Three-phase permanent magnet synchronous motor turn-to-turn short circuit fault severity and phase diagnosis method

Abstract

The invention provides a three-phase permanent magnet synchronous motor turn-to-turn short circuit fault severity and phase diagnosis method, which combines a signal-based fault diagnosis method and a model-based fault diagnosis method, and is characterized in that residual signals for fault diagnosis are obtained through actually measured alpha-beta plane voltage and current signals of a motor; a state observer is not used, and the method does not depend on an accurate mathematical model and motor parameters; only alpha-beta plane voltage and current signals are needed, additional hardware does not need to be added, invasiveness is avoided, and the method can be easily integrated into a three-phase permanent magnet synchronous motor control system; whether the motor has a turn-to-turn short circuit fault or not, quantitative representation of severity of the motor turn-to-turn short circuit fault and phase positioning of the turn-to-turn short circuit fault can be realized at the same time; hilbert transformation is only carried out on alpha-beta plane voltage and current signals, and a large amount of historical data is not needed for training and calculation.

Description

Technical Field

[0001] This invention belongs to the field of fault diagnosis technology for three-phase permanent magnet synchronous motor drive systems, specifically relating to a non-intrusive inter-turn short circuit fault severity and phase diagnosis method for three-phase permanent magnet synchronous motors. Background Technology

[0002] With the increasing demand for high power / torque density in motors, motors will be subjected to higher electrical, thermal, and mechanical stresses, which can easily lead to motor failures. Among these, inter-turn short circuit faults are a relatively common and difficult-to-detect type of fault.

[0003] When a motor experiences an inter-turn short-circuit fault, a large short-circuit current will be generated due to the low impedance in the short-circuit loop, resulting in intense heat at the fault point. Without fault-tolerant control and maintenance, this will further lead to residual insulation degradation and irreversible demagnetization of the permanent magnets. Therefore, real-time monitoring of the healthy operation of a three-phase permanent magnet synchronous motor, designing a rapid and reliable inter-turn short-circuit fault diagnosis method, and identifying whether an inter-turn short-circuit fault has occurred, its severity, and the phase in which it occurs are crucial for post-fault fault-tolerant operation and preventing catastrophic failures.

[0004] To ensure timely diagnosis of inter-turn short-circuit faults in three-phase permanent magnet synchronous motor drive systems and guarantee safe and reliable motor operation, common methods include model-based, signal-based, and data-driven diagnostic methods. However, model-based methods often require precise mathematical models to generate the necessary residuals, which are affected not only by inter-turn short-circuit faults but also by parameter variations, unbalanced currents, and measurement noise—all of which can coexist even when the drive system is healthy. Data-driven methods require large datasets for training and learning, placing high demands on the system's computational power and resulting in relatively long computation times. Signal-based diagnostic methods, on the other hand, can diagnose inter-turn short-circuit faults without requiring precise mathematical models, motor parameters, or large datasets for training, without increasing hardware intrusion.

[0005] In related technologies, Chinese patent application CN119149984A discloses a method for diagnosing inter-turn short-circuit faults based on feature selection and multi-scale residual networks. Chinese patent application CN118980926A discloses a digital twin system for diagnosing inter-turn short-circuit faults in permanent magnet synchronous motors. Chinese patent application CN118801767A discloses a method for locating and monitoring early inter-turn short-circuit faults in permanent magnet synchronous motors. Chinese patent application CN118747255A discloses a simplified prediction method for the short-circuit current of inter-turn short circuits in fault-tolerant permanent magnet synchronous motors. Chinese patent application CN118884214A discloses a method, diagnostic device, inter-turn protection method, and protection device for diagnosing inter-turn faults in permanent magnet wind turbines based on current residuals.

[0006] In summary, designing a diagnostic method that can monitor the severity of inter-turn short circuit faults and locate the fault phase in a permanent magnet synchronous motor in real time without hardware intrusion, by making full use of the control signals in the permanent magnet synchronous motor control system, is crucial for post-fault shutdown maintenance, fault-tolerant operation, and prevention of catastrophic failures. Summary of the Invention

[0007] (a) Technical problems to be solved

[0008] This invention proposes a method for diagnosing the severity and phase of inter-turn short-circuit faults in a three-phase permanent magnet synchronous motor, in order to solve the technical problem of how to monitor the severity and locate the fault phase of an inter-turn short-circuit fault in a permanent magnet synchronous motor in real time without hardware intrusion.

