Method and system for online monitoring of traction motor faults based on leakage current impedance characteristics

Abstract

The present application relates to the technical field of motor state monitoring, in particular to a traction motor fault online monitoring method and system based on leakage current impedance characteristics. The present application provides a traction motor fault online monitoring method based on leakage current impedance characteristics, the method comprising: collecting three-phase-to-ground voltage signals and three-phase leakage current signals of the input end of the traction motor during operation; performing Fourier transform processing on the three-phase-to-ground voltage signals and the three-phase leakage current signals to obtain voltage spectrum and current spectrum respectively; based on the voltage spectrum and the current spectrum, calculating the impedance characteristics of the traction motor within a preset characteristic frequency band; comparing the calculated impedance characteristics with the preset healthy motor impedance characteristics, and judging the stator insulation degradation fault or bearing fault according to whether the deviation of the comparison exceeds the corresponding threshold. The method provided by the present application improves the safety and operation and maintenance level of the traction motor.

Description

Technical Field

[0001] This invention relates to the field of motor condition monitoring technology, specifically to a method and system for online monitoring of traction motor faults based on leakage current impedance characteristics. Background Technology

[0002] In industrial production, high-speed rail, ship propulsion, and new energy vehicles, traction motors are core drive equipment, and their operational reliability directly affects system safety and economy. However, motor failures (such as stator insulation deterioration, bearing damage, and rotor bar breakage) can easily lead to unexpected downtime and cause significant economic losses. Among these, stator insulation failures and bearing failures are particularly common, both of which are closely related to the application of power electronic devices.

[0003] With the development of power semiconductor devices, high-frequency PWM inverters have improved control performance, but the common-mode voltage (du / dt) generated during the switching process will form leakage current through the distributed capacitance of the motor to ground. This current leads to increased electrical stress on the insulation material, increased dielectric loss, and accelerated aging of the stator insulation; at the same time, leakage current flowing through the bearings will cause electrolytic corrosion, shorten the bearing life, and affect the safe and stable operation of the motor.

[0004] Currently, insulation and bearing fault diagnosis mainly relies on offline disassembly and repair, which consumes a lot of manpower and time, is inefficient, and poses safety risks. Insulation degradation is a slow process, and there are no effective means for early diagnosis; bearing monitoring mostly relies on vibration sensors, which requires additional equipment installation, resulting in high equipment and construction costs. Therefore, a systematic online motor monitoring solution has not yet been developed.

[0005] Given the difficulty in achieving low-cost, multi-fault synchronous online monitoring in existing technologies, there is an urgent need for an online monitoring method to solve the above problems. Summary of the Invention

[0006] The following provides a brief overview of one or more aspects to offer a basic understanding of them. This overview is not an exhaustive summary of all conceived aspects, nor is it intended to identify key or decisive elements of all aspects, nor to define the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form to prepare for the more detailed descriptions that follow.

[0007] The purpose of this invention is to provide a method and system for online monitoring of traction motor faults based on leakage current impedance characteristics, which solves the technical problems of existing technologies that cannot simultaneously and effectively monitor the stator insulation and bearing status of motors online, and are characterized by high cost and low efficiency.

[0008] The technical solution adopted by this invention to solve the above-mentioned technical problems is to provide an online fault monitoring method for traction motors based on leakage current impedance characteristics, the method comprising:

[0009] Collect the three-phase voltage signal to ground and the three-phase leakage current signal at the input terminal of the traction motor during operation;

[0010] The three-phase ground voltage signal and the three-phase leakage current signal are subjected to Fourier transform processing to obtain the voltage spectrum and the current spectrum, respectively.

[0011] Based on the voltage and current spectra, calculate the impedance characteristics of the traction motor in the preset characteristic frequency band;

[0012] The calculated impedance characteristics are compared with the preset healthy motor impedance characteristics. Based on whether the comparison deviation exceeds the corresponding threshold, the stator insulation deterioration fault or bearing fault is determined.

