Permanent magnet motor turn-to-turn short circuit fault diagnosis method considering complex working condition influence

Abstract

The invention discloses a permanent magnet motor turn-to-turn short circuit fault diagnosis method considering complex working condition influence, belongs to the technical field of permanent magnet motor fault diagnosis, and aims to solve the problems that a turn-to-turn short circuit diagnosis result of a permanent magnet synchronous motor for an electric vehicle is easily influenced by working conditions and slight faults are difficult to diagnose under complex operation working conditions. The method comprises the following steps: step 1, high-frequency signal injection and information acquisition; injecting the high-frequency rotating voltage signal into a motor control system under a natural coordinate system, and collecting each phase of high-frequency current and each phase of high-frequency voltage of the motor through a band-pass filter; 2, subtracting the high-frequency voltage from the healthy voltage under the condition that the high-frequency signal is injected, and calculating to obtain a high-frequency voltage residual error of each phase; 3, according to the high-frequency voltage residual error of each phase, obtaining two fault characteristic quantities, namely the standard deviation of the high-frequency voltage residual error and the absolute average value of the high-frequency voltage residual error of each phase; and 4, judging whether a turn-to-turn short circuit fault occurs or not according to the fault characteristic quantity, and judging a fault phase.

Description

Technical Field

[0001] The invention relates to a permanent magnet motor turn-to-turn short circuit fault diagnosis method taking into account the influence of complex working conditions, and belongs to the technical field of permanent magnet motor fault diagnosis. Background Art

[0002] Permanent magnet synchronous motors (PMSMs), with their high efficiency, high power density, and dynamic response, have become the core power unit of electric vehicle drive systems. Under complex operating conditions such as frequent vehicle starts and stops and wide-range speed regulation, the motor's stator windings are constantly subjected to mechanical vibration, temperature fluctuations, and other shocks. Faults such as open windings and interturn shorts are unavoidable. These faults can cause current imbalances, localized overheating, and other issues, threatening system stability. Therefore, researching fault diagnosis strategies that consider the dynamic characteristics of complex operating conditions is crucial for improving the operational safety of electric vehicles.

[0003] Turn-to-turn short-circuit faults arise from localized failure of the insulation of the winding conductors. Essentially, they form a low-impedance path between adjacent conductors due to insulation aging, mechanical stress, or electrothermal degradation. When a turn-to-turn short-circuit fault occurs, the symmetry of the stator winding is disrupted, and the magnetic circuits corresponding to the healthy and faulty parts of the winding interact with each other, resulting in an uneven magnetic field distribution. This can cause neutral point voltage offset, reduced fault phase voltage, and increased electromagnetic torque harmonic content, leading to increased torque fluctuations and reduced system efficiency. It is important to note that the subtle characteristics of minor faults make them difficult to detect. Failure to detect them in a timely manner can easily lead to irreversible damage, such as permanent demagnetization of the permanent magnets and accelerated melting of the insulation.

[0004] The diagnostic results of currently proposed turn-to-turn short-circuit diagnostic methods are significantly affected by changes in operating conditions, especially complex operating conditions, making it difficult to establish a unified standard for distinguishing the severity of faults. Since the parameters such as current and voltage required for fault diagnosis are often closely related to the operating conditions, the diagnostic results for motors with the same fault condition may not be the same when operating under different speed and torque conditions, thus affecting the judgment of the severity of the fault. Most diagnostic methods are tested under fixed operating conditions. However, for motor systems operating in complex environments and conditions, it is very important to reduce the impact of operating condition changes on the diagnostic results. At the same time, commonly used methods are not effective in diagnosing minor faults. Since the electrical characteristics of minor faults are weak and easily masked by factors such as electromagnetic noise and load fluctuations, it is difficult to diagnose the fault in its early stages. By the time the fault is detected using commonly used methods, the short circuit inside the motor is often already quite serious, and the optimal maintenance opportunity has been missed. Summary of the Invention

[0005] In order to solve the problem that the turn-to-turn short circuit diagnosis results of permanent magnet synchronous motors for electric vehicles are easily affected by operating conditions under complex operating conditions and minor faults are difficult to diagnose, the present invention provides a permanent magnet motor turn-to-turn short circuit fault diagnosis method that takes the influence of complex operating conditions into consideration.