[0009] (II) Technical Solution

[0010] To address the aforementioned technical problems, this invention proposes a method for diagnosing the severity and phase of inter-turn short-circuit faults in three-phase permanent magnet synchronous motors (PMSMs). This method involves extracting voltage and current signals in a stationary coordinate system from the PMSM control system, performing Hilbert transform and signal processing on these signals, establishing a mathematical model of the natural coordinate system and stationary coordinate system after an inter-turn short-circuit fault, extracting fault characteristics related to the short-circuit current from the current signal in the stationary coordinate system based on the established mathematical model, establishing diagnostic factors for whether an inter-turn short-circuit fault has occurred and its severity, indicating whether an inter-turn short-circuit fault has occurred and quantitatively representing its severity, and extracting the differences in inter-turn short-circuit fault occurrence at different phases from the orthogonal signals composed of the voltage signal and its Hilbert transform signal in the stationary coordinate system, establishing relevant fault factors, and thus locating the phase of the inter-turn short-circuit fault.

[0011] (III) Beneficial Effects

[0012] This invention proposes a method for diagnosing the severity and phase of inter-turn short-circuit faults in three-phase permanent magnet synchronous motors. This invention combines signal-based and model-based fault diagnosis methods. The residual signal used for fault diagnosis is obtained from the measured α-β plane voltage and current signals of the motor, without using a state observer or relying on precise mathematical models and motor parameters. It only requires α-β plane voltage and current signals, without adding additional hardware, is non-intrusive, and is easily integrated into the three-phase permanent magnet synchronous motor control system. It can simultaneously diagnose whether an inter-turn short-circuit fault has occurred, quantitatively represent the severity of the inter-turn short-circuit fault, and locate the phase of the inter-turn short-circuit fault. It only performs Hilbert transform on the α-β plane voltage and current signals, without requiring extensive historical data for training and calculation. Attached Figure Description

[0013] Figure 1 This is a block diagram of the three-phase permanent magnet synchronous motor control system of the present invention;

[0014] Figure 2 This is a diagram of the equivalent circuit model of the inter-turn short circuit of the A-phase winding of the three-phase permanent magnet synchronous motor of the present invention.

[0015] Figure 3 A flowchart illustrating the quantitative representation of the severity of inter-turn short-circuit faults in the three-phase permanent magnet synchronous motor of the present invention;

[0016] Figure 4 This is a flowchart of the phase location process for inter-turn short circuit faults in a three-phase permanent magnet synchronous motor according to the present invention.

[0017] Figure 5 The simulation results of the inter-turn short-circuit phase current and α-β plane current of the three-phase permanent magnet synchronous motor of the present invention are as follows (short-circuit turns ratio μ = 20%, contact resistance Rs = 0.2Ω);

[0018] Figure 6 The simulation results of the inter-turn short-circuit phase current and α-β plane current of the three-phase permanent magnet synchronous motor of the present invention are shown (short-circuit turns ratio μ = 40%, contact resistance Rs = 0.2Ω). Detailed Implementation

[0019] To make the objectives, contents, and advantages of the present invention clearer, the specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples.

[0020] This embodiment proposes a method for diagnosing the severity and phase of inter-turn short-circuit faults in a three-phase permanent magnet synchronous motor. The method involves extracting voltage and current signals in a stationary coordinate system from the three-phase permanent magnet synchronous motor control system, performing Hilbert transform and signal processing on these signals, establishing a mathematical model of the natural coordinate system and stationary coordinate system after an inter-turn short-circuit fault, extracting fault characteristics related to the short-circuit current from the current signal in the stationary coordinate system based on the established mathematical model, establishing diagnostic factors for whether an inter-turn short-circuit fault has occurred and its severity, indicating whether an inter-turn short-circuit fault has occurred and quantitatively representing its severity, and extracting the differences in inter-turn short-circuit fault occurrence at different phases from the orthogonal signals composed of the voltage signal and its Hilbert transform signal in the stationary coordinate system, establishing relevant fault factors, and achieving phase localization of the inter-turn short-circuit fault.

[0021] The three-phase permanent magnet synchronous motor control system in this embodiment is as follows: Figure 1 As shown, it includes a speed outer loop controller, a current inner loop controller, a stationary coordinate transformation (Clark transformation, as shown in equation (1)), a rotating coordinate transformation (Park transformation, as shown in equation (2)), SVPWM modulation, a voltage-type two-level three-bridge inverter, a surface-mounted three-phase permanent magnet synchronous motor, a torque sensor, a current sensor, a rotary transformer, and an inter-turn short-circuit fault detection module. Figure 1 in,i dr and i qr These are the reference currents in the dq plane, i and i are respectively. d and i q These are the actual currents in the dq plane, i and i are respectively. α and i β These are the α-β plane currents, i abc U represents the three-phase winding current of the motor. d and u q These are the dq plane voltages, u α and u β These are the α-β plane voltages, S abc This is the inverter drive signal, where Udc is the DC bus voltage, θ is the electrical angle, and ω is the voltage at the DC bus. m , n and n r These represent the motor's mechanical angular velocity, rotational speed, and reference speed, respectively. PI m PI d and PI q These are PI controllers for speed, d-axis current, and q-axis current, respectively; PMSM is a surface-mounted three-phase permanent magnet synchronous motor; SVPWM is space vector pulse width modulation; and VSI is a voltage-type three-phase two-level inverter.

[0022] The deviation between the measured motor speed and the reference speed is controlled via a PI controller to form the outer loop speed control. The measured three-phase current of the motor is converted into the dq-axis current in a synchronous rotating coordinate system through Clark and Park transformations, and then controlled via a PI controller to form the inner loop current control. SVPWM modulation is used, and the motor is powered through a voltage-type two-level three-bridge inverter (VSI).

[0023] Signal processing and Hilbert transform of current and voltage signals in a stationary coordinate system (α-β) include filtering the extracted α-β plane voltage and current signals to extract the fundamental voltage and current signals in the α-β plane, followed by Hilbert transform to obtain orthogonal signal sets of voltage and current along the α-axis and β-axis. Residuals are generated from the α-axis and β-axis current signal sets to obtain information about the short-circuit current i. f The characteristic variables are used to establish a fault factor FI1 to diagnose whether an inter-turn short circuit fault has occurred in the motor and to quantitatively represent the severity of the inter-turn short circuit fault. A corresponding diagnostic threshold Th is set; when the fault factor FI1 exceeds the threshold, an inter-turn short circuit fault is determined to have occurred in the motor, and the severity of the inter-turn short circuit fault is quantitatively represented by the value of the fault factor. The voltage distortion after an inter-turn short circuit fault occurs in different phases is analyzed using the voltage quadrature signal group of the α-axis and the voltage signal group of the β-axis. Based on the different distortion degrees of the voltage quadrature signal group of the α-axis and the voltage signal group of the β-axis, a fault factor FI2 is established to distinguish the phase of the inter-turn short circuit fault in the motor.

[0024] The current signal in the stationary coordinate system is obtained by transforming the phase winding current signal measured by the current sensor into stationary coordinates. The voltage signal in the stationary coordinate system is obtained by inverse rotation transformation of the dq-axis voltage signal output by the dq-axis current controller. The extracted voltage and current signals in the stationary coordinate system are then subjected to fundamental signal extraction and Hilbert transform to obtain two sets of mutually orthogonal fundamental signals along the α-axis and β-axis.

[0025]

[0026] In this real-time example, the equivalent circuit model for an inter-turn short-circuit fault in phase A of a three-phase motor is as follows: Figure 2 As shown, the equivalent circuit model divides the A-phase winding where an inter-turn short-circuit fault occurs into a healthy part and an inter-turn short-circuit part, R ah L ah e ah These represent the resistance, inductance, and back EMF of the healthy portion of phase A winding, respectively; R af L af e af These represent the resistance, inductance, and back EMF of the faulty section of phase A winding; R f Contact resistance for inter-turn short-circuit faults; if Contact resistance R f Branch current; R b L b and e b These represent the resistance, inductance, and back EMF of phase B winding, respectively. c L c and e c These represent the resistance, inductance, and back EMF of the C-phase winding, respectively.

[0027] The impedance and back electromotive force between the healthy section and the inter-turn short-circuit section are related to the number of short-circuit turns. μ is the short-circuit turns ratio μ = Nc / Ns, which represents the ratio of the number of turns Nc that have an inter-turn short-circuit fault to the total number of turns Ns of the motor phase winding. The larger μ is, the more turns have an inter-turn short circuit, and the more severe the inter-turn short-circuit fault is. The relationship between each impedance and back electromotive force and the short-circuit turns ratio μ is shown in equation (3). Wherein, R s L is the phase winding resistance. k (k = a, b, c) represents the self-inductance of the k-phase winding, M k1k2 (k1,k2=a,b,c) represents the mutual inductance between phases k1 and k2, e k (k = a, b, c) is the back electromotive force of the k-phase winding, M ahaf For the mutual inductance between the healthy portion and the inter-turn short-circuit fault portion of phase A winding, M ahk and M afk These represent the mutual inductance between the healthy portion and the portion with an inter-turn short circuit fault in phase A of the motor, and the phase k (k = b, c) windings, respectively. The parallel contact resistance in the winding section with the inter-turn short circuit fault is equivalent to the degree of insulation degradation of the motor. The smaller the contact resistance value, the greater the degree of insulation degradation. When the contact resistance value is 0, it indicates that the winding insulation is completely damaged.