[0013] In one embodiment, calculating the impedance characteristics of the traction motor within a preset characteristic frequency band includes:

[0014] Calculate the common-mode voltage based on the three-phase-to-ground voltage;

[0015] Within the preset characteristic frequency band, the common-mode impedance is calculated based on the spectral components of the common-mode voltage and the leakage current.

[0016] In one embodiment, the preset characteristic frequency band includes a first frequency band and a second frequency band for stator insulation degradation detection, and a third frequency band for bearing condition abnormality detection.

[0017] In one embodiment, determining the stator insulation degradation fault includes:

[0018] Extract the impedance characteristics calculated in the first and second frequency bands;

[0019] The extracted impedance characteristics are compared with the impedance characteristics of a healthy motor in the first and second frequency bands to calculate the first deviation value.

[0020] When the first deviation value exceeds the first set threshold, a stator insulation deterioration fault is determined to have occurred.

[0021] In one embodiment, determining the bearing fault includes:

[0022] Extract the impedance characteristics calculated within the third frequency band;

[0023] The extracted impedance characteristics are compared with the impedance characteristics of a healthy motor in the third frequency band to calculate the second deviation value.

[0024] When the second deviation value exceeds the second set threshold, it is determined that an abnormal bearing condition fault has occurred.

[0025] In one embodiment, before performing Fourier transform processing on the three-phase ground voltage signal and the three-phase leakage current signal to obtain the voltage spectrum and current spectrum respectively, the method further includes:

[0026] Obtain the real-time operating parameters of the motor;

[0027] Based on the operating condition parameters, the three-phase-to-ground voltage signal and the three-phase leakage current signal are filtered and / or compensated to obtain a stable three-phase-to-ground voltage signal and leakage current signal.

[0028] The operating parameters include one or more of speed, torque, and temperature.

[0029] To achieve the above objectives, the present invention also provides an online fault monitoring system for traction motors based on leakage current impedance characteristics, for implementing the method described in any of the above claims, wherein the system includes at least: a motor-side sensor group and a signal processing module;

[0030] The motor-side sensor group includes a leakage current sensor and a voltage sensor. The leakage current sensor is used to collect the leakage current signal at the three-phase input terminal of the motor, and the voltage sensor is used to collect the three-phase voltage signal to ground.

[0031] The signal processing module includes a signal acquisition unit and a signal analysis unit. The signal acquisition unit is used to receive three-phase ground voltage signals and three-phase leakage current signals from the motor-side sensor group.

[0032] The signal analysis unit includes a data processing subunit, which performs Fourier transform on the three-phase ground voltage signal and the three-phase leakage current signal to obtain voltage spectrum and current spectrum, respectively; calculates the impedance characteristics of the traction motor in a preset characteristic frequency band based on the voltage spectrum and current spectrum; compares the calculated impedance characteristics with the preset healthy motor impedance characteristics, and determines stator insulation deterioration fault or bearing fault based on whether the comparison deviation exceeds the corresponding threshold.

[0033] In one embodiment, the signal analysis unit further includes a condition parameter processing subunit;

[0034] The operating condition parameter processing subunit is used to process the real-time operating condition parameters of the motor from the control unit;

[0035] Based on the operating condition parameters, the three-phase-to-ground voltage signal and the three-phase leakage current signal are filtered and / or compensated to obtain a stable three-phase-to-ground voltage signal and leakage current signal.

[0036] In one embodiment, the control unit is connected to the converter and is responsible for motor control, sending operating condition parameters to the signal analysis unit.

[0037] In one embodiment, the system further includes a wireless transmission device and a ground display platform;

[0038] The wireless transmission device receives the warning results and characteristic parameters output by the signal processing module;

[0039] The ground display platform receives data via a wireless network of a wireless transmission device, which is used to remotely display the motor status in real time and push early warning information.