[0006] The present invention provides a method for diagnosing a permanent magnet motor turn-to-turn short circuit fault taking into account the influence of complex working conditions. The method comprises the following steps:

[0007] Step 1: high-frequency signal injection and information collection step;

[0008] Inject high-frequency rotating voltage signals into the motor control system in the natural coordinate system, where n represents each phase winding of the motor, n = a, b, c...;

[0009] The high-frequency current i of each phase of the motor is collected through a bandpass filter nh and each phase high frequency voltage

[0010] Step 2: High frequency voltage The healthy voltage under the injection of high frequency signal The high-frequency voltage residual of each phase is calculated by subtracting

[0011] Step 3: Calculate the fault characteristic quantity: According to the high-frequency voltage residual of each phase Obtain fault characteristics, which include the standard deviation SD of the high-frequency voltage residual and the absolute average value Z of the high-frequency voltage residual of each phase. n ;

[0012] Step 4: Turn-to-turn short circuit fault diagnosis: Determine whether a turn-to-turn short circuit fault occurs based on the fault characteristic quantity, and determine the fault phase.

[0013] Preferably, the process of step 2 is:

[0014] The high-frequency voltage residual of each phase is obtained by the following formula:

[0015]

[0016] Where, Represents the high-frequency voltage residual matrix, which is composed of the high-frequency voltage residual of each phase The N×1 matrix is formed, where N is the number of motor phases;

[0017] Represents the high-frequency voltage matrix, which is composed of the high-frequency voltage of each phase The N×1 matrix formed;

[0018] Represents the high-frequency healthy voltage matrix, which is the healthy voltage injected by each phase at high frequency The N×1 matrix; high-frequency health voltage matrix Estimate as follows:

[0019]

[0020] In the formula, [I nh ] represents the high-frequency current matrix, and the high-frequency current i of each phase nh The N×1 matrix formed;

[0021] [L s ] represents the inductance matrix of the motor, which is an N×N matrix consisting of self-inductance L and mutual inductance;

[0022] R s Indicates the phase resistance of the stator winding.

[0023] Preferably, the high-frequency voltage residual standard deviation SD in step 3 is calculated as follows:

[0024]

[0025] Where V0 is the average value of the high-frequency voltage residual of each phase,

[0026] Preferably, the absolute average value Z of the high-frequency voltage residual of each phase in step 3 is n Calculate as follows:

[0027]

[0028] Where, T v is the integration period, T v =k×T s , T s is the electrical period, k is the ratio of the integral period to the electrical period, k≤1.

[0029] Preferably, the judgment criteria for the inter-turn short circuit fault in step 4 are:

[0030] SD>SD T Indicates that a turn-to-turn short circuit fault has occurred, otherwise it is healthy, SD T is the fault threshold.

[0031] Preferably, the phase difference between each phase of the injected high-frequency rotating voltage signal is consistent with the phase difference between the motor windings.

[0032] Preferably, the method of the present invention is applicable to realizing fault diagnosis under complex working conditions such as sinusoidal speed change, step-wise torque change and speed-torque coupled change.

[0033] Preferably, the method is suitable for diagnosing a turn-to-turn short circuit fault in a single-phase winding.

[0034] Preferably, it is characterized in that the method is applicable to a structure in which each phase winding of the motor is a coil or a plurality of coils connected in series.

[0035] Beneficial effects of the present invention:

[0036] 1. The method for diagnosing inter-turn short-circuit faults of permanent magnet motors proposed in the present invention, which takes into account the influence of complex working conditions, solves the problem that minor faults are difficult to diagnose. It can complete the diagnosis of multi-level fault scenarios from minor to serious, and realizes the distinction between similar faults, positioning of the fault phase and judgment of the severity of the fault with high sensitivity.

[0037] 2. The method for diagnosing inter-turn short-circuit faults of permanent magnet motors proposed in the present invention, which takes into account the influence of complex working conditions, solves the problem that fault characteristics are easily disturbed by working conditions. Under dynamic working conditions where the speed or torque changes, the diagnostic effect is decoupled from the speed, and the method is less affected by torque changes and has good robustness.

[0038] 3. The method for diagnosing inter-turn short-circuit faults of permanent magnet motors proposed in the present invention takes into account the influence of complex working conditions. In response to the operating requirements of the motor under complex working conditions, the diagnostic results can still maintain high robustness under complex working conditions such as changes in speed and torque coupling, step changes in torque, and sinusoidal changes in speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 is an equivalent circuit model of a six-phase motor with an inter-turn short circuit fault according to an embodiment of the present invention;

[0040] Figure 2 This is a control block diagram of a high-frequency voltage injection system for a motor according to an embodiment of the present invention;

[0041] Figure 3 This is a schematic diagram of the fault diagnosis process of the present invention;

[0042] Figure 4 Schematic diagram of the effect of speed change on diagnostic effect in an embodiment of the present invention, wherein Figure 4 (a) shows two conductor short circuit scenarios, which are minor faults. Figure 4 (b) presents two conductor short circuit scenarios, which are serious faults;

[0043] Figure 5 Schematic diagram of the effect of torque change on diagnostic effect in an embodiment of the present invention, where Figure 5 (a) shows two conductor short circuit scenarios, which are minor faults. Figure 5 (b) presents two conductor short circuit scenarios, which are serious faults;

[0044] Figure 6 Schematic diagram of the effect of speed and torque coupling changes on diagnostic results in an embodiment of the present invention, where Figure 6 (a) shows two conductor short circuit scenarios, which are minor faults. Figure 6 (b) shows two conductor short circuit scenarios that are serious faults

[0045] Figure 7 Schematic diagram of the effect of torque step change on diagnostic effect in an embodiment of the present invention, where Figure 7 (a) is the torque step change curve, Figure 7 (b) is the curve of the change of the fault characteristic quantity standard deviation SD over time for four different fault scenarios. Figure 7 (c) is the effect of four different fault scenarios on Z n The curve of the change of this fault characteristic quantity over time;

[0046] Figure 8 Schematic diagram of the effect of sinusoidal change of speed on diagnostic effect in an embodiment of the present invention, where Figure 8 (a) is the sinusoidal curve of the speed, Figure 8 (b) is the curve of the change of the fault characteristic quantity standard deviation SD over time for four different fault scenarios. Figure 8 (c) is the effect of four different fault scenarios on Z n The curve of the change of this fault characteristic quantity over time. DETAILED DESCRIPTION

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0048] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0049] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but they are not intended to limit the present invention.

[0050] Specific implementation method 1: Figures 1 to 8 This embodiment describes a method for diagnosing a turn-to-turn short-circuit fault in a permanent magnet motor taking into account the influence of complex working conditions. The method includes the following steps:

[0051] Step 1: high-frequency signal injection and information collection step;

[0052] Injecting a high-frequency rotating voltage signal into the motor control system in a natural coordinate system, where n represents each phase winding of the motor, n = a, b, c, ...; the phase difference between each phase of the injected high-frequency rotating voltage signal is consistent with the phase difference between the motor windings;

[0053] The high-frequency current i of each phase of the motor is collected through a bandpass filter nh and each phase high frequency voltage

[0054] Step 2: High frequency voltage The healthy voltage under the injection of high frequency signal The high-frequency voltage residual of each phase is calculated by subtracting

[0055] Step 3: Calculate the fault characteristic quantity: According to the high-frequency voltage residual of each phase Obtain fault characteristics, which include the standard deviation SD of the high-frequency voltage residual and the absolute average value Z of the high-frequency voltage residual of each phase. n ;

[0056] Step 4: Turn-to-turn short circuit fault diagnosis: Determine whether a turn-to-turn short circuit fault has occurred based on the fault characteristic quantity, and determine the fault phase.

[0057] Under certain working conditions, the method of the present invention is applicable to realizing fault diagnosis under complex working conditions such as sinusoidal change of speed, step change of torque and coupled change of speed and torque.

[0058] This method is applicable to the structure where each phase winding of the motor is a coil or multiple coils connected in series. Taking a six-phase permanent magnet synchronous motor as an example, the six phase windings of the motor are symmetrically distributed and connected together at a neutral point to form a Y-type connection structure, such as Figure 1 As shown in FIG. 1 , it is an equivalent circuit model of a turn-to-turn short circuit fault of the motor phase A winding in this embodiment. The inductance of the two coils of phase A is L a1 , L a2 , the phase current is i a , the phase resistance is R a ; The inductance of the two coils of phase B is L b1 , L b2 , the phase current is i b , the phase resistance is R b ; The inductance of the two coils of phase C is L c1 , L c2 , the phase current is i c , the phase resistance is R c ; The inductance of the two coils of phase D is L d1 , L d2 , the phase current is i d , the phase resistance is R d ; The inductance of the two coils of phase E is L e1 , L e2 , the phase current is i e , the phase resistance is R e ; The inductance of the two coils of phase F is L f1 , L f2 , the phase current is i f , the phase resistance is R f ; A phase has a turn-to-turn short circuit, R fis the short-circuit resistance, representing the contact resistance between the short-circuit conductors, i F For the flow through R f of short-circuit current.

[0059] See also Figure 2 As shown in the figure, the high-frequency voltage injection system control block diagram of the motor described in this embodiment is shown. In order to ensure good control effect and easy implementation of the algorithm, the motor is regarded as a system with two sets of three-phase windings, that is, the phases in each set of windings are separated by 120 degrees of electrical angle, where the ABC phases are separated by 120 degrees and the DEF phases are separated by 120 degrees. For the six-motor motor as a whole, the ABCDEF phases are separated by 60 degrees. d = 0. According to the detected six-phase current and the electrical angle θ of the motor, two sets of fundamental currents i in the rotating coordinate system are obtained after coordinate transformation. d1 、i q1 and i d2 、i q2 , respectively with the preset given value I d1_ref , I q1_ref , I d2_ref , I q2_ref Since the two sets of windings are not completely independent, they share a neutral point, which is one less degree of freedom than the traditional dual three-phase system, thus increasing the control of zero-sequence current i o1 Constraints can be used to improve system stability and harmonic suppression capabilities. o1 With the preset given value I o1_ref Compare. d1 、i q1 、i o1 and i d2 、i q2 The two sets of differences after comparison are respectively passed through the PI regulator to obtain the given voltage u in the rotating coordinate system. d1 、u d1 and u d2 、u q2 At the same time, according to the electrical angular velocity ω of the motor, a feedforward voltage compensation is added to the control system to achieve decoupling control between the dq axes. In order to obtain the high-frequency component of the motor under fault conditions, a six-phase high-frequency rotating voltage u with a constant frequency and amplitude and a 60° phase difference is injected into the motor control system. ah 、u bh 、u ch 、u dh 、u eh 、u fh .

[0060] Figure 3 FIG. 1 is a flow chart of a method for diagnosing a permanent magnet motor turn-to-turn short circuit fault according to the present invention, taking into account the influence of complex working conditions. The specific implementation steps are as follows:

[0061] Step 1: high-frequency signal injection and information collection step;

[0062] A high-frequency rotating voltage with a frequency of 1600 Hz, an amplitude of 4 V, and a phase difference of 60° is injected into the motor control system. The current i of each phase injected at high frequency is collected through a second-order bandpass filter. nh and voltage Will With the healthy voltage injected at high frequency The high-frequency voltage residual of each phase is calculated by subtracting

[0063] Step 2: High frequency voltage The healthy voltage under the injection of high frequency signal The high-frequency voltage residual of each phase is calculated by subtracting

[0064] The specific steps are:

[0065] The high-frequency voltage residual of each phase is obtained by the following formula:

[0066]

[0067] Where, Represents the high-frequency voltage residual matrix, which is composed of the high-frequency voltage residual of each phase The N×1 matrix is formed, where N is the number of motor phases; are the high-frequency voltage residuals of the ABCEDF phases respectively;

[0068] Represents the high-frequency voltage matrix, which is composed of the high-frequency voltage of each phase The N×1 matrix formed;

[0069] are the measured high-frequency voltages of the ABCEDF phases;

[0070] Represents the high-frequency healthy voltage matrix, which is the healthy voltage injected by each phase at high frequency The N×1 matrix formed; are the healthy voltages of the ABCEDF phase under high frequency injection;

[0071] Among them, the voltage equation of the healthy motor under high frequency injection is used to estimate the high frequency healthy voltage of each phase by direct calculation. Compared with the healthy motor voltage equation at the fundamental frequency, this equation does not contain the back-EMF term. This is because under high-frequency excitation, the mechanical angular frequency is much lower than the injection frequency, and the back-EMF term is omitted because its frequency is not in the same frequency band as the high-frequency excitation signal.

[0072] The equation for the healthy motor voltage at high frequency injection is:

[0073]

[0074] In the formula, [I nh ] represents the high-frequency current matrix, and the high-frequency current i of each phase nh The N×1 matrix formed;

[0075] [I nh ]=[i ah i bh i ch i dh i eh i fh ] T ,i ah ,i bh ,i ch ,i dh ,i eh ,i fh are the measured high-frequency currents of the ABCEDF phases;

[0076] [L s ] represents the inductance matrix of the motor, which is an N×N matrix consisting of self-inductance L and mutual inductance;

[0077] Where L is the self-inductance, M1, M2, and M3 are the mutual inductances at three different spatial positions in the motor winding;

[0078] R s Indicates the phase resistance of the stator winding.

[0079] In this step, the theoretical basis for calculating the fault characteristic using the high-frequency voltage residual is:

[0080] First, the mathematical model of the surface-mounted six-phase permanent magnet synchronous motor in a healthy state is:

[0081]

[0082] Where [L s ]——The inductance matrix of the motor

[0083]

[0084] Where L, L ls 、L ms——are the self-inductance of each phase winding, stator leakage inductance and mutual inductance;

[0085] M1, M2, M3 - mutual inductance at three different spatial positions in the motor winding;

[0086] [V n ]——phase voltage matrix, [V n ]=[v a v b v c v d v e v f ] T ;

[0087] [I n ]——phase current matrix, [I n ]=[i a i b i c i d i e i f ] T ;

[0088] [ψ PM,n ]——Permanent magnet flux matrix (Wb). The permanent magnet flux of each phase in the stationary coordinate system can be obtained by the relative position between the stator and rotor of the permanent magnet synchronous motor. The calculation formula for the flux of the dual three-phase motor studied in this paper is as follows:

[0089]

[0090] Assuming that a fault occurs in the A-phase winding, based on the turn-to-turn short-circuit equivalent circuit fault model, the voltage equation of the motor in the fault state is:

[0091]

[0092] Where [A1] is the vector used to represent the fault phase. When phase A fails, [A1] = [1 0 0 0 0 0] T , that is, the component corresponding to the fault is 1, and the component corresponding to the healthy phase is 0.

[0093] μ——failure rate, which represents the ratio of the number of short-circuited coil turns to the total number of turns in one phase;

[0094] i F ——Short-circuit current (A), which can reflect the severity of the fault. The larger the short-circuit current, the more serious the fault;

[0095] Secondly, the voltage equation under fault state is subtracted from the voltage equation under healthy state to obtain the voltage residual v of each phase nvrThe expression of is as follows. It can be seen that the size of the voltage residual mainly depends on the motor parameters, fault rate μ and the operating conditions of the motor.

[0096]

[0097] Since the short-circuit current i reflects the severity of the fault F The voltage residual is positively correlated with the motor speed, especially at low speeds, where it is almost proportional. Therefore, diagnosing the same fault scenario at different speeds will yield different voltage residuals. This makes it impossible to decouple the diagnostic results from the motor speed. This also hinders the development of a unified standard for motors operating under complex conditions, compromising diagnostic effectiveness. Furthermore, when the motor is running at low speeds, the voltage residual is relatively small, making the diagnosis of minor faults more difficult.

