Method and device for detecting turn-to-turn short circuit fault of permanent magnet synchronous motor

Abstract

The invention relates to the technical field of permanent magnet synchronous motors, and discloses a permanent magnet synchronous motor turn-to-turn short circuit fault detection method and device, and the method comprises the steps: determining a discrete Fourier transform coefficient according to a carrier wave ratio; sampling the motor stator current for multiple times, and calculating a fundamental wave amplitude corresponding to the motor stator current by using discrete Fourier transform; and judging whether a turn-to-turn short circuit fault occurs or not according to the fundamental wave amplitude. According to the invention, fault detection is realized only through sampling and signal processing (for example, determining a DFT coefficient based on a carrier wave ratio and calculating a fundamental wave amplitude and an unbalance degree) on the stator current in an existing motor control system, and hardware equipment such as a resistance network and the like is not required to be additionally installed like a method based on a neutral-point voltage zero-sequence component, so that the hardware cost is prevented from being increased, and the fault detection efficiency is improved. And the system structure complexity and the subsequent maintenance difficulty are reduced, and the target of improving the reliability of the equipment is consistent.

Description

Technical Field

[0001] This invention relates to the field of permanent magnet synchronous motor technology, and specifically to a method and device for detecting inter-turn short circuit faults in permanent magnet synchronous motors. Background Technology

[0002] Permanent magnet synchronous motors (PMSMs) have been widely used in industrial production, electric vehicles, and many other fields due to their advantages of high power density, high efficiency, and high reliability. However, in actual operation, motors are prone to failure due to factors such as winding insulation aging, mechanical component wear, and permanent magnet demagnetization. Among these, stator winding inter-turn short circuit faults are the most concealed and the most dangerous. In the early stages of the fault, the short circuit current is weak, making detection difficult. If not handled in time, it will gradually develop into more serious faults such as phase-to-phase short circuits and short circuits to ground. This not only affects the normal operation of the motor and reduces system performance, but may also cause safety accidents and result in huge economic losses. Summary of the Invention

[0003] This invention provides a method and apparatus for detecting inter-turn short-circuit faults in permanent magnet synchronous motors, in order to solve the problem of how to detect inter-turn faults.

[0004] In a first aspect, the present invention provides a method for detecting inter-turn short-circuit faults in a permanent magnet synchronous motor, comprising: determining the coefficients of a discrete Fourier transform based on a carrier ratio; sampling the stator current of the motor multiple times and calculating the fundamental amplitude corresponding to the stator current using a discrete Fourier transform; and determining whether an inter-turn short-circuit fault has occurred based on the fundamental amplitude.

[0005] In one optional implementation, the process of determining the coefficients of the discrete Fourier transform based on the carrier ratio includes: dividing the horizontal and vertical coordinates of the complex plane into equal parts according to the carrier ratio, with each part being a carrier ratio value; using the horizontal coordinates corresponding to the unit element division points on the complex plane as the real part coefficients of the discrete Fourier transform; and using the vertical coordinates corresponding to the unit element division points as the imaginary part coefficients of the discrete Fourier transform.

[0006] In one optional implementation, the fundamental amplitude corresponding to the stator current of the motor is calculated using the discrete Fourier transform, and the specific calculation formula is as follows:

[0007] in, X [1] represents the fundamental frequency amplitude; n Indicates the first n One sampling point; N This indicates the total number of sampling points; j It is the imaginary unit.

[0008] In one alternative implementation, at any given time, the number of sampling points is numerically equal to the carrier ratio.

[0009] In one optional implementation, the process of determining whether an inter-turn short-circuit fault has occurred based on the fundamental amplitude includes: calculating the relative imbalance of the three-phase currents based on the fundamental amplitude of the three-phase currents; if the relative imbalance of the three-phase currents exceeds a preset threshold range, then an inter-turn short-circuit fault is determined to have occurred.

[0010] In one alternative implementation, the formula for calculating the relative imbalance of the three-phase current is:

[0011] in, FI The relative imbalance of the three-phase current; I A , I B , I C These represent the fundamental amplitude values ​​of the three-phase currents A, B, and C, respectively.

[0012] Secondly, the present invention provides a device for detecting inter-turn short-circuit faults in a permanent magnet synchronous motor. The device includes: determining the coefficients of a discrete Fourier transform based on a carrier ratio; sampling the stator current of the motor multiple times and calculating the fundamental amplitude corresponding to the stator current using a discrete Fourier transform; and determining whether an inter-turn short-circuit fault has occurred based on the fundamental amplitude.

[0013] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the inter-turn short-circuit fault detection method for permanent magnet synchronous motor described in the first aspect or any corresponding embodiment thereof.

[0014] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the inter-turn short-circuit fault detection method for a permanent magnet synchronous motor according to the first aspect or any corresponding embodiment described above.

[0015] Fifthly, the present invention provides a computer program product, including computer instructions, which are used to cause a computer to execute the inter-turn short-circuit fault detection method for permanent magnet synchronous motors described in the first aspect or any corresponding embodiment.

[0016] This invention achieves fault detection by sampling and signal processing of the stator current in the existing motor control system (such as determining the DFT coefficient based on the carrier ratio, calculating the fundamental amplitude and unbalance). Unlike methods based on the zero-sequence component of the midpoint voltage, it does not require additional hardware such as resistor networks. This avoids increased hardware costs and reduces the complexity of the system structure and the difficulty of subsequent maintenance, which is consistent with the goal of improving equipment reliability.

[0017] This invention divides the complex plane unit element equally according to the carrier ratio value, and uses the horizontal and vertical coordinates of the division points as the real and imaginary coefficients of the DFT, respectively. Combined with the matching rule that the number of sampling points equals the carrier ratio value, it ensures that the DFT calculation is accurately adapted to the current operating conditions (speed, bandwidth) of the motor. Furthermore, through a clear formula for calculating the fundamental amplitude, it can effectively extract accurate fundamental information from the high harmonic interference current of the high-speed motor, solving the problems of complex harmonic calculation and poor filter effect in traditional current harmonic analysis-based methods. Attached Figure Description

[0018] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 This is a schematic flowchart of the first method for detecting inter-turn short-circuit faults in a permanent magnet synchronous motor according to an embodiment of the present invention; Figure 2 This is a control block diagram of a permanent magnet synchronous motor according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the real coefficients and imaginary coefficients of the discrete Fourier transform according to an embodiment of the present invention. Figure 4 This is a schematic diagram of the stator three-phase current and short-circuit current under normal operating conditions and fault conditions according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the fundamental amplitude and unbalance of three-phase current under normal and fault conditions according to an embodiment of the present invention. Figure 6 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0022] According to an embodiment of the present invention, an embodiment of a method for detecting inter-turn short-circuit faults in a permanent magnet synchronous motor is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0023] Current methods for fault detection in permanent magnet synchronous motors have significant shortcomings, as detailed below: 1. Vibration analysis-based method: Faults are determined by measuring vibration signals, but it is easily affected by environmental noise and has high requirements for sensor installation location and accuracy, which is not conducive to its widespread application; 2. Methods based on the zero-sequence component of the midpoint voltage: These require additional hardware such as resistor networks, increasing system cost, complexity, and maintenance difficulty, which contradicts the goal of improving equipment reliability. 3. Stator winding temperature monitoring method: Although it can detect temperature anomalies caused by faults, the material temperature change is delayed. It takes a period of time for the temperature to change significantly after the fault occurs, resulting in poor real-time detection. 4. High-frequency signal injection method: Fault diagnosis requires impedance characteristics or residual components under high-frequency conditions, but the carrier ratio of high-speed motors is small, making high-frequency injection difficult, and high-frequency signals will introduce additional harmonic losses, reducing motor efficiency; 5. Traditional methods based on current harmonic analysis: Although they can detect faults to a certain extent, the calculation of harmonic currents is complicated, and the high-speed motor windings have small inductance and large leakage inductance, resulting in poor filter performance and difficulty in meeting the requirements of high-speed motor control systems. 6. Disturbance immunity / sliding mode observer-based method: It is necessary to calculate the back EMF of the motor to determine the fault and implement fault-tolerant control. However, the observer depends on accurate motor parameters. In high-speed PMSMs, the parameters change greatly in environments with high temperature rise and complex operating conditions, which affects the detection effect.

