator core saturation, while the fifth and seventh harmonic components are mainly affected by inverter nonlinearity. The fundamental component is the most significant component of the short-circuit current, and its variation with the severity of inter-turn short-circuit faults is most pronounced. Therefore, the first component, which is the main component of the fault current, can be selected as the object for designing feature values ​​characterizing the fault severity.

[0090] Based on the relevant conclusions of orthogonal Fourier transform, i can be extracted according to the following relationship. x Amplitude information of the fundamental component in the current residual:

[0091]

[0092] In the formula, A1 and A2 are the characteristic parameters of the orthogonal Fourier transform; FI is the fault characteristic value.

[0093] in,

[0094]

[0095] In the formula, x1 is the subscript of the fundamental component; k = 1, 2, 3, ...

[0096] Using FI as a fault characteristic value can reflect the input deviation of fault harmonic current between the model reference adaptive system adjustment model and the real motor.

[0097] Please see Figure 1 This is a schematic diagram illustrating how the fault characteristic value FI changes with the degree of fault in a specific embodiment of the present invention. Figure 1 This paper illustrates the variation of the fault characteristic value FI with fault severity under different short-circuit turns ratios. In this figure, a short-circuit fault with σ = 0.3 is introduced into the motor's A-phase winding at t = 0.2s, a short-circuit fault with σ = 0.5 is introduced at t = 0.4s, and the fault is reset at t = 0.6s. The results show that FI can proportionally reflect the current short-circuit turns ratio and exhibits good responsiveness to changes in fault severity.

[0098] Please see Figure 2 This is a schematic diagram of fault degree diagnosis according to a specific embodiment of the present invention; Figure 2 The control block diagram based on model reference adaptive diagnostic method is shown. Current closed-loop control is used to keep the d-axis current and xy-axis current near the zero value before the fault.

[0099] By applying a certain load torque TL to the motor, a short-circuit fault with a given turns ratio is introduced into phase A after the motor has reached a stable speed. Then, the residual between the x and y axis current signals of the actual motor and the x and y axis current signals of the adjustable model is used to generate the fault characteristic value FI, which serves as the adaptive law input for the observer.

[0100] Step 4: To achieve closed-loop tracking estimation of short-circuit fault severity, this invention, based on fault feature extraction, also designs a model reference adaptive law based on a piecewise PI controller to achieve adaptive feedback adjustment of the parameter to be estimated. Please refer to [link to relevant documentation]. Figure 3 This is a schematic diagram of a model structure based on a segmented PI controller according to a specific embodiment of the present invention; Figure 3 The regulator structure is shown, mainly consisting of three parts: the input is the current residual signal in the xy subspace between the adjustable model and the real motor; the output is the estimated short-circuit turns ratio; and the control law is composed of a piecewise PI regulator. During regulation, the control law collects the motor speed and load signals, determines in real time which segment the current operating condition is in, and selects the corresponding PI control parameters (KP_1, KI_1, ...) to adjust the short-circuit turns ratio estimate. The regulator selects the maximum operating range of the motor (rated operating point: speed 1200 rpm, load torque 10 Nm, with the actual measurement range defined by the maximum deviation of speed and torque ±40%) as a reference. The boundary operating conditions correspond to four operating points: p1: 800 rpm, 6 Nm / p2: 800 rpm, 14 Nm / p3: 1600 rpm, 6 Nm / p4: 1600 rpm, 14 Nm) as a reference. The PI parameter values ​​under the boundary operating conditions are determined based on maintaining specific tracking performance. At the same time, the operating range within the boundary is gridded, and the regulator parameters for operating points in other grids are determined using linear interpolation to maintain the relative stability of fault tracking performance under different operating conditions.