[0098] In order to reduce the influence of the rotation speed on the diagnostic effect, a high-frequency voltage signal is injected into the motor control system. After the signal is injected, the short-circuit current i F High-frequency components appear in , as shown in the following formula:

[0099] i F =i F1 +i Fh =I F1 sin(θ+α1)+I Fh sin(θ h +α h )

[0100] Where i F1 、i Fh ——respectively, the fundamental frequency and high frequency short-circuit currents under high frequency injection;

[0101] I F1 , I Fh ——are the fundamental frequency and high frequency short-circuit current amplitudes under high frequency injection;

[0102] α1, α h ——are the initial phase angles of the short-circuit fault current at fundamental frequency and high frequency respectively.

[0103] Finally, by leveraging the fact that high-frequency response components are less susceptible to changes in operating conditions such as motor speed and torque, we considered creating a diagnostic method that is robust to complex motor operating conditions. Injecting a high-frequency signal not only addresses the issue of fault signatures being susceptible to operating conditions, but also amplifies the voltage residual through the differential term, facilitating the diagnosis of minor faults. Under high-frequency injection, the change in the resistance term is minimal compared to the change in the inductance and short-circuit current product term, so the high-frequency voltage residual can be simplified to:

[0104]

[0105] Where ωh ——The electrical angular frequency of the injected high-frequency signal;

[0106] θ h ——The phase angle of the injected high-frequency voltage.

[0107] Among them, the high-frequency voltage residual of the fault phase is the most prominent, while the high-frequency voltage residuals of other healthy phases are relatively small.

[0108] In this step, although there is a certain error between the calculated healthy voltage value and the actual voltage value after the fault occurs, the error is the same for all six phases, so it does not cause additional imbalance between the six-phase windings. Furthermore, compared to the healthy voltage, the six-phase voltage after the fault will produce an additional zero-sequence voltage component. This is caused by the disruption of the impedance symmetry of the six-phase windings. However, the voltage offset caused by the zero-sequence voltage is the same for all six phases and is therefore not considered an error source.

[0109] Step 3: Calculate the fault characteristic quantity: According to the high-frequency voltage residual of each phase Obtain fault characteristic quantity and convert each phase high frequency voltage residual Input to the fault characteristic quantity calculation module, the fault characteristic quantities calculated by this module include the standard deviation SD of the high-frequency voltage residual and the absolute average value Z of the high-frequency voltage residual of each phase n ;

[0110] Among them, the standard deviation of the high-frequency voltage residual SD is calculated as follows:

[0111]

[0112] Where V0 is the average value of the high-frequency voltage residual of each phase,

[0113] Among them, the absolute average value Z of the high-frequency voltage residual of each phase n Calculate as follows:

[0114]

[0115] Where, T v is the integration period, T v =k×T s , T s is the electrical period, k is the ratio of the integral period to the electrical period, k≤1.

[0116] Step 4: Diagnosis of inter-turn short circuit fault. The standard deviation SD and the absolute average value Z of the high-frequency voltage residual of each phase are n Input to the inter-turn short circuit fault diagnosis module to determine whether the motor winding is faulty. If a fault occurs, further locate the fault phase and determine the severity of the fault. If no fault occurs, return to step 1 to continue monitoring.

[0117] The judgment criteria for inter-turn short circuit fault are:

[0118] SD>SD T Indicates that a turn-to-turn short circuit fault has occurred, otherwise it is healthy, SD T is the fault threshold, SD T =0.36.

[0119] The fault phase is determined by: when a turn-to-turn short circuit fault occurs, the absolute average value Z of the high-frequency voltage residual is n The largest phase is the fault phase.

[0120] The severity of the fault is determined by:

[0121] SD=(0.36,0.48] indicates that the motor turn-to-turn short circuit fault is mild;

[0122] SD = [0.48, 0.83) indicates that the motor inter-turn short circuit fault is of moderate severity;

[0123] SD=[0.83,+∞) indicates that the motor inter-turn short circuit fault is serious.

[0124] In summary, the processing basis of the turn-to-turn short circuit fault diagnosis module is: after the fault occurs, the dispersion of the residuals of each phase increases, and once the standard deviation SD exceeds the fault threshold, the fault can be judged to have occurred. Then, according to the absolute average value Z of the high-frequency voltage residuals of each phase n The magnitude relationship determines the fault phase, Z n The largest phase is the fault phase. n Both can represent the severity of the fault. The larger the value of the two fault characteristic quantities, the more serious the fault. In this embodiment, SD is used as the standard for judging the severity of the fault, and the SD threshold is set to 0.36.