[0024] Based on this, this embodiment provides a method for detecting inter-turn short-circuit faults in permanent magnet synchronous motors. This method mainly addresses the problems of low winding inductance in high-speed permanent magnet synchronous motors and the susceptibility of existing detection methods to interference or reliance on additional hardware. It aims to achieve accurate and real-time detection of inter-turn short-circuit faults through simple and efficient signal processing and analysis logic, thus filling the gaps in fault detection under high-speed conditions in existing technologies. Figure 1 This is a flowchart of a method for detecting inter-turn short-circuit faults in a permanent magnet synchronous motor according to an embodiment of the present invention. The flowchart clearly presents the complete logical chain of fault detection from parameter preparation and data processing to fault judgment, intuitively demonstrating the execution order and interrelationships of each step. It provides clear and operable guidance for implementing the detection process in practical engineering applications. Figure 1 As shown, the process includes the following steps: Step S1: Determine the coefficients of the discrete Fourier transform based on the carrier ratio.

[0025] The carrier ratio is a key parameter connecting the real-time operating status of the motor (such as speed and control system bandwidth) with the accuracy of signal analysis. Its value directly determines the rules for the selection of the discrete Fourier transform coefficients. These coefficients are the core prerequisite for the accurate extraction of the fundamental current information. Only by determining the coefficients based on the carrier ratio that matches the current operating conditions can the effectiveness of the subsequent discrete Fourier transform calculation be ensured, laying the foundation for accurately obtaining the amplitude of the stator current fundamental wave. Therefore, this step is the parameter calibration link of the entire detection process, which determines the accuracy benchmark of all subsequent data processing.

[0026] Step S2: Sample the motor stator current multiple times and use Discrete Fourier Transform to calculate the fundamental amplitude corresponding to the motor stator current.

[0027] Stator current is the most direct electrical signal reflecting the operating state of the motor windings. When an inter-turn short-circuit fault occurs, the stator current of the faulty phase will change due to the superposition of the short-circuit current. Therefore, sampling the stator current multiple times can avoid the random errors of a single sampling and ensure that representative current data covering one fundamental cycle of the motor is obtained. The key to realizing fault feature extraction is to use the discrete Fourier transform coefficients determined in step S1 to convert the sampled time-domain current signal into the fundamental amplitude information in the frequency domain. The fundamental amplitude can intuitively reflect the symmetrical characteristics of the three-phase current, providing quantitative core data support for subsequent fault judgment.

[0028] Step S3: Determine whether an inter-turn short circuit fault has occurred based on the fundamental amplitude value.

[0029] Under normal operating conditions, the fundamental amplitude of the three-phase stator current of a permanent magnet synchronous motor exhibits good symmetry with minimal deviation. However, when an inter-turn short-circuit fault occurs, the fault phase current is superimposed with the short-circuit component, disrupting the balance of the three-phase fundamental amplitude and resulting in a significant asymmetry. Therefore, by analyzing the fundamental amplitude calculated in step S2 and combining it with preset fault judgment criteria (such as the three-phase amplitude imbalance threshold), it is possible to accurately identify whether an inter-turn short-circuit fault has occurred in the motor. This step is the output stage of the entire detection process, directly providing the motor control system with a judgment on whether a fault has occurred, so as to promptly activate subsequent protection or fault-tolerant measures.

[0030] In one optional implementation, the process of determining the coefficients of the discrete Fourier transform based on the carrier ratio includes: (1) Divide the horizontal and vertical coordinates on the complex plane according to the carrier ratio, and the number of equal parts is the carrier ratio value.

[0031] The carrier ratio here is a key operating parameter calculated by combining the real-time speed of the motor and the bandwidth frequency of the control system (rounded to the nearest integer if not an integer). Its value directly determines the resolution of the Discrete Fourier Transform (DFT) coefficients: dividing the horizontal and vertical coordinates of the complex plane equally according to the carrier ratio value is essentially to keep the number of DFT coefficients consistent with the number of sampling points of the stator current (the number of subsequent sampling points must be equal to the carrier ratio value), ensuring that the sampling period of the time-domain current signal is completely matched with the frequency interval of the frequency-domain coefficients, avoiding frequency domain aliasing or fundamental information extraction deviation caused by sampling-coefficient mismatch, and also providing a unified equal division benchmark for the subsequent determination of real and imaginary coefficients, ensuring the integrity of the coefficient sequence and the adaptability of the operating conditions.

[0032] (2) The abscissas corresponding to the unit element division points on the complex plane are used as the real part coefficients of the discrete Fourier transform.