[0101] This invention establishes a finite element model of an inter-turn short-circuit fault in a dual-phase three-phase motor based on real motor data, and performs fault simulation under single-phase short-circuit fault conditions. Please refer to [link / reference]. Figure 4 This is a schematic diagram of the fault phase current waveform under a single-phase short-circuit fault condition according to a specific embodiment of the present invention; please refer to [link / reference]. Figure 5 This is a schematic diagram of the short-circuit current waveform under a single-phase short-circuit fault condition according to a specific embodiment of the present invention; please refer to [link / reference]. Figure 6 This is a schematic diagram of the fault harmonic plane current waveform under a single-phase short-circuit fault condition according to a specific embodiment of the present invention; please refer to... Figure 7 This is a schematic diagram of the fault electromagnetic torque under a single-phase short-circuit fault condition according to a specific embodiment of the present invention. Figures 4 to 7The simulation results show that when an inter-turn short-circuit fault occurs in phase a winding, the corresponding phase current increases rapidly. Under a fault severity with a short-circuit turns ratio σ = 0.2, the peak current of phase a increases by approximately 22% compared to normal operation, consistent with the variation of short-circuit current with increasing fault severity. Simultaneously, harmonic components are generated in the d-axis, q-axis, and x-axis currents after the phase a fault occurs. This is consistent with the conclusion that short-circuit current introduces additional components into the dq and xy subspaces of a dual three-phase motor. The model used in this invention effectively reproduces the motor operating state under inter-turn short-circuit fault conditions.

[0102] An adaptive diagnostic method for inter-turn short-circuit faults in a dual three-phase permanent magnet synchronous motor was compared with a traditional estimation method (i.e., a method that does not use the control law for feedback adjustment, but only uses the open-loop diagnostic estimation based on the residual current signal between the healthy motor model and the actual motor). The results showed how the diagnostic accuracy of the fault severity changes with speed / load conditions under two sets of conditions: minor and severe inter-turn short-circuit faults. Please refer to [link / reference]. Figure 8 This is a schematic diagram illustrating the diagnostic accuracy of traditional diagnostic methods as the operating conditions of a motor with minor faults change; please refer to [link / reference]. Figure 9 This is a schematic diagram illustrating the diagnostic accuracy of traditional diagnostic methods as the operating conditions of a motor undergo severe faults; please refer to [link / reference]. Figure 10 This is a schematic diagram illustrating the diagnostic accuracy of a specific embodiment of the present invention as the operating conditions of a motor with minor faults change; please refer to [link / reference]. Figure 11 This is a schematic diagram illustrating the diagnostic accuracy of a specific embodiment of the present invention as the operating conditions of a motor undergo severe faults. Figures 8 to 11 The comparison shown illustrates how the estimation accuracy of the two diagnostic methods varies with operating conditions within a range of ±40% of the motor's rated operating point in terms of speed and load torque. The results indicate that the traditional diagnostic method only achieves high accuracy near the motor's rated operating point. Under minor fault conditions, accuracy distortion occurs with changes in motor speed; under severe fault conditions, accuracy distortion occurs with both motor speed and load deviation from the rated operating point. For example, in... Figure 8 In the case of positive deviation at maximum rotational speed, the diagnostic accuracy of the traditional method exhibits a distortion of 0.2. Figure 9 Traditional methods achieve a distortion of 0.36 under maximum speed and torque positive deviation. In contrast, the diagnostic distortion of the closed-loop diagnostic system remains within 0.1 under both minor and major fault conditions, exhibiting steady-state tracking accuracy unaffected by motor operating conditions. This reduces the diagnostic error by approximately 20% compared to traditional diagnostic methods.