[0028]

[0029] A mathematical model is established based on the equivalent circuit model of inter-turn short-circuit fault in the natural coordinate system and the relationship between circuit parameters, short-circuit turns ratio, and contact resistance. A Clark transformation is then performed on the mathematical model to obtain the mathematical model of inter-turn short-circuit fault in the stationary coordinate system. The mathematical model of inter-turn short-circuit fault in the stationary coordinate system is analyzed to extract relevant short-circuit current i. f Fault characteristics.

[0030] After an inter-turn short-circuit fault occurs in phase A winding, the voltage equation of the motor in the natural coordinate system is:

[0031]

[0032] Based on equation (1), performing Clark transformation on equation (4), the voltage equation of the α-β plane after the inter-turn short-circuit fault in phase A is obtained as follows:

[0033]

[0034] Among them, u αfA u βfA Let α-β be the plane voltage after an inter-turn short-circuit fault occurs in phase A. According to equation (5), when an inter-turn short-circuit fault occurs in phase A of the motor, the α-axis current is equivalent to the superposition of (-2μ / 3)i in the healthy mode. f The short-circuit current is large, while the β-axis current remains at its healthy value. The α-axis voltage is severely distorted, while the β-axis voltage remains undistorted.

[0035] Under healthy conditions, the α-axis and β-axis currents are sinusoidal currents with equal amplitude and orthogonality, assuming the α-β plane current is as shown in equation (6). When an inter-turn short circuit occurs, the short-circuit current i f The winding current is in phase with the winding current that experiences an inter-turn short-circuit fault; only the short-circuit current i is considered. f The fundamental frequency component, short-circuit current i f The expression is shown in equation (7). Where, I f For short-circuit current i f The amplitude, θ k (when k = a, θ) k =0; when k=b, θ k = -2π / 3; when k = c, θ k =2π / 3) is the phase of the short-circuit current.

[0036]

[0037] if = -I f sin(θ+θ k (7)

[0038] Based on the α-axis and β-axis current distortions expressed in equation (5) and equations (6) and (7), the α-β plane current when an inter-turn short-circuit fault occurs in phase A can be derived as follows:

[0039]

[0040] Among them, i αfA i βfA The α-β plane current is the current after an inter-turn short-circuit fault occurs in phase A.

[0041] As can be seen from equation (8), after an inter-turn short-circuit fault occurs, the α-β plane current is equivalent to the short-circuit current i superimposed on the original fundamental current. f The fundamental component of the α-β plane current is distorted, thus the fault characteristics that characterize the inter-turn short circuit fault of the motor can be obtained from the distortion of the α-β plane current.

[0042] When an inter-turn short circuit fault occurs in phase B or phase C of the motor, simply... Figure 2 The contact resistance R in the equivalent circuit shown f The branch is connected in parallel to the faulty section of phase B or phase C. The α-β plane voltage equations after an inter-turn short circuit fault occurs in phase B and phase C are shown in equations (9) and (10).

[0043]

[0044] Among them, u αfB u βfB and u αfC u βfC Let α and β be the plane voltages after inter-turn short-circuit faults in phases B and C, respectively. From equations (9) and (10), it can be seen that, unlike inter-turn short-circuit faults in phase A, after inter-turn short-circuit faults in phases B and C, both the α-axis voltage and β-axis voltage will increase due to the superimposed short-circuit current i f The distortion is caused by the component. By combining equations (9) and (10) with equations (6) and (7), the expressions for the α-β plane current when inter-turn short circuit faults occur in phase B and phase C can be derived, as shown in equations (11) and (12).

[0045]

[0046] From the above equations for the α-β plane voltage and current after an inter-turn short-circuit fault in the motor, it can be seen that the α-β plane voltage and current of the motor will be affected by the superposition of the short-circuit current i. f This distortion can characterize the severity of inter-turn short-circuit faults in the motor. However, when the same degree (μ and R) occurs in different phase windings... f When there is a short circuit between turns (of the same type), the distortion of the α-β plane current is different, and the α-β plane current is a sinusoidal current that is orthogonal to each other, making it difficult to extract fault features by directly processing it. Therefore, a set of current signals orthogonal to the α axis and a set of current signals orthogonal to the β axis can be constructed by Hilbert transform, and the residual of the two sets of orthogonal signals can be used to diagnose whether the motor has a short circuit between turns and the severity of the short circuit fault. The expression of Hilbert transform is shown in equation (13), where x is the original signal, H(x) is the signal after Hilbert transform, and x and H(x) constitute a set of mutually orthogonal signals. The constructed set of current signals orthogonal to the α axis and the set of current signals orthogonal to the β axis can form a residual, eliminating the -i of the healthy operation part of the motor. q sin(θ) and i q The cos(θ) component retains only the part related to the severity of the fault, i.e., i f Related components.

[0047]

[0048] The residual FI1 can be formed by the mutually orthogonal current signal groups along the α-axis and the mutually orthogonal current signal groups along the β-axis. This residual FI1 serves as a fault factor and can quantitatively characterize the short-circuit current i after an inter-turn short-circuit fault occurs in the motor. f Furthermore, setting a corresponding diagnostic threshold Th can enable the diagnosis of whether the motor has experienced an inter-turn short circuit fault. The expression for the fault factor FI1 is shown in equation (14), where, (i α ,H(i α )) and (i β ,H(i β () represents a set of current signals orthogonal to each other along the α-axis and a set of current signals orthogonal to each other along the β-axis. f() is a function that processes the set of current signals orthogonal to each other along the α-β axes to obtain the residual in the set of signals, which is only related to the short-circuit current i. f Relevant characteristic variables. Obtain only the short-circuit current i. f After considering the relevant characteristic variables, a sliding window integration is performed over one current cycle, and the average is taken to convert it into a DC quantity. This reduces the deviation in the residual and the interference during motor operation. In the formula, T... S This is one fundamental current cycle.

[0049]

[0050] The diagnostic process for determining whether a three-phase permanent magnet motor has an inter-turn short-circuit fault and the quantitative expression of the severity of the inter-turn short-circuit fault is as follows: Figure 3 As shown, the three-phase winding current measured by the current sensor during the operation of the three-phase permanent magnet synchronous motor is transformed by Clark to obtain the α-β plane current. The fundamental component is obtained through a low-pass filter. Then, the α-β plane current is transformed by Hilbert according to Equation (13) to obtain the current signal groups that are orthogonal to the α axis and the current signal groups that are orthogonal to the β axis. The fault factor FI1 is constructed by Equation (14) to characterize whether the motor has an inter-turn short circuit fault and to quantitatively represent the severity of the inter-turn short circuit fault. The diagnostic threshold Th is determined according to the maximum short-circuit current amplitude that the motor can tolerate during actual operation and application. On the one hand, it can more accurately diagnose minor inter-turn short circuit faults, and on the other hand, it can prevent misdiagnosis caused by asymmetry of the motor's α-β plane impedance parameters. When the fault factor FI1 is less than the set diagnostic threshold, it is determined that the motor has not had an inter-turn short circuit fault; when the fault factor FI1 is greater than the diagnostic threshold Th, it is determined that the motor has had an inter-turn short circuit fault, and the short-circuit current i is quantitatively represented by the value of the fault factor FI1. f The amplitude is used to characterize the severity of inter-turn short circuit fault diagnosis in motors.

[0051] According to equations (5), (9), and (10), when an inter-turn short-circuit fault occurs in phases A, B, and C, the α-β plane voltage undergoes different degrees of distortion. Therefore, the relevant short-circuit current i can be extracted from the α-β plane voltage. f The additional components are used to distinguish the phase of the inter-turn short circuit fault based on the different distortion degrees of the α-axis voltage and β-axis voltage when the inter-turn short circuit fault occurs in different phases.

[0052] Assume the expression for the α-β plane voltage under healthy conditions is as follows:

[0053]

[0054] Where A is the magnitude of the α-β plane voltage. Let α be the phase angle of the α-β plane voltage, and its specific expression is shown in equation (16):

[0055]

[0056] Based on equation (16) and the voltage equations (5), (9) and (10) under inter-turn short-circuit fault, the α-β plane voltages when inter-turn short-circuit faults occur in phases A, B and C can be expressed as shown in equations (17), (18) and (19):

[0057]

[0058]

[0059] Where B and θ R The amplitude and phase angle of the additional component after the motor experiences an inter-turn short circuit fault are given by equation (20):

[0060]

[0061] It can be seen from equations (17) to (20) that, under the same inter-turn short-circuit fault severity, when inter-turn short-circuit faults occur in different phases, the superposition of relevant short-circuit currents i f The additional fundamental component in u α u β The images show varying degrees of distortion.

[0062] First, the u output from the inner current loop PI controller of the three-phase permanent magnet synchronous motor control system is filtered through a low-pass filter. α u β Extracting the fundamental component of the α-β plane voltage from the control signal for u α u β Perform a Hilbert transform according to equation (13) to obtain a group of voltage signals (u) that are orthogonal to each other along the α axis. α ,H(u αThe voltage signal group (u) that is orthogonal to the β axis β ,H(u β The two sets of orthogonal voltage signals are transformed and processed to eliminate the healthy operation of the α-β plane voltage. Components and The component only retains the relevant short-circuit current i caused by the inter-turn short-circuit fault. f The additional components of the α-axis voltage and β-axis voltage are used to obtain the fault factor FI2 related to the inter-turn short-circuit fault from different values ​​of the additional components of the α-axis voltage and β-axis voltage, as shown in equation (21). α ,H(u α )) and (u β ,H(u β Let f1 be a set of voltage signals orthogonal to the α-axis and a set of voltage signals orthogonal to the β-axis. f1() is a transformation and function processing of the α-β axis orthogonal current signal sets. By using the ratio of the square root of the difference between the β-axis orthogonal voltage signal set and the α-β plane orthogonal voltage signal set, we seek to quantitatively represent the difference in the degree of distortion of the α-axis voltage and β-axis voltage when an inter-turn short-circuit fault occurs at different phases. This difference characterizes the phase of the inter-turn short-circuit fault in the motor. Furthermore, by averaging the integral over a sliding window of one fundamental current cycle, we eliminate other influences such as disturbances during motor operation; the magnitude of this average value is used to distinguish the phase of the inter-turn short-circuit fault.