[0033] The unit element (a circle with a modulus of 1) on the complex plane is the core carrier of DFT coefficients. The abscissa of its division point is essentially the cosine value of the angle corresponding to that point (i.e., cosθ, where θ is the angle between the division point and the positive direction of the real axis of the complex plane). Choosing the abscissa of the unit element's division point as the real part coefficients is, on the one hand, in accordance with the mathematical definition of DFT. The basis functions of DFT consist of cosine (real part) and sine (imaginary part) functions. The cosine term corresponds to the in-phase component of the signal and can capture the amplitude information in the fundamental current wave that is in phase with the reference phase. On the other hand, the modulus characteristic of the unit element can ensure the uniformity of the amplitude of the real part coefficients and will not introduce additional errors due to the scaling of the coefficients themselves, thereby ensuring the accuracy of the subsequent fundamental amplitude calculation. This is especially suitable for scenarios where high-speed motors have large harmonic interference and the fundamental signal is easily masked.

[0034] (3) The ordinates corresponding to the points where the unit element is divided are used as the imaginary part coefficients of the discrete Fourier transform.

[0035] Corresponding to the real part coefficients, the ordinate of the unit element division point is the sine value of the angle corresponding to that point (i.e., sinθ). The sine term corresponds to the quadrature component of the signal in the DFT, which can capture the amplitude information of the fundamental current wave that is 90° out of phase with the reference. Since the stator current is a typical AC signal, its characteristics need to be described by both amplitude and phase. The real part coefficients alone cannot fully reflect all the information of the fundamental wave. The introduction of the imaginary part coefficients can form a complete complex coefficient together with the real part coefficients, so that the DFT can process the in-phase component and the quadrature component of the current signal at the same time, thereby accurately calculating the actual amplitude of the fundamental wave (the modulus of the complex number). This step complements step (2) and together they construct a DFT coefficient system adapted to the operating conditions of high-speed motors, providing mathematical guarantee for the subsequent separation of the fundamental wave amplitude from harmonic interference.

[0036] For example, the control block diagram of a permanent magnet synchronous motor is as follows: Figure 2 As shown, this includes both power generation and motoring modes. The dashed line represents the fault monitoring module, which uses the stator three-phase current as input and the fault signal as output, participating in the control system's decision-making. Taking a controller bandwidth of 20kHz and a motor winding fundamental frequency of 1kHz as an example, with a carrier ratio of 20, the control system needs to record the 20 most recent stator current samples in memory. Simultaneously, the coefficients required for the Discrete Fourier Transform can be determined based on the carrier ratio. Figure 3 As shown.

[0037] The real part coefficients are the abscissas corresponding to the 20 equal divisions of the identity element on the complex plane, and the imaginary part coefficients are the ordinates corresponding to the 20 equal divisions of the identity element.

[0038] In one optional implementation, the fundamental amplitude corresponding to the stator current of the motor is calculated using the discrete Fourier transform, and the specific calculation formula is as follows:

[0039] in, X [1] represents the fundamental frequency amplitude; n Indicates the first n One sampling point; N This indicates the total number of sampling points; j It is the imaginary unit.

[0040] In one optional implementation, the process of determining whether an inter-turn short-circuit fault has occurred based on the fundamental amplitude includes: calculating the relative imbalance of the three-phase currents based on the fundamental amplitude of the three-phase currents; if the relative imbalance of the three-phase currents exceeds a preset threshold range, then an inter-turn short-circuit fault is determined to have occurred.

[0041] The core quantitative indicator for fault diagnosis is relative imbalance, rather than the simple absolute difference of the three-phase fundamental amplitude. The main reason is that the operating load of a high-speed permanent magnet synchronous motor changes with the operating conditions (such as load fluctuations in industrial equipment and acceleration and deceleration of electric vehicles), which causes the overall amplitude of the three-phase fundamental wave to increase or decrease synchronously. If the absolute difference is used, it may be misjudged as imbalance due to the overall increase in current caused by the increase in load, or minor faults may be missed due to the decrease in absolute difference caused by the decrease in load. The relative imbalance, calculated by taking the average of the three-phase fundamental amplitudes as a benchmark, measures the deviation of the maximum and minimum values ​​from the average. This effectively eliminates the interference of load fluctuations on the judgment results and accurately focuses on the core issue of whether the three-phase currents are symmetrical. Under normal operating conditions, the three-phase winding parameters are consistent, the magnetic field distribution is uniform, the difference in fundamental amplitude is minimal, and the relative imbalance is at an extremely low level. Once an inter-turn short circuit occurs, the fundamental amplitude of the faulty phase will deviate significantly from the other two phases due to the superposition of the short-circuit current, directly resulting in a significant increase in the relative imbalance. Therefore, this indicator can truly and stably reflect the health status of the motor windings and provide a reliable quantitative basis for subsequent fault judgment.

[0042] The preset threshold range is not subjectively set, but is derived from the calibration of the inherent error of the system under normal motor operating conditions. When the motor is fault-free, the relative imbalance of the three-phase current will have a normal fluctuation range due to the small imbalance of winding parameters caused by the manufacturing process (such as wire impedance deviation, small difference in the number of turns), the inherent sampling error of the current sensor (such as zero drift, accuracy deviation), and the slight influence of the system common-mode current. The preset threshold is the upper limit of this range. Its function is to clearly define the normal small imbalance and the significant imbalance caused by the fault: when the relative imbalance is within the threshold, it means that the current three-phase difference is a normal phenomenon caused by the inherent error of the system, and the motor is operating normally; when the relative imbalance exceeds the threshold, it means that the three-phase difference has exceeded the reasonable range of the inherent error of the system, and it must be caused by the abnormal current of the fault phase due to the inter-turn short circuit fault. Meanwhile, the judgment logic has strong real-time performance. Since the relative imbalance is calculated based on the fundamental amplitude updated every cycle, once a fault occurs, the breakthrough of the imbalance can be captured in just a few fundamental cycles, and the fault judgment result can be output quickly, so as to prevent the fault from developing into more serious problems such as phase-to-phase short circuit or short circuit to ground. This fully meets the core requirement of high-speed permanent magnet synchronous motors for rapid fault detection and response.

[0043] In one alternative implementation, the formula for calculating the relative imbalance of the three-phase current is:

[0044] in, FI The relative imbalance of the three-phase current; I A , IB , I C These represent the fundamental amplitude values ​​of the three-phase currents A, B, and C, respectively.

[0045] If the motor is under normal operating conditions, the unbalanced component introduced by factors such as asymmetry of system parameters or common-mode current is small, and the calculated result of relative unbalance, FI, is small. If an inter-turn short-circuit fault occurs, the phase corresponding to the fault will be superimposed with the fault current component, and the calculated result of the corresponding relative unbalanced component, FI, will increase. The fault state can be distinguished based on the threshold.

[0046] Figure 4 This diagram illustrates the stator three-phase current and short-circuit current under normal and fault conditions. An inter-turn short-circuit fault will cause the three-phase currents to become unbalanced. Figure 4 The image above shows the stator current waveforms before and after an inter-turn short-circuit fault. Figure 4 The figure below shows the short-circuit current waveforms before and after the inter-turn short-circuit fault. The system introduces an inter-turn short-circuit fault at 10ms. Before the inter-turn short-circuit fault, the currents of the three phases A, B, and C are symmetrical and their amplitudes are approximately equal, and the short-circuit current waveform is zero. After the inter-turn short circuit, the currents of the three phases all increase to different degrees, with the increase in the current of phase A being higher than that of phases B and C.

[0047] Figure 5 The diagram shows the fundamental amplitude and unbalance of the three-phase current under normal and fault conditions. The fundamental amplitude of the three-phase current is calculated according to equation (1). Figure 5 The figure above shows the calculated fundamental amplitude values ​​of the three-phase currents under normal and fault conditions. Before the inter-turn short circuit occurs, the fundamental amplitude values ​​of the three-phase currents A, B, and C are approximately equal. After the inter-turn short circuit occurs, the increase in the fundamental amplitude value of the A-phase current is significantly higher than that of the B and C-phase currents. The unbalance of the three-phase currents is calculated according to equation (2). Figure 5 The above figure shows the calculation results of the three-phase current imbalance under normal and fault conditions. Before the short circuit occurs, the three-phase current imbalance is small. After the inter-turn short circuit occurs, the three-phase current imbalance increases. A fault threshold is set to distinguish between the inter-turn short circuit state and the normal state.

[0048] This embodiment also provides a device for detecting inter-turn short-circuit faults in a permanent magnet synchronous motor. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0049] This embodiment provides a device for detecting inter-turn short-circuit faults in a permanent magnet synchronous motor, the device comprising: The coefficients of the discrete Fourier transform are determined based on the carrier ratio; The stator current of the motor is sampled multiple times, and the fundamental amplitude corresponding to the stator current is calculated using discrete Fourier transform. Based on the fundamental amplitude, determine whether an inter-turn short circuit fault has occurred.

[0050] The inter-turn short-circuit fault detection device for permanent magnet synchronous motors provided in this embodiment of the invention can execute the inter-turn short-circuit fault detection method for permanent magnet synchronous motors provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the above modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0051] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0052] The following is a detailed reference. Figure 6 The diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 001, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 002 or a program loaded from memory 008 into random access memory (RAM) 003. The RAM 003 also stores various programs and data required for the operation of the electronic device. The processor 001, ROM 002, and RAM 003 are interconnected via bus 004. An input / output (I / O) interface 005 is also connected to bus 004.

[0053] Typically, the following devices can be connected to I / O interface 005: input devices 006 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 007 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 008 including, for example, magnetic tapes, hard disks, etc.; and communication devices 009. Communication device 009 allows electronic devices to exchange data via wireless or wired communication with other devices. Although Figure 6 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0054] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 009, or installed from memory 008, or installed from ROM 002. When the computer program is executed by processor 001, it performs the functions defined in the permanent magnet synchronous motor inter-turn short-circuit fault detection method of the present invention.

[0055] Figure 6 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0056] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the inter-turn short-circuit fault detection method for permanent magnet synchronous motors shown in the above embodiments is implemented.

[0057] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0058] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for detecting inter-turn short-circuit faults in a permanent magnet synchronous motor, characterized in that, include: The coefficients of the discrete Fourier transform are determined based on the carrier ratio; The stator current of the motor is sampled multiple times, and the fundamental amplitude corresponding to the stator current is calculated using discrete Fourier transform. Based on the fundamental amplitude, determine whether an inter-turn short circuit fault has occurred.

2. The method for detecting inter-turn short-circuit faults in a permanent magnet synchronous motor according to claim 1, characterized in that, The process of determining the coefficients of the discrete Fourier transform based on the carrier ratio includes: The carrier ratio is divided into equal parts on the horizontal and vertical axes of the complex plane, and the number of equal parts is the carrier ratio value. The abscissas corresponding to the points where the unit element is divided equally on the complex plane are taken as the real part coefficients of the discrete Fourier transform. The ordinates corresponding to the points where the unit element is divided are used as the imaginary coefficients of the discrete Fourier transform.

3. The method for detecting inter-turn short-circuit faults in a permanent magnet synchronous motor according to claim 1, characterized in that, The fundamental amplitude of the motor stator current is calculated using the Discrete Fourier Transform (DFT). The specific calculation formula is as follows: in, X [1] represents the fundamental frequency amplitude; n Indicates the first n One sampling point; N This indicates the total number of sampling points; j It is the imaginary unit.

4. The method for detecting inter-turn short-circuit faults in a permanent magnet synchronous motor according to claim 1, characterized in that, At any given time, the number of sampling points is numerically equal to the carrier ratio.

5. The method for detecting inter-turn short-circuit faults in a permanent magnet synchronous motor according to claim 1, characterized in that, The process of determining whether an inter-turn short-circuit fault has occurred based on the fundamental amplitude includes: Calculate the relative unbalance of the three-phase currents based on the fundamental amplitude of the three-phase currents; If the relative imbalance of the three-phase current exceeds the preset threshold range, an inter-turn short circuit fault is determined to have occurred.

6. The method for detecting inter-turn short-circuit faults in a permanent magnet synchronous motor according to claim 5, characterized in that, The formula for calculating the relative unbalance of three-phase current is: in, FI The relative imbalance of the three-phase current; I A , I B , I C These represent the fundamental amplitude values ​​of the three-phase currents A, B, and C, respectively.

7. A device for detecting inter-turn short-circuit faults in a permanent magnet synchronous motor, characterized in that, The device includes: The coefficients of the discrete Fourier transform are determined based on the carrier ratio; The stator current of the motor is sampled multiple times, and the fundamental amplitude corresponding to the stator current is calculated using discrete Fourier transform. Based on the fundamental amplitude, determine whether an inter-turn short circuit fault has occurred.

8. An electronic device, characterized in that, include: The method includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the inter-turn short-circuit fault detection method for permanent magnet synchronous motors as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the inter-turn short-circuit fault detection method for permanent magnet synchronous motors according to any one of claims 1 to 6.

10. A computer program product, characterized in that, The method includes computer instructions for causing a computer to execute the inter-turn short-circuit fault detection method for permanent magnet synchronous motors as described in any one of claims 1 to 6.

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