[0040] The present invention provides an online fault monitoring method for traction motors based on leakage current impedance characteristics. By synchronously collecting leakage current and phase voltage signals at the motor terminals, and calculating their impedance characteristics within a preset fault characteristic frequency band after Fourier transform, a working condition compensation mechanism is introduced to eliminate the influence of operating state fluctuations. Finally, the processed impedance characteristics are compared with a healthy motor benchmark in a multimodal manner, thereby improving the safety and maintenance level of traction motor operation. Attached Figure Description

[0041] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein:

[0042] Figure 1 A flowchart of an online traction motor fault monitoring method according to an embodiment of the present invention is disclosed;

[0043] Figure 2 A first impedance characteristic curve according to an embodiment of the present invention is disclosed;

[0044] Figure 3 A second impedance characteristic curve according to an embodiment of the present invention is disclosed;

[0045] Figure 4 A diagram of an online traction motor fault monitoring system according to an embodiment of the present invention is disclosed. Detailed Implementation

[0046] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0047] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the invention is not limited to the specific embodiments disclosed below.

[0048] As indicated in this invention and the claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0049] In traction motor systems, complex impedance networks dynamically change with equipment conditions. Weakened motor insulation affects parasitic capacitances between phases and ground, between phases, and between windings. Deterioration in the main insulation or inter-turn insulation leads to changes in parameters such as capacitance and impedance in the motor's equivalent circuit. Specifically, insulation material degradation alters the equivalent capacitance, while bearing galvanic corrosion or wear affects bearing resistance and oil film capacitance. When the inverter's power semiconductors rapidly switch on and off, the resulting high-frequency common-mode voltage acts on the equivalent parameter circuit of the motor system, generating characteristic leakage current.

[0050] Figure 1 A flowchart of an online fault monitoring method for traction motors according to an embodiment of the present invention is disclosed, as follows: Figure 1 As shown, this invention provides an online fault monitoring method for traction motors based on leakage current impedance characteristics, the method comprising:

[0051] Collect the three-phase-to-ground voltage signal and leakage current signal at the three-phase input terminal of the traction motor during operation;

[0052] The three-phase ground voltage signal and leakage current signal are processed by Fast Fourier Transform to obtain the voltage spectrum and current spectrum, respectively.

[0053] Based on the voltage and current spectra, calculate the impedance characteristics of the traction motor in the preset characteristic frequency band;

[0054] The calculated impedance characteristics are compared with the preset healthy motor impedance characteristics. Based on whether the comparison deviation exceeds the corresponding threshold, the stator insulation deterioration fault or bearing fault is determined.

[0055] This invention extracts impedance characteristics of different modes by real-time acquisition of leakage current signals and three-phase-to-ground voltages at the motor input terminals, combined with Fast Fourier Transform (FFT) for spectral analysis. Since stator insulation damage and bearing failures exhibit unique spectral characteristics, this method effectively enables comprehensive monitoring of stator insulation and bearing conditions, as well as early fault warning, reducing safety hazards and labor costs caused by motor failures.

[0056] The steps of the present invention will be described in detail below. It should be understood that, within the scope of the present invention, the above-described technical features of the present invention and the technical features specifically described below (such as in the embodiments) can be combined with each other and related to each other to form a preferred technical solution.

[0057] Step S1: Collect the three-phase-to-ground voltage signal and leakage current signal of the three-phase input terminal of the traction motor during operation.

[0058] In this step, when the stator insulation of the motor deteriorates or the bearing is damaged (electrolytic corrosion and wear, etc.), a current sensor is installed at the input terminal of the traction motor to collect the leakage current of the three phases A, B, and C respectively, which is used to calculate the impedance characteristics of the traction motor.

[0059] A voltage sensor is used to collect three-phase voltage signals to ground and extract the common-mode voltage to calculate the impedance characteristics of the traction motor. The voltage sensor must meet the three-phase voltage acquisition range requirements to ensure the reliability of the acquired voltage signals.

[0060] Step S2: Perform Fourier transform on the three-phase ground voltage signal and the three-phase leakage current signal to obtain the voltage spectrum and current spectrum, respectively.

[0061] In one embodiment, the method further includes:

[0062] Obtain the real-time operating parameters of the motor;

[0063] Based on operating condition parameters, the three-phase-to-ground voltage signal and the three-phase leakage current signal are filtered and / or compensated to obtain stable three-phase-to-ground voltage signal and leakage current signal. The operating condition parameters include one or more of speed, torque and temperature.

[0064] The impedance characteristics of a motor naturally change under different speeds, loads, and temperatures. Without compensation, the characteristics extracted from this normal operating condition fluctuation data may be incorrectly identified as fault features, leading to false alarms.

[0065] In this embodiment, during the actual operation of the motor, the collected sensor data (three-phase ground voltage signal and leakage current signal) or the features calculated therefrom are preprocessed by acquiring the real-time operating parameters of the motor (such as speed, torque, temperature, etc.) to eliminate or reduce the interference caused by changes in operating conditions.

[0066] By filtering and / or compensating for the three-phase ground voltage signal and the three-phase leakage current signal based on the operating condition parameters, the influence of non-fault factors can be isolated, so that the impedance characteristics extracted subsequently can truly and consistently reflect the health status of the insulation or bearings. This significantly improves the accuracy and reliability of fault early warning and reduces the probability of missed and false alarms.

[0067] Preferably, the present invention employs Fast Fourier Transform (FFT), an efficient algorithm of Discrete Fourier Transform (DFT), which is the basis of many digital signal processing methods.

[0068] Step S3: Based on the voltage spectrum and current spectrum, calculate the impedance characteristics of the traction motor in the preset characteristic frequency band.

[0069] In one embodiment, the preset characteristic frequency band includes a first frequency band and a second frequency band for stator insulation degradation detection, and a third frequency band for bearing condition abnormality detection.

[0070] The weakening of motor insulation affects the parasitic capacitance between phase and ground, between phases, and between windings. If the main insulation or inter-turn insulation of the motor deteriorates, it will cause changes in parameters such as capacitance and impedance in the equivalent circuit of the motor, thereby affecting the impedance characteristics of the motor. Offline frequency sweep analysis using an impedance analyzer on normal prototypes and simulated insulation degradation patterns can obtain the modal range affected by the motor insulation degradation. Selecting the first frequency band [f1, f2] and the second frequency band [f3, f4] where the impedance curves show significant differences, such as... Figure 2 As shown, the insulation detection modal diagram shows that the impedance spectrum feature extraction in the first frequency band [f1,f2] and the second frequency band [f3,f4] can identify motor insulation degradation problems.

[0071] The calculation of the impedance characteristics of the traction motor in the preset characteristic frequency band includes:

[0072] Calculate the common-mode voltage based on the three-phase ground voltage. The common-mode voltage for:

[0073] (1);

[0074] Within a preset characteristic frequency band, based on the spectral components of the common-mode voltage and the spectral components of leakage current Calculate this frequency point impedance The impedance for:

[0075] (2);

[0076] in, It is the A-phase voltage of the three-phase ground voltage. It is the B-phase voltage of the three-phase ground voltage. .

[0077] Step S4: Compare the calculated impedance characteristics with the preset healthy motor impedance characteristics, and determine the stator insulation deterioration fault based on whether the comparison deviation exceeds the corresponding threshold.

[0078] In one embodiment, determining the stator insulation degradation fault includes:

[0079] Extract the impedance characteristics calculated within the first frequency band [f1, f2] and the second frequency band [f3, f4].

[0080] The extracted impedance characteristics are compared with the impedance characteristics of a healthy motor in the first and second frequency bands to calculate the first deviation value. Specifically, the impedance characteristics within the aforementioned frequency bands are integrated to obtain the characteristic value. Normal motor impedance characteristics The impedance characteristics calculated in the first frequency band [f1, f2] and the second frequency band [f3, f4] are compared and calculated.

[0081] Among them, the features of healthy motors are features extracted based on normal motor operation data, which are used to compare with the features of faulty motors.

[0082] When the first deviation value exceeds the first set threshold, a stator insulation deterioration fault is determined to have occurred. The first set threshold can be x%, that is, the insulation deterioration fault is identified after the alarm threshold x% is reached.

[0083] In this embodiment, a voltage sensor is used to collect the three-phase voltage to ground of the motor, a leakage current sensor is used to measure the common-mode current of the motor, and the voltage and current spectra are extracted based on the FFT method to calculate the impedance characteristics of the preset frequency band, thereby realizing the assessment and location of the insulation degradation state of the motor.

[0084] Damage to the traction motor bearings can also cause changes in the motor impedance, resulting in deviations in the high-frequency modal impedance characteristic curve, such as... Figure 3 As shown, the modal diagram corresponding to the bearing abnormality is in [ , The impedance characteristic curves within the frequency band show significant deviations.

[0085] In one embodiment, determining the bearing fault includes:

[0086] Extracted in the third frequency band [ , The impedance characteristics calculated within [ ], [ , This refers to the lower and upper limits of the frequency band from which the bearing impedance characteristics are extracted.

[0087] The extracted impedance characteristics are compared with the impedance characteristics of a healthy motor in the third frequency band to calculate the second deviation value.

[0088] When the second deviation value exceeds the second set threshold, it is determined that an abnormal bearing condition fault has occurred.

[0089] In this embodiment, FFT analysis is performed on the three-phase voltage and leakage current data to extract [ , The impedance is calculated based on the leakage current characteristics and common-mode voltage characteristics within the frequency band. The impedance calculation methods are shown in equations (1) and (2). Based on the calculated [ , The impedance characteristics of the motor are compared with those of a healthy motor. When the deviation exceeds a second set threshold, the motor bearing condition is identified as abnormal. The second set threshold can be... .

[0090] It should be noted that the settings for x and y in this invention are based on the comparison of test data of normal motors and faulty motors to extract alarm thresholds.

[0091] This invention synchronously collects leakage current and phase voltage signals from the motor terminals, calculates their impedance characteristics within a preset fault characteristic frequency band after FFT transformation, and introduces a working condition compensation mechanism to eliminate the influence of operating state fluctuations. Finally, the processed impedance characteristics are compared with a healthy motor benchmark in a multimodal manner to achieve accurate diagnosis and early warning, which greatly improves the safety and maintenance of traction motor operation.

[0092] The method provided by this invention is to diagnose through deviation comparison, but it can also be replaced by methods such as neural networks and weighted averages.

[0093] To achieve the above objectives, the present invention also provides an online fault monitoring system for traction motors based on leakage current impedance characteristics, used to implement the online fault monitoring method for traction motors based on leakage current impedance characteristics described above. Figure 4 A diagram of an online traction motor fault monitoring system according to an embodiment of the present invention is disclosed, such as... Figure 4 As shown, the online fault monitoring system for traction motors based on leakage current impedance characteristics may include: a sensor group on the motor 100 side and a signal processing module 200.

[0094] The sensor group on the motor 100 side may include a leakage current sensor 101 and a voltage sensor 102. The leakage current sensor 101 is used to collect the leakage current signal at the three-phase input terminal of the motor, and the voltage sensor 102 is used to collect the three-phase voltage signal to ground.

[0095] The signal processing module 200 includes a signal acquisition unit 201 and a signal analysis unit 202. The signal acquisition unit 201 is used to receive three-phase ground voltage signals and three-phase leakage current signals from the sensor group.

[0096] The signal analysis unit 202 includes a data processing subunit 2021, which performs Fourier transform processing on the three-phase ground voltage signal and the three-phase leakage current signal to obtain the voltage spectrum and current spectrum, respectively; based on the voltage spectrum and current spectrum, it calculates the impedance characteristics of the traction motor in a preset characteristic frequency band; it compares the calculated impedance characteristics with the preset healthy motor impedance characteristics, and determines whether the stator insulation deterioration fault or bearing fault is determined according to whether the comparison deviation exceeds the corresponding threshold. The data processing subunit 2021 is the algorithm model module, which extracts the impedance characteristic features.

[0097] In one embodiment, the signal analysis unit 202 further includes a working condition parameter processing subunit 2022, which is used to process the real-time operating condition parameters of the motor from the control unit;

[0098] Based on the operating condition parameters, the three-phase-to-ground voltage signal and the three-phase leakage current signal are filtered and / or compensated to obtain a stable three-phase-to-ground voltage signal and leakage current signal.

[0099] The control unit 300 is connected to the inverter 103 and is responsible for motor control. At the same time, it sends the operating condition parameters to the signal analysis unit 202. The control unit controls the motor by controlling the inverter switch. In order to identify special operating conditions judged by the model, the control unit 300 transmits control signals such as motor speed and torque to the operating condition parameter processing subunit 2022 of the signal analysis unit 202 for processing by establishing communication.

[0100] The operating condition parameter processing subunit 2022 processes and filters data based on signals such as speed, torque, and temperature in the control signals, and extracts stable operating conditions without significant fluctuations for model analysis.

[0101] In one embodiment, the device further includes a wireless transmission device 400 and a ground display platform 500;

[0102] The wireless transmission device receives the warning results and characteristic parameters output by the signal processing module 200, and transmits the warning results and characteristic parameters obtained by the signal processing module 200 to the ground platform for real-time display via wireless transmission.

[0103] The ground display platform receives data via wireless network to remotely display the motor status in real time and push early warning information, prompting users to check the motor's real-time status and carry out maintenance work.

[0104] This invention provides a method and system for online monitoring of traction motor faults based on leakage current impedance characteristics. The method calculates the motor impedance characteristics based on online motor data, and extracts impedance characteristics of insulation degradation and bearing faults based on multi-modal impedance feature analysis and compares them with the characteristics of healthy motors. This not only enables online early warning of the motor, but also enables comprehensive diagnosis of bearings and insulation. The method performs comprehensive comparative analysis of impedance characteristics of healthy and faulty motors in multiple modes affected by the fault, thereby reducing safety hazards and labor costs caused by motor faults.

[0105] The systems and methods described in this invention can correspond to and be referenced from each other in terms of features, and the parts not described in detail can be cited from each other without further elaboration.

[0106] The basic concepts have been described above. It is clear that the above disclosure is merely illustrative and does not constitute a limitation of the invention. Although not explicitly stated herein, various modifications, improvements, and corrections may be made to the invention by those skilled in the art. Such modifications, improvements, and corrections are suggested in this invention and therefore remain within the spirit and scope of the exemplary embodiments of the invention.

[0107] Meanwhile, this invention uses specific terms to describe embodiments of the invention. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic related to at least one embodiment of the invention. Therefore, it should be emphasized and noted that "an embodiment," "one embodiment," or "an alternative embodiment" mentioned twice or more in different locations in this specification do not necessarily refer to the same embodiment. Furthermore, certain features, structures, or characteristics in one or more embodiments of the invention can be appropriately combined.

[0108] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of range in some embodiments of the invention are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

Claims

1. A method for online fault monitoring of traction motors based on leakage current impedance characteristics, characterized in that, The method includes: Collect the three-phase voltage signal to ground and the three-phase leakage current signal at the input terminal of the traction motor during operation; The three-phase ground voltage signal and the three-phase leakage current signal are subjected to Fourier transform processing to obtain the voltage spectrum and the current spectrum, respectively. Based on the voltage and current spectra, calculate the impedance characteristics of the traction motor in the preset characteristic frequency band; The calculated impedance characteristics are compared with the preset healthy motor impedance characteristics. Based on whether the comparison deviation exceeds the corresponding threshold, the stator insulation deterioration fault or bearing fault is determined. The preset characteristic frequency bands include a first frequency band and a second frequency band for stator insulation degradation detection, and a third frequency band for bearing condition abnormality detection.