[0063]

[0064] The diagnostic process for locating the phase of an inter-turn short circuit fault in a three-phase permanent magnet motor is as follows: Figure 4 As shown, u is extracted from the current loop PI controller during the operation of a three-phase permanent magnet synchronous motor. d u q The control signal is then subjected to an inverse Clark transform to obtain u. α u β The control signal is filtered by a low-pass filter to extract the fundamental component of the α-β plane voltage control signal. Then, the fundamental component of the filtered α-β plane voltage control signal is subjected to a Hilbert transform according to equation (13) to obtain a group of voltage signals (u) that are orthogonal to each other along the α axis. α ,H(u α The current signal group (u) that is orthogonal to the β axis β ,H(u β The fault factor FI2 is constructed using equation (21) to characterize the difference in distortion between the α-axis and β-axis voltages. Its specific value determines the phase of the inter-turn short-circuit fault in the motor. It should be noted that the diagnosis of the inter-turn short-circuit fault phase using FI2 is performed after the fault factor FI1 is greater than Th, i.e., through... Figure 3The flowchart shown illustrates the diagnosis of the severity of inter-turn short circuit faults. After diagnosing an inter-turn short circuit fault in the motor, the severity is then determined based on... Figure 4 The flowchart shown diagnoses the phase of an inter-turn short circuit fault in the motor. When the fault factor FI1 is less than Th, it diagnoses that no inter-turn short circuit fault has occurred in the motor; therefore, it is not enabled at this time. Figure 4 The algorithm for locating inter-turn short-circuit fault phase is shown.

[0065] Figure 5 and Figure 6 This presents simulation results of inter-turn short-circuit faults in phases A and B of a surface-mounted three-phase permanent magnet synchronous motor control system model built in MATLAB / Sumlink software. The motor adopts a 10-pole, 12-slot structure, and the permanent magnet flux linkage amplitude is ψ. f =0.0217Wb, winding resistance R S =0.5Ω, dq-axis inductance Ld=Lq=2.88×10 -4 H, moment of inertia J = 3.57 × 10 -4 kg·m 2 . Figure 5 In the middle, the motor operates at n = 1000 rpm, T e Under the fault-free start-up condition of 5 N·m, a short-circuit fault occurred in phase A winding at 1 second, with a short-circuit turns ratio μ = 20% and a contact resistance Rf = 0.2 Ω. Simulation results show that before 1 second, the three-phase winding currents are symmetrical, and the α-β plane currents are equal in amplitude and mutually orthogonal sine waves. At 1 second, the inter-turn short-circuit fault occurred in phase A, and the currents of all three phases were distorted, with the faulty phase winding experiencing the greatest distortion. The degree of α-β plane current distortion is consistent with theoretical analysis. Compared to the β-axis current, the α-axis current is more distorted due to the superposition of the short-circuit current i. f This results in severe distortion. Figure 6 In the middle, the motor is Figure 5 During a fault-free start-up under the same operating conditions, a short circuit occurred in the B-phase winding at 1 second, with a turns ratio μ = 40% and a contact resistance R. f =0.2Ω inter-turn short circuit fault. When a B-phase inter-turn short circuit fault occurs in the motor, the amplitude and distortion of the B-phase winding current are greater than those of the other two phases. In the α-β plane current, compared with... Figure 5 The distortion degrees of the inter-turn short-circuit fault in phase A shown are different. Both the α-axis current and the β-axis current are strongly distorted, with the β-axis current showing a relatively larger distortion degree. This is consistent with the result derived from equation (11). Figure 5 and Figure 6 The simulation results of inter-turn short-circuit faults in phase A and phase B windings show that, under different degrees of inter-turn short-circuit faults, the α-β plane current superimposed on the short-circuit current i fThe amplitudes differ, and as the severity of the fault increases, the distortion of the α-β plane current increases, resulting in an additional component, the recirculation current i. f The amplitude increases, therefore, information about the short-circuit current i can be extracted from the α-β plane current. f The additional component is feasible for detecting whether a motor has an inter-turn short-circuit fault and for quantitatively representing the severity of the inter-turn short-circuit fault. Furthermore, Figure 5 and Figure 6 The simulation results comparing the inter-turn short-circuit faults in phase A and phase B windings show that the distortion degrees of the α-axis current and β-axis current differ when inter-turn short-circuit faults occur in different phases of the motor. For example, when an inter-turn short-circuit fault occurs in phase A, the distortion degree of the α-axis current is greater than that of the β-axis current, while when an inter-turn short-circuit fault occurs in phase B, the distortion degree of the β-axis current is greater than that of the α-axis current. A similar relationship exists in the corresponding α-β plane voltage control signal. Therefore, it is feasible to seek the characteristics of inter-turn short-circuit faults in different phases from the difference in the distortion degree of the α-axis voltage and β-axis voltage signals to locate the phase of the inter-turn short-circuit fault.

[0066] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for diagnosing the severity and phase of inter-turn short-circuit faults in a three-phase permanent magnet synchronous motor, characterized in that, The method for diagnosing the severity and phase of inter-turn short-circuit faults in a three-phase permanent magnet synchronous motor includes the following steps: Voltage and current signals in the stationary coordinate system are extracted from the control system of a three-phase permanent magnet synchronous motor, and Hilbert transform and signal processing are performed on the voltage and current signals. A mathematical model of the natural coordinate system and the stationary coordinate system after an inter-turn short circuit fault in a three-phase permanent magnet synchronous motor is established. Based on the established mathematical model, fault characteristics related to the short circuit current are extracted from the current signal in the stationary coordinate system. Diagnostic factors for whether an inter-turn short circuit fault occurs and the severity of the fault are established to indicate whether an inter-turn short circuit fault has occurred in the motor and to quantitatively represent the severity of the inter-turn short circuit fault. In the orthogonal signal composed of voltage signal and its Hilbert transform signal in stationary coordinate system, the differences in the phases of inter-turn short circuit faults are extracted, relevant fault factors are established, and the phase of inter-turn short circuit fault is located.

2. The method for diagnosing the severity and phase of inter-turn short-circuit faults in a three-phase permanent magnet synchronous motor as described in claim 1, characterized in that, The deviation between the measured motor speed and the reference speed is controlled by a PI controller to form an outer loop control of the speed. The measured three-phase current of the motor is converted into the dq axis current in the synchronous rotating coordinate system through Clark transformation and Park transformation, and then controlled by a PI controller to form an inner loop control of the current. The SVPWM modulation method is adopted, and the motor is powered through a voltage-type two-level three-bridge inverter VSI.

3. The method for diagnosing the severity and phase of inter-turn short-circuit faults in a three-phase permanent magnet synchronous motor as described in claim 1, characterized in that... Signal processing and Hilbert transform of current and voltage signals in the stationary coordinate system α-β include filtering the extracted α-β plane voltage and current signals to extract the fundamental voltage and current signals in the α-β plane, then performing a Hilbert transform to obtain orthogonal signal sets of voltage and current along the α-axis and β-axis; generating residuals from the orthogonal current signal sets along the α-axis and β-axis to obtain information about the short-circuit current i. f The characteristic variables are used to establish a fault factor FI1 to diagnose whether the motor has an inter-turn short circuit fault and to quantitatively represent the severity of the inter-turn short circuit fault. A corresponding diagnostic threshold Th is set. When the fault factor FI1 exceeds the threshold, it is determined that the motor has an inter-turn short circuit fault, and the severity of the motor inter-turn short circuit fault is quantitatively represented by the value of the fault factor. The voltage distortion after the inter-turn short circuit fault occurs in different phases is analyzed by the voltage quadrature signal group of the α axis and the voltage signal group of the β axis. The fault factor FI2 is established according to the different distortion degrees of the voltage quadrature signal group of the α axis and the voltage signal group of the β axis to distinguish the phase of the motor inter-turn short circuit fault.

4. The method for diagnosing the severity and phase of inter-turn short-circuit faults in a three-phase permanent magnet synchronous motor as described in claim 1, characterized in that... The current signal in the stationary coordinate system is obtained by transforming the phase winding current signal measured by the current sensor into stationary coordinates; the voltage signal in the stationary coordinate system is obtained by transforming the dq-axis voltage signal output by the dq-axis current controller into inverse rotation; the extracted voltage and current signals in the stationary coordinate system are subjected to fundamental signal extraction and Hilbert transformation to obtain two sets of mutually orthogonal fundamental signals on the α-axis and β-axis.