[0103] Fault characteristics based on the xy subplane current residual signal exhibit good responsiveness in reflecting the degree of inter-turn short-circuit faults, and the adaptive feedback regulator can achieve accurate tracking of the degree of inter-turn short-circuit faults. Experimental results show that, within the operating range of ±40% speed / load of the controlled object's rated operating point, the proposed diagnostic method reduces the fault degree diagnosis error by approximately 20 percentage points compared to the traditional open-loop diagnostic method.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. An adaptive diagnostic method for inter-turn short-circuit faults in a dual three-phase permanent magnet synchronous motor, characterized in that, Includes the following steps: Step 1: Establish a mathematical model and an adjustable model for the inter-turn short-circuit fault condition of a dual-phase three-phase motor, and establish a fault model for the dual-phase three-phase motor according to the spatial vector decoupling transformation of the multi-phase motor. Step 2, in the stator voltage equation dq, xy The harmonic subplane introduces short-circuit fault components; utilizing the relationship between the real motor and the adjustable model... xy The current difference component is designed as a characteristic value that reflects the degree of inter-turn short-circuit fault. Step 3: Establish an observer from the short-circuit current residual component to the fault turns ratio to design a feedback control law; Step 4: Establish a model reference adaptive law based on a piecewise PI controller to adaptively adjust the parameter to be estimated; The A-phase fault in the dual three-phase motor fault model described in step 1 is represented by the following formula: (1) in, u d It is the direct-axis voltage; u q It is the quadrature axis voltage; u x , u y Harmonic voltage; R s Stator resistance; i d It is the direct-axis current; i q It is the quadrature-axis current; i x , i y Harmonic current; i F This is the short-circuit current; For synchronous electrical angle; ω For synchronous angular velocity, L d It is a direct-axis inductor; L q It is a quadrature axis inductor; L z For stator leakage inductance; It is a permanent magnet flux linkage; σ This refers to the number of turns in a short-circuit fault. The fault model of the dual three-phase motor in phase A fault u x and u y Harmonic voltage is expressed by the following formula: (2) In this context, the symbol "~" represents the motor parameters of the adjustable model; The differential signal is represented by the following formula: (3) in, i x for x Shaft current residual; i y for y Shaft current residual; d The differential symbol; The differential signal to short-circuit turns ratio is obtained from formulas (1) to (3). σ The mapping relationship between them is expressed by the following formula: (4) Step 2 specifically includes: Calculate the xy current difference components between the real motor and the adjustable model; The feature extraction function of the fault current is simplified, and the primary component contained in the fault current is used as the object to design the feature value of the fault degree. Based on the relevant conclusions of orthogonal Fourier transform, the amplitude information of the fundamental component in the xy current difference component is extracted as a feature value characterizing the degree of fault. Step 2 also includes: Extract according to the following relationship i x Amplitude information of the fundamental component in the current residual: (5) In the formula, A 1. A 2 represents the characteristic parameters of the orthogonal Fourier transform. FI These are fault characteristic values; in, In the formula, x 1 is the subscript for the fundamental component. k =1, 2, 3, ...; The fault characteristic value can reflect the input deviation of the fault harmonic current between the model reference adaptive system adjustment model and the real motor.

2. The adaptive diagnosis method for inter-turn short-circuit faults in a dual three-phase permanent magnet synchronous motor according to claim 1, characterized in that: Step 3 specifically includes: By applying a certain load torque to the tractor motor TL After the motor has reached a stable speed, a short-circuit fault with a given turns ratio is introduced into phase A. The residual between the x and y axis current signals of the real motor and the x and y axis current signals of the adjustable model is used to generate fault feature values ​​FI, which are then used as the adaptive law input of the observer.

3. The adaptive diagnosis method for inter-turn short-circuit faults in a dual three-phase permanent magnet synchronous motor according to claim 1, characterized in that: Step 4 specifically includes: Collect motor speed and load information to determine in real time which segment range the current operating condition is in; Select the appropriate PI control parameters to adjust the short-circuit turns ratio estimate.

4. The adaptive diagnosis method for inter-turn short-circuit faults in a dual three-phase permanent magnet synchronous motor according to claim 3, characterized in that: The segmented PI controller in step 4 includes: Input end, adjustable model and real motor xy The current residual signal in the subspace; At the output end, the estimated value of the short-circuit turns ratio; The control law section consists of a segmented PI controller; The control law section collects the motor speed and load signals, determines the segmented range of the current operating condition in real time, and selects the corresponding PI control parameters to adjust the short-turn ratio estimate.

5. The adaptive diagnosis method for inter-turn short-circuit faults in a dual three-phase permanent magnet synchronous motor according to claim 4, characterized in that: The segmented PI controller divides the operating range within the boundary into grids and uses linear interpolation to determine the controller parameters for operating points in other grids, so as to maintain fault tracking under different operating conditions.

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