[0125] like Figure 4 The figure shows the influence of speed change on the diagnostic effect of the present invention, keeping the load torque 10N·m constant and the speed changing within the rated range. n The Z of the fault phase is the largest among all phases. n . Figure 4 (a) Two conductor short circuit scenarios are minor faults. Figure 4 (b) Both scenarios are serious faults, and the severity of the two faults in each figure is similar. Simulation results show that in this embodiment, the present invention can diagnose minor faults that are difficult to diagnose and distinguish between similar faults. The diagnostic effect is almost unaffected by changes in speed conditions.

[0126] like Figure 5The figure shows the effect of torque change on the diagnostic effect of the present invention. The speed is kept constant at 1000r / min and the load torque changes within the rated range. n The Z of the fault phase is the largest among all phases. n , Figure 5 (a) Two conductor short circuit scenarios are minor faults. Figure 5 (b) Both scenarios are serious faults, and the severity of the two faults in each figure is similar. The results show that in this embodiment, the present invention can diagnose serious faults and distinguish similar faults, and the diagnostic effect is only slightly affected by changes in torque conditions.

[0127] like Figure 6 The figure shows the influence of the coupling change of speed and torque within the rated range on the diagnostic effect of the present invention. n The Z of the fault phase is the largest among all phases. n , Figure 6 (a) Two conductor short circuit scenarios are minor faults. Figure 6 (b) Both scenarios are serious faults, and the severity of the two faults in each figure is similar. Simulation results show that in this embodiment, the characteristic value surface is relatively flat and there is no aliasing, demonstrating the good robustness of the present invention under complex operating conditions with coupled changes in speed and torque.

[0128] like Figure 7 The figure shows the effect of torque step change on the diagnostic effect of the present invention. Keeping the speed at 1000r / min unchanged, the torque changes in a step-by-step manner within the rated range. n The Z of the fault phase is the largest among all phases. n , Figure 7 (a) is the torque step-by-step change process, Figure 7 (b) Figure 7 (c) shows the time-varying curves of the characteristic quantities corresponding to four different fault scenarios. The results demonstrate that, in this embodiment, the present invention can clearly reflect the differences in characteristic quantities between healthy and faulty states, identify the occurrence of a fault, and locate the faulty phase. Furthermore, the characteristic quantities exhibit minimal fluctuations during transient torque changes and are not susceptible to interference from sudden current changes, demonstrating the present invention's robustness under complex operating conditions characterized by step-like torque variations.

[0129] like Figure 8 The figure shows the effect of sinusoidal speed change on the diagnostic effect. The load torque is kept constant at 10N·m and the speed changes sinusoidally within the range of 1000r / min. n The Z of the fault phase is the largest among all phases. n , Figure 8 (a) is the sinusoidal change process of the speed, Figure 8(b) Figure 8 (c) shows the time-varying curves of the characteristic quantities corresponding to four different fault scenarios. The results demonstrate that, in this embodiment, the present invention can clearly reflect the differences in characteristic quantities between healthy and faulty states, diagnose the occurrence of a fault, and locate the faulty phase. The characteristic quantities exhibit minimal fluctuations with speed changes, demonstrating the present invention's robustness under complex operating conditions involving sinusoidal speed variations.

[0130] Although the present invention is described herein with reference to specific embodiments, it should be understood that these embodiments are merely illustrative of the principles and applications of the invention. It should be understood that many modifications may be made to the illustrative embodiments, and that other arrangements may be devised, without departing from the spirit and scope of the invention as defined by the appended claims. It should be understood that the various dependent claims and features described herein may be combined in ways other than those described in the original claims. It should also be understood that features described in conjunction with individual embodiments may be used in conjunction with other described embodiments.

Claims

1. A method for diagnosing inter-turn short-circuit faults of a permanent magnet motor considering the influence of complex working conditions, characterized in that: The method comprises the following steps: Step 1: high-frequency signal injection and information collection step; Inject high-frequency rotating voltage signals into the motor control system in the natural coordinate system, where n represents each phase winding of the motor, n = a, b, c...; The high-frequency current i of each phase of the motor is collected through a bandpass filter nh and each phase high frequency voltage Step 2: High frequency voltage The healthy voltage under the injection of high frequency signal The high-frequency voltage residual of each phase is calculated by subtracting Step 3: Calculate the fault characteristic quantity: According to the high-frequency voltage residual of each phase Obtain fault characteristics, which include the standard deviation SD of the high-frequency voltage residual and the absolute average value Z of the high-frequency voltage residual of each phase. n ; Step 4: Turn-to-turn short circuit fault diagnosis: Determine whether a turn-to-turn short circuit fault occurs based on the fault characteristic quantity, and determine the fault phase.

2. A permanent magnet motor turn-to-turn short circuit fault diagnosis method considering the influence of complex working conditions according to claim 1, characterized in that: The process of step 2 is: The high-frequency voltage residual of each phase is obtained by the following formula: Where, Represents the high-frequency voltage residual matrix, which is composed of the high-frequency voltage residual of each phase The N×1 matrix is formed, where N is the number of motor phases; Represents the high-frequency voltage matrix, which is composed of the high-frequency voltage of each phase The N×1 matrix formed; Represents the high-frequency healthy voltage matrix, which is the healthy voltage injected by each phase at high frequency The N×1 matrix; high-frequency health voltage matrix Estimate as follows: In the formula, [I nh ] represents the high-frequency current matrix, and the high-frequency current i of each phase nh The N×1 matrix formed; [L s ] represents the inductance matrix of the motor, which is an N×N matrix consisting of self-inductance L and mutual inductance; R s Indicates the phase resistance of the stator winding.

3. A permanent magnet motor turn-to-turn short circuit fault diagnosis method considering the influence of complex working conditions according to claim 2, characterized in that: The standard deviation SD of the high-frequency voltage residual in step 3 is calculated as follows: Where V0 is the average value of the high-frequency voltage residual of each phase, 4. A permanent magnet motor turn-to-turn short circuit fault diagnosis method considering the influence of complex working conditions according to claim 3, characterized in that: The absolute average value Z of the high-frequency voltage residual of each phase in step 3 n Calculate as follows: Where, T v is the integration period, T v =k×T s , T s is the electrical period, k is the ratio of the integral period to the electrical period, k≤1.

5. A permanent magnet motor turn-to-turn short circuit fault diagnosis method considering the influence of complex working conditions according to claim 4, characterized in that: The judgment criteria for the inter-turn short circuit fault in step 4 are: SD>SD T Indicates that a turn-to-turn short circuit fault has occurred, otherwise it is healthy, SD T is the fault threshold.

6. A permanent magnet motor turn-to-turn short circuit fault diagnosis method considering the influence of complex working conditions according to claim 5, characterized in that: The fault phase is determined in step 4 as follows: when a turn-to-turn short circuit fault occurs, the absolute average value of the high-frequency voltage residual Z n The largest phase is the fault phase.

7. A permanent magnet motor turn-to-turn short circuit fault diagnosis method considering the influence of complex working conditions according to claim 1, characterized in that: The phase difference between each phase of the injected high-frequency rotating voltage signal is consistent with the phase difference between the motor windings.

8. The method for diagnosing a permanent magnet motor turn-to-turn short circuit fault considering the influence of complex working conditions according to claim 1, characterized in that: The method of the present invention is suitable for realizing fault diagnosis under complex working conditions of sinusoidal speed change, step-by-step torque change and speed-torque coupled change.

9. The method for diagnosing a permanent magnet motor turn-to-turn short circuit fault considering the influence of complex working conditions according to claim 1, characterized in that: This method is suitable for diagnosing a turn-to-turn short circuit fault in a single-phase winding.

10. The method for diagnosing a permanent magnet motor turn-to-turn short circuit fault considering the influence of complex working conditions according to claim 1, characterized in that: This method is applicable to a structure in which each phase winding of a motor is a coil or multiple coils are connected in series.

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