5. The method for diagnosing the severity and phase of inter-turn short-circuit faults in a three-phase permanent magnet synchronous motor as described in claim 1, characterized in that... The equivalent circuit model for a three-phase motor experiencing an inter-turn short-circuit fault in phase A divides the phase A winding affected by the fault into a healthy portion and an inter-turn short-circuit portion, R ah L ah e ah These represent the resistance, inductance, and back EMF of the healthy portion of phase A winding, respectively; R af L af e af These represent the resistance, inductance, and back EMF of the faulty section of phase A winding; R f Contact resistance for inter-turn short-circuit faults; i f Contact resistance R f The short-circuit current of the branch; R b L b and e b These represent the resistance, inductance, and back EMF of phase B winding, R. c L c and e c These are the resistance, inductance, and back EMF of the C-phase winding, respectively. μ is the short-circuit turns ratio μ = Nc / Ns, which represents the ratio of the number of turns Nc that experience inter-turn short-circuit faults to the total number of turns Ns in the motor phase windings. The relationship between various impedances and back EMF and the short-circuit turns ratio μ is shown in the following formula: Among them, R s L is the phase winding resistance. k (k = a, b, c) represents the self-inductance of the k-phase winding, M k1k2 (k1,k2=a,b,c) represents the mutual inductance between phases k1 and k2, e k (k = a, b, c) is the back electromotive force of the k-phase winding, M ahaf For the mutual inductance between the healthy portion and the inter-turn short-circuit fault portion of phase A winding, M ahk and M afk These are the mutual inductances between the healthy portion and the portion with inter-turn short circuit faults of the motor A-phase winding and the k-phase windings (k = b, c). The parallel contact resistance in the winding portion with inter-turn short circuit faults is equivalent to the degree of insulation degradation of the motor. The smaller the contact resistance value, the greater the degree of insulation degradation. When the contact resistance value is 0, it indicates that the winding insulation is completely damaged.

6. The method for diagnosing the severity and phase of inter-turn short-circuit faults in a three-phase permanent magnet synchronous motor as described in claim 1, characterized in that... A mathematical model is established based on the equivalent circuit model of inter-turn short-circuit fault in the natural coordinate system and the relationship between circuit parameters, short-circuit turns ratio, and contact resistance. The mathematical model is then subjected to Clark transformation to obtain the mathematical model of inter-turn short-circuit fault in the stationary coordinate system. The mathematical model of inter-turn short-circuit fault in the stationary coordinate system is analyzed to extract relevant short-circuit current i. f Fault characteristics.

7. The method for diagnosing the severity and phase of inter-turn short-circuit faults in a three-phase permanent magnet synchronous motor as described in claim 5, characterized in that... After an inter-turn short-circuit fault occurs in phase A winding, the voltage equation of the motor in the natural coordinate system is: The voltage equation can be transformed using the Clark transformation as follows: The voltage equations in the α-β plane after an inter-turn short-circuit fault in phase A are obtained as follows: Among them, u αfA u βfA The α-β plane voltage is the voltage after an inter-turn short-circuit fault occurs in phase A.

8. The method for diagnosing the severity and phase of inter-turn short-circuit faults in a three-phase permanent magnet synchronous motor as described in claim 1, characterized in that... The expression for the fault factor FI1 is shown below: Among them, (i α ,H(i α )) and (i β ,H(i β () represents a set of current signals orthogonal to each other along the α-axis and a set of current signals orthogonal to each other along the β-axis. f() is a function that processes the set of current signals orthogonal to each other along the α-β axes to obtain the residual in the set of signals, which is only related to the short-circuit current i. f Relevant characteristic variables; Get only the short-circuit current i f After considering the relevant characteristic variables, a sliding window integration is performed over one current cycle, and the average is taken to convert it into a DC quantity. This reduces the deviation in the residual and the interference during motor operation. In the formula, T... S This is one fundamental current cycle.

9. The method for diagnosing the severity and phase of inter-turn short-circuit faults in a three-phase permanent magnet synchronous motor as described in claim 8, characterized in that... When the fault factor FI1 is less than the set diagnostic threshold, it is determined that the motor has not experienced an inter-turn short circuit fault; when the fault factor FI1 is greater than the diagnostic threshold Th, it is determined that the motor has experienced an inter-turn short circuit fault, and the short circuit current i is quantitatively represented by the value of the fault factor FI1. f The amplitude is used to characterize the severity of inter-turn short circuit fault diagnosis in motors.

10. The method for diagnosing the severity and phase of inter-turn short-circuit faults in a three-phase permanent magnet synchronous motor as described in claim 9, characterized in that... Extracting the relevant short-circuit current i from the α-β plane voltage. f The additional components are used to distinguish the phase of the inter-turn short circuit fault based on the different distortion degrees of the α-axis voltage and β-axis voltage when the inter-turn short circuit fault occurs in different phases.

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