2. The online fault monitoring method for traction motors based on leakage current impedance characteristics according to claim 1, characterized in that, The calculation of the impedance characteristics of the traction motor within the preset characteristic frequency band includes: Calculate the common-mode voltage based on the three-phase-to-ground voltage; Within the preset characteristic frequency band, the common-mode impedance is calculated based on the spectral components of the common-mode voltage and the leakage current.

3. The online fault monitoring method for traction motors based on leakage current impedance characteristics according to claim 1, characterized in that, The determination of stator insulation degradation faults includes: Extract the impedance characteristics calculated in the first and second frequency bands; The extracted impedance characteristics are compared with the impedance characteristics of a healthy motor in the first and second frequency bands to calculate the first deviation value. When the first deviation value exceeds the first set threshold, a stator insulation deterioration fault is determined to have occurred.

4. The online fault monitoring method for traction motors based on leakage current impedance characteristics according to claim 1, characterized in that, Determining the bearing fault includes: Extract the impedance characteristics calculated within the third frequency band; The extracted impedance characteristics are compared with the impedance characteristics of a healthy motor in the third frequency band to calculate the second deviation value. When the second deviation value exceeds the second set threshold, it is determined that an abnormal bearing condition fault has occurred.

5. The online fault monitoring method for traction motors based on leakage current impedance characteristics according to claim 1, characterized in that, Before performing Fourier transform processing on the three-phase ground voltage signal and the three-phase leakage current signal to obtain the voltage spectrum and current spectrum respectively, the following steps are included: Obtain the real-time operating parameters of the motor; Based on the operating condition parameters, the three-phase ground voltage signal and the three-phase leakage current signal are filtered and / or compensated to obtain a stable three-phase ground voltage signal and leakage current signal. The operating parameters include one or more of speed, torque, and temperature.

6. An online fault monitoring system for traction motors based on leakage current impedance characteristics, used to implement the method as described in any one of claims 1 to 5, characterized in that, The system includes at least: a motor-side sensor group and a signal processing module; The motor-side sensor group includes a leakage current sensor and a voltage sensor. The leakage current sensor is used to collect the leakage current signal at the three-phase input terminal of the motor, and the voltage sensor is used to collect the three-phase voltage signal to ground. The signal processing module includes a signal acquisition unit and a signal analysis unit. The signal acquisition unit is used to receive three-phase ground voltage signals and three-phase leakage current signals from the motor-side sensor group. The signal analysis unit includes a data processing subunit, which performs Fourier transform on the three-phase ground voltage signal and the three-phase leakage current signal to obtain voltage spectrum and current spectrum, respectively; calculates the impedance characteristics of the traction motor in a preset characteristic frequency band based on the voltage spectrum and current spectrum; compares the calculated impedance characteristics with the preset healthy motor impedance characteristics, and determines stator insulation deterioration fault or bearing fault based on whether the comparison deviation exceeds the corresponding threshold.

7. The traction motor fault online monitoring system based on leakage current impedance characteristics according to claim 6, characterized in that, The signal analysis unit also includes a condition parameter processing subunit; The operating condition parameter processing subunit is used to process the real-time operating condition parameters of the motor from the control unit; Based on the operating condition parameters, the three-phase ground voltage signal and the three-phase leakage current signal are filtered and / or compensated to obtain a stable three-phase ground voltage signal and leakage current signal. The operating parameters include one or more of speed, torque, and temperature.

8. The traction motor fault online monitoring system based on leakage current impedance characteristics according to claim 7, characterized in that, The control unit is connected to the converter and is responsible for motor control, sending operating parameters to the signal analysis unit.

9. The traction motor fault online monitoring system based on leakage current impedance characteristics according to claim 8, characterized in that, The system also includes a wireless transmission device and a ground display platform; The wireless transmission device receives the warning results and characteristic parameters output by the signal processing module; The ground display platform receives data via a wireless network of a wireless transmission device, which is used to remotely display the motor status in real time and push early warning information.

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