Rotor turn-to-turn short circuit monitoring system and method based on tunnel magnetoresistive sensor array

Abstract

The invention provides a rotor turn-to-turn short circuit monitoring system and method based on a tunnel magnetoresistive sensor array, and the system achieves the axial positioning of a rotor turn-to-turn short circuit fault point through the axial arrangement of a plurality of magnetic field sensors at the opposite positions of the same rotor groove, and comparing the differences of the magnetic field waveforms corresponding to the magnetic field sensors. The fault positioning precision is greatly improved, and key guidance information is provided for maintenance. The array arrangement of the magnetic field sensors provides magnetic field sampling points with high spatial resolution, and a plurality of fault points in a short distance can be distinguished. In addition, the magnetic field intensity is directly measured instead of the change rate, signals are more stable, and the influence of rotating speed fluctuation is small.

Description

Technical Field

[0001] This invention relates to the field of condition monitoring and fault diagnosis technology for large rotating electric machines, specifically to a rotor inter-turn short circuit monitoring system and method based on a tunnel magnetoresistive sensor array. Background Technology

[0002] Rotor winding inter-turn short circuits are a frequent and serious fault in critical rotating equipment such as salient-pole synchronous generators and large electric motors. Early detection and precise location are crucial to preventing the fault from escalating and avoiding catastrophic downtime. Currently, online monitoring technologies for rotor winding inter-turn short circuits are mainly classified into the following categories, but all have significant limitations.

[0003] The air gap detection coil method is the most traditional and widely used approach. It involves installing one or more detection coils within the stator core to measure the electromotive force induced by the rotor's rotating magnetic field. This method identifies faults by analyzing the distortion or harmonic component increments of the induced electromotive force waveform. However, because the detection coils are based on the principle of electromagnetic induction, their output signal has an amplitude of V∝ω·Φ (ω is the angular frequency, Φ is the magnetic flux). During motor startup, shutdown, and low-speed operation (when ω is very small), the signal is extremely weak, creating a monitoring blind zone. Furthermore, a single coil senses the average magnetic flux of its covered area, making it insensitive to localized, weak magnetic field distortions and difficult to identify early faults. Typically, it can only determine the magnetic pole where the fault occurred, and cannot achieve precise location along the rotor's axial direction (length).

[0004] The method based on excitation current harmonic analysis diagnoses the problem by analyzing the odd-order harmonic components in the excitation current. This method is an indirect, system-level monitoring approach. The excitation current signal reflects the overall state of the entire rotor winding; however, it has very low sensitivity to localized, minor inter-turn short circuits and is highly susceptible to disturbances within the excitation system itself and background harmonics from the power grid, resulting in a high false alarm rate.

[0005] Indirect methods based on vibration and infrared thermography monitor increased bearing housing vibration or detect abnormal rotor surface temperature fields using infrared thermal imagers. However, both methods only detect superficial symptoms in the middle to late stages of a fault, when significant mechanical or thermal effects have already occurred, and lack early warning capabilities. Furthermore, vibration and temperature rise are affected by various factors (such as misalignment and cooling system malfunctions), resulting in poor specificity and an inability to accurately pinpoint the short circuit point.

[0006] In summary, existing technologies cannot achieve early detection of inter-turn short circuits in rotor windings with high sensitivity across all operating conditions (especially at low speeds), and simultaneously perform precise two-dimensional localization of the fault point in both the circumferential and axial directions. Therefore, a novel monitoring scheme that can overcome these shortcomings and achieve early and accurate diagnosis is urgently needed. Summary of the Invention

[0007] To address the problems of the prior art, this invention provides a rotor inter-turn short circuit monitoring system and method based on a tunnel magnetoresistive sensor array. This method has higher sensitivity, can achieve full-speed monitoring, and can accurately locate inter-turn short circuit faults in the winding axially.

[0008] This invention is achieved through the following technical solution: In a first aspect, the present invention provides a rotor inter-turn short circuit monitoring system based on a magnetic field sensor array, comprising a magnetic field sensor array, a data acquisition and processing module, and an intelligent diagnostic module; the magnetic field sensor array comprises several axial sensor groups, each axial sensor group comprising several magnetic field sensors; each axial sensor group is distributed along the circumferential direction on the inner surface of the stator core, each axial sensor group is arranged opposite to a rotor slot, and several magnetic field sensors in each axial sensor group are evenly distributed along the rotor axis on the stator slot wedge or the inner surface of the stator core; The magnetic field sensor is used to collect simulated magnetic field strength signals; The data acquisition and processing module is used to receive the magnetic field strength analog signals output by all magnetic field sensors and convert the magnetic field strength analog signals into digital signals; The intelligent diagnostic module is used to receive the digital signal, extract the magnetic field waveform corresponding to each rotation of the rotor from the digital signal, compare the magnetic field waveform corresponding to each magnetic field sensor in each axial sensor group, and determine the inter-turn short circuit status of the rotor area corresponding to each magnetic field sensor in each axial sensor group based on the comparison results.

[0009] Preferably, each axial sensor group includes at least three magnetic field sensors, with one near the drive end of the rotor, one located in the middle of the stator core, and one near the non-drive end of the rotor.

[0010] Preferably, the magnetic field sensor is a tunnel magnetoresistive sensor.

[0011] Secondly, the present invention provides a rotor inter-turn short-circuit monitoring method based on a magnetic field sensor array, which, based on the system described above, includes: During motor operation, the magnetic field sensor collects simulated magnetic field strength signals; The data acquisition and processing module receives the analog magnetic field strength signals output by all magnetic field sensors and converts the analog magnetic field strength signals into digital signals. The intelligent diagnostic module receives the digital signal, extracts the magnetic field waveform corresponding to each rotation of the rotor from the digital signal, compares it with the magnetic field waveform corresponding to each magnetic field sensor in each axial sensor group, and determines the inter-turn short circuit status of the rotor area corresponding to each magnetic field sensor in each axial sensor group based on the comparison results.

[0012] Preferably, the rotor inter-turn short circuit monitoring method based on magnetic field sensor array uses the rotor key phase signal as a reference, aligns the magnetic field waveforms corresponding to all magnetic field sensors on the time axis, and then compares the magnetic field waveforms corresponding to each magnetic field sensor in each axial sensor group.

[0013] Preferably, in the rotor inter-turn short circuit monitoring method based on magnetic field sensor array, the magnetic field waveforms corresponding to each magnetic field sensor in each axial sensor group are compared, and the inter-turn short circuit situation of the rotor region corresponding to each magnetic field sensor is determined according to the comparison results. Specifically, the waveform distortion intensity factor of the magnetic field waveforms corresponding to each magnetic field sensor in each axial sensor group is compared, and the rotor region corresponding to the magnetic field sensor with the largest waveform distortion intensity factor is determined as a suspected inter-turn short circuit fault point.

[0014] Preferably, in the rotor inter-turn short-circuit monitoring method based on a magnetic field sensor array, the formula for calculating the waveform distortion intensity factor is as follows:

[0015] in, B i,healthy ( i k () represents the angle of the i-th magnetic field sensor in a certain axial sensor group when the motor is in a healthy state. i k The magnetic field reference value, For the i-th magnetic field sensor in a certain axial sensor group at an angle i k The magnetic field amplitude, i k For the first k The angle corresponding to each sampling point, where N is the number of sampling points.

[0016] Preferably, the rotor inter-turn short-circuit monitoring method based on a magnetic field sensor array further includes: performing spectral analysis on the magnetic field waveform corresponding to the largest waveform distortion intensity factor to calculate the second harmonic amplitude of the magnetic field waveform. A 2 and fundamental amplitude A The ratio of 1 HR=A 2 / A 1; when HR Greater than the threshold K th When the suspected inter-turn short circuit fault point is confirmed to be faulty, the threshold... K th This was determined based on historical monitoring data of the motor's health status.

[0017] Preferably, in the rotor inter-turn short circuit monitoring method based on a magnetic field sensor array, the K th The method for determining this is as follows: under the healthy condition of the motor, statistically analyze multiple data points obtained from historical monitoring. HR healthy Values, multiple values HR healthy The mean of the values ​​is obtained. HR average ,but K th = HR average +n·σ where, HR healthy The second harmonic amplitude of the magnetic field waveform corresponding to the magnetic field sensor when the motor is in a healthy state. A 2 and fundamental amplitude A The ratio of 1 to n is the confidence coefficient set according to the false alarm rate requirement, and σ is the standard deviation.

[0018] Preferably, the rotor inter-turn short-circuit monitoring method based on a magnetic field sensor array further includes: estimating the equivalent number of short-circuit turns at a suspected inter-turn short-circuit fault point in the following manner: N short ~η· N total η= ΔB / B healthy ΔB = B healthy - B fault in, N short The equivalent number of short-circuit turns at the suspected inter-turn short-circuit fault point. N total This represents the total number of turns in the rotor slot corresponding to the suspected inter-turn short-circuit fault point. B healthy This is the reference value for the magnetic field under healthy motor conditions. B fault The magnetic field amplitude of the magnetic field waveform corresponding to the largest waveform distortion intensity factor. ΔB The depth of magnetic field waveform distortion.

[0019] Compared with the prior art, the present invention has the following beneficial effects: This invention relates to a rotor inter-turn short-circuit monitoring system based on a magnetic field sensor array. By arranging several magnetic field sensors axially at opposite positions in the same rotor slot and comparing the differences in the magnetic field waveforms corresponding to each sensor, the axial location of the rotor inter-turn short-circuit fault point is achieved, greatly improving fault location accuracy and providing crucial guidance information for maintenance. The arrayed arrangement of the magnetic field sensors provides high spatial resolution magnetic field sampling points, enabling the differentiation of multiple fault points in close proximity. Furthermore, this invention directly measures the magnetic field strength rather than its rate of change, resulting in a more stable signal that is less affected by speed fluctuations.

[0020] Furthermore, the magnetic field sensor of this invention employs a tunnel magnetoresistive (TMR) sensor. TMR sensors exhibit extremely high sensitivity to both static and dynamic magnetic fields, capable of detecting weak magnetic field distortions caused by early, slight inter-turn short circuits, thus enabling early warning. The TMR sensor possesses a wide bandwidth response characteristic from DC to high frequencies, allowing this invention to operate effectively under all operating conditions, including motor start-up, shutdown, low-speed turning, and rated speed, filling the monitoring blind spot of traditional methods in the low-speed range.

[0021] This invention relates to a rotor inter-turn short-circuit monitoring method based on a magnetic field sensor array. Several magnetic field sensors arranged axially at relative positions in the same rotor slot collect simulated magnetic field intensity signals. After processing, the magnetic field waveforms corresponding to each sensor are obtained. Based on the differences in the magnetic field waveforms, the axial position information of the rotor inter-turn short-circuit fault point can be obtained. Simultaneously, by using several axial sensor groups arranged circumferentially, the circumferential position information of the rotor inter-turn short-circuit fault point can be located. Thus, two-dimensional precise positioning of the rotor inter-turn short-circuit fault point is simultaneously achieved in both the circumferential and axial directions.

[0022] Furthermore, the method of the present invention obtains the waveform distortion degree of each magnetic field waveform by comparing the waveform distortion intensity factor of the magnetic field waveform corresponding to each magnetic field sensor in each axial sensor group. The rotor region corresponding to the magnetic field waveform with the largest waveform distortion depth is the suspected inter-turn short circuit fault point.

[0023] Furthermore, this invention measures the second harmonic amplitude of the magnetic field waveform with the greatest waveform distortion depth. A 2 and fundamental amplitude A The ratio of 1 HR Thresholds related to the motor's health status K th Only by comparing HR Greater than the threshold K th Only then is the suspected inter-turn short circuit fault considered valid, thus avoiding misjudgment.

[0024] Furthermore, this invention determines the severity of a fault based on the waveform distortion depth of the magnetic field waveform with the largest waveform distortion depth, providing a basis for selecting subsequent countermeasures. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the 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 based on these drawings without creative effort.

[0026] Figure 1 The diagram shows the structure of the rotor turn-to-turn short circuit monitoring system based on a magnetic field sensor array according to the present invention; (a) an axial view of one arrangement of the magnetic field sensor array; (b) a top view of one arrangement of the magnetic field sensor array.

[0027] Figure 2 This is a flowchart of the rotor turn-to-turn short-circuit monitoring method based on a magnetic field sensor array according to the present invention. Detailed Implementation

[0028] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention.

[0029] It should be noted that the process equipment or apparatus not specifically mentioned in the following embodiments are all conventional equipment or apparatus in the art.

[0030] It should be noted that the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or apparatuses. Furthermore, unless otherwise stated, the numbering of each method step is merely a convenient tool for identifying each method step, and not intended to limit the order of the method steps or define the scope of the invention. Changes or adjustments to their relative relationships, without substantially altering the technical content, should also be considered within the scope of the invention.

[0031] The rotor inter-turn short circuit monitoring system based on a magnetic field sensor array of the present invention includes a magnetic field sensor array, a data acquisition and processing module, and an intelligent diagnostic module; the magnetic field sensor array includes several groups of axial sensor groups, each group of axial sensor groups includes several magnetic field sensors; each group of axial sensor groups is distributed along the circumferential direction on the inner surface of the stator core, each group of axial sensor groups is arranged opposite to a rotor slot or the same magnetic pole centerline, and several magnetic field sensors in each group of axial sensor groups are evenly distributed along the rotor axis on the stator slot wedge or the inner surface of the stator core; The magnetic field sensor is used to collect simulated magnetic field strength signals; The data acquisition and processing module is used to receive the magnetic field strength analog signals output by all magnetic field sensors and convert the magnetic field strength analog signals into digital signals; The intelligent diagnostic module is used to receive the digital signal, extract the magnetic field waveform corresponding to each rotation of the rotor from the digital signal, compare the magnetic field waveform corresponding to each magnetic field sensor in each axial sensor group, and determine the inter-turn short circuit status of the rotor area corresponding to each magnetic field sensor in each axial sensor group based on the comparison results.

[0032] In some embodiments of the present invention, each axial sensor group includes at least three magnetic field sensors, wherein the three magnetic field sensors in each axial sensor group are: one near the driving end of the rotor, one located in the middle of the stator core, and one near the non-driving end of the rotor.

[0033] In some embodiments of the present invention, the magnetic field sensor is a tunnel magnetoresistive (TMR) sensor, which is fixed to the stator slot wedge or the inner surface of the stator core by means of embedding or mounting.

[0034] In some embodiments of the present invention, the intelligent diagnostic module further includes a fault severity quantification unit, which is configured to: quantify the magnetic field waveform distortion depth corresponding to the maximum waveform distortion intensity factor. ΔB = B healthy - B fault The magnetic field reference value under the healthy condition of the motor B healthy The proportion η= ΔB / B healthy Based on the design total number of turns of the rotor slot corresponding to the suspected inter-turn short circuit fault point. N total Estimate the equivalent number of short-circuit turns N short ~η· N total .

[0035] The system described in this invention can operate under all operating conditions of the motor, including starting, stopping, turning, and rated speed.

[0036] Based on the system described above, this invention provides a rotor inter-turn short-circuit monitoring method based on a magnetic field sensor array, comprising: During motor operation, the magnetic field sensor collects simulated magnetic field strength signals; The data acquisition and processing module receives the analog magnetic field strength signals output by all magnetic field sensors and converts the analog magnetic field strength signals into digital signals. The intelligent diagnostic module receives the digital signal and extracts the magnetic field waveform corresponding to each revolution of the rotor from the digital signal. B i ( i ),in i Number the magnetic field sensor. i The rotor rotation angle (corresponding to a specific rotor slot number) is used to compare the magnetic field waveforms of each magnetic field sensor in each axial sensor group. Based on the comparison results, the inter-turn short circuit status of the rotor region corresponding to each magnetic field sensor in each axial sensor group is determined.

[0037] In some embodiments of the present invention, the magnetic field waveforms corresponding to all magnetic field sensors are aligned on the time axis based on the rotor key phase signal, and then the magnetic field waveforms corresponding to each magnetic field sensor in each axial sensor group are compared.

[0038] The method of this invention determines the location of the inter-turn short-circuit fault point in the rotor axial dimension by comparing the magnetic field waveforms generated by magnetic field sensors arranged along the axial direction at the same circumferential position of the rotor, based on the attenuation of waveform distortion intensity along the axial direction. If the magnetic field waveforms of all magnetic field sensors in the same axial sensor group are undistorted and consistent, it is determined that there is no inter-turn short circuit in the rotor slot corresponding to that axial sensor group. If the magnetic field waveform of one magnetic field sensor is distorted, and the distortion degree of the waveform of the adjacent magnetic field sensor along the axial direction is significantly reduced or disappears, it is determined that the inter-turn short-circuit fault point is close to the axial position of the magnetic field sensor with the deepest waveform distortion.

[0039] Specifically, in some embodiments of the present invention, the magnetic field waveforms corresponding to each magnetic field sensor in each axial sensor group are compared, and the inter-turn short circuit situation of the rotor region corresponding to each magnetic field sensor is determined based on the comparison results. Specifically, the waveform distortion intensity factor of the magnetic field waveforms corresponding to each magnetic field sensor in each axial sensor group is compared, and the rotor region corresponding to the magnetic field sensor with the largest waveform distortion intensity factor is determined as a suspected inter-turn short circuit fault point.

[0040] In some embodiments of the present invention, the formula for calculating the waveform distortion intensity factor is as follows:

[0041] in, B i,healthy ( i k () represents the angle of the i-th magnetic field sensor in a certain axial sensor group when the motor is in a healthy state. i k The magnetic field reference value, For the i-th magnetic field sensor in a certain axial sensor group at an angle i k The magnetic field amplitude, i k For the first k The angle corresponding to each sampling point, where N is the number of sampling points.

[0042] In some embodiments of the present invention, the rotor inter-turn short-circuit monitoring method based on a magnetic field sensor array further includes: performing spectral analysis on the magnetic field waveform corresponding to the largest waveform distortion intensity factor, and calculating the second harmonic amplitude of the magnetic field waveform. A 2 and fundamental amplitude A The ratio of 1 HR=A 2 / A 1; when HR > K th When the suspected inter-turn short circuit fault point is confirmed to be faulty, the threshold... K th This was determined based on historical monitoring data of the motor's health status.

[0043] In some embodiments of the present invention, the K th The method for determining this is as follows: under the healthy condition of the motor, statistically analyze multiple data points obtained from historical monitoring. HR healthy Values, multiple values HR healthy The mean of the values ​​is obtained. HR average ,but K th = HR average +n·σ where, HR healthy The second harmonic amplitude of the magnetic field waveform corresponding to the magnetic field sensor when the motor is in a healthy state. A 2 and fundamental amplitude A The ratio of 1 to n; n is the confidence coefficient set according to the false alarm rate requirement, usually 3≤n≤6; σ is the standard deviation.

[0044] In some embodiments of the present invention, the rotor inter-turn short-circuit monitoring method based on a magnetic field sensor array further includes: estimating the equivalent number of short-circuit turns at a suspected inter-turn short-circuit fault point in the following manner: N short ~n· N total n= ΔB / B healthy ΔB = B healthy - B fault in, N short The equivalent number of short-circuit turns at the suspected inter-turn short-circuit fault point. N total This represents the total number of turns in the rotor slot corresponding to the suspected inter-turn short-circuit fault point. B healthy This is the reference value for the magnetic field under healthy motor conditions. B fault The magnetic field amplitude of the magnetic field waveform corresponding to the largest waveform distortion intensity factor. ΔB The depth of magnetic field waveform distortion.

[0045] Example like Figure 1 As shown, the system in this embodiment includes a magnetic field sensor array 2, a data acquisition and processing module 3, and an intelligent diagnostic module 4. The rotor rotates in the air gap. The magnetic field sensor array 2 includes several groups of axial sensors. In the circumferential direction of the stator core 1, one group of axial sensors is arranged at regular mechanical angles (e.g., 120 degrees). Each group of axial sensors consists of three TMR sensors arranged along the rotor axis. Therefore, there are a total of nine TMR sensors: TMR sensors D1, D2, and D3 near the rotor drive end (the axial cross-section of D1, D2, and D3 is section D); TMR sensors M1, M2, and M3 located in the middle of the stator core (the axial cross-section of M1, M2, and M3 is section M); and TMR sensors N1, N2, and N3 near the non-drive end of the rotor (the axial cross-section of N1, N2, and N3 is section N). This arrangement provides both circumferential and axial magnetic field sampling.

[0046] Simulated fault settings: Axial position: Middle of the rotor (corresponding to section M) Circumferential position: Rotor slot number 12 (directly below TMR sensor M2) Fault type: Manually set 1-turn short circuit Short-circuit resistance: approximately 0.5Ω (simulating actual contact resistance).

[0047] When the motor is running, execute the following: Figure 2 The process shown is as follows: (1) All TMR sensors synchronously and continuously acquire magnetic field strength analog signals, and the data are shown in Table 1 below.

[0048] Table 1. Magnetic field strength of each TMR sensor in the characteristic angle region (when rotor slot 12 is directly opposite).

[0049] All rotor sensors can detect changes in the magnetic field. The TMR sensor M2 has the largest change (1.00 Gauss), which is 5-10 times that of the other TMR sensors. The changes of the other TMR sensors are between 0.10-0.20 Gauss and are evenly distributed.

[0050] 2) For each axial section, calculate the distortion factor of the TMR sensor (sensor 2 for each axial section) facing the 12th rotor slot.

[0051] formula:

[0052] Calculation results: TMR sensor D2 (driving end): D D2 =0.15 Gauss TMR sensor M2 (middle): D M2 =1.00 Gauss TMR sensor N2 (non-driving end): D N2 =0.10 Gauss Axial positioning analysis: The D value of TMR sensor M2 is the largest, which is 6.67 times that of TMR sensor D2 and 10 times that of TMR sensor N2.

[0053] Diagnostic conclusion: The fault is located in the axial mid-section (M section).

[0054] 3) Harmonic analysis verification Harmonic reference for health status (24-hour statistics): Second harmonic ratio HR healthy Mean: m =0.8% Standard deviation: s =0.15% Threshold setting (n=4): K th = m +4 s=0.8% + 4 × 0.15% = 1.4% The calculation results of the fault state harmonic ratio are shown in Table 2.

[0055] Table 2 Harmonic Ratios under Fault Conditions

[0056] Harmonic analysis conclusion: The HR of all TMR sensors exceeded the limit, confirming a global fault.

[0057] The HR value of the TMR sensor M2 was the highest (3.00%), further confirming that the fault mainly affected the M section.

[0058] (4) Quantification of fault severity Calculations using TMR sensor M2 data: 1. Relative rate of change: η = ΔB / B healthy =1 / 45.08==0.0222 (2.22%) 2. Equivalent short-circuit turns: N short =η×N total =0.0222×14=0.31 turns).

[0059] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of this invention.

Claims

1. A rotor inter-turn short-circuit monitoring system based on a magnetic field sensor array, characterized in that, It includes a magnetic field sensor array, a data acquisition and processing module, and an intelligent diagnostic module; the magnetic field sensor array includes several groups of axial sensor groups, each group of axial sensor groups includes several magnetic field sensors; each group of axial sensor groups is distributed along the circumferential direction on the inner surface of the stator core, each group of axial sensor groups is arranged opposite to a rotor slot, and several magnetic field sensors in each group of axial sensor groups are evenly distributed along the rotor axis on the stator slot wedge or the inner surface of the stator core; The magnetic field sensor is used to collect simulated magnetic field strength signals; The data acquisition and processing module is used to receive the magnetic field strength analog signals output by all magnetic field sensors and convert the magnetic field strength analog signals into digital signals; The intelligent diagnostic module is used to receive the digital signal, extract the magnetic field waveform corresponding to each rotation of the rotor from the digital signal, compare the magnetic field waveform corresponding to each magnetic field sensor in each axial sensor group, and determine the inter-turn short circuit status of the rotor area corresponding to each magnetic field sensor in each axial sensor group based on the comparison results.

2. The rotor inter-turn short-circuit monitoring system based on a magnetic field sensor array according to claim 1, characterized in that, Each axial sensor group includes at least three magnetic field sensors: one near the drive end of the rotor, one in the middle of the stator core, and one near the non-drive end of the rotor.

3. The rotor inter-turn short-circuit monitoring system based on a magnetic field sensor array according to claim 1, characterized in that, The magnetic field sensor is a tunnel magnetoresistive sensor.

4. A rotor inter-turn short-circuit monitoring method based on a magnetic field sensor array, characterized in that, The system based on any one of claims 1-3 includes: During motor operation, the magnetic field sensor collects simulated magnetic field strength signals; The data acquisition and processing module receives the analog magnetic field strength signals output by all magnetic field sensors and converts the analog magnetic field strength signals into digital signals. The intelligent diagnostic module receives the digital signal, extracts the magnetic field waveform corresponding to each rotation of the rotor from the digital signal, compares it with the magnetic field waveform corresponding to each magnetic field sensor in each axial sensor group, and determines the inter-turn short circuit status of the rotor area corresponding to each magnetic field sensor in each axial sensor group based on the comparison results.

5. The rotor inter-turn short-circuit monitoring method based on a magnetic field sensor array according to claim 4, characterized in that, Using the rotor key phase signal as a reference, the magnetic field waveforms corresponding to all magnetic field sensors are aligned on the time axis, and then the magnetic field waveforms corresponding to each magnetic field sensor in each axial sensor group are compared.

6. The rotor inter-turn short-circuit monitoring method based on a magnetic field sensor array according to claim 4, characterized in that, By comparing the magnetic field waveforms of each magnetic field sensor in each axial sensor group, the inter-turn short circuit situation of the rotor area corresponding to each magnetic field sensor is determined based on the comparison results. Specifically, the waveform distortion intensity factor of the magnetic field waveforms of each magnetic field sensor in each axial sensor group is compared, and the rotor area corresponding to the magnetic field sensor with the largest waveform distortion intensity factor is determined as the suspected inter-turn short circuit fault point.

7. The rotor inter-turn short-circuit monitoring method based on a magnetic field sensor array according to claim 6, characterized in that, The formula for calculating the waveform distortion intensity factor is: in, B i,healthy ( θ k () represents the angle of the i-th magnetic field sensor in a certain axial sensor group when the motor is in a healthy state. θ k The magnetic field reference value, For the i-th magnetic field sensor in a certain axial sensor group at an angle θ k The magnetic field amplitude, θ k For the first k The angle corresponding to each sampling point, where N is the number of sampling points.

8. The rotor inter-turn short-circuit monitoring method based on a magnetic field sensor array according to claim 6, characterized in that, It also includes: performing spectral analysis on the magnetic field waveform corresponding to the largest waveform distortion intensity factor, and calculating the second harmonic amplitude of the magnetic field waveform. A 2 and fundamental amplitude A The ratio of 1 HR=A 2 / A 1; when HR Greater than the threshold K th When the suspected inter-turn short circuit fault point is confirmed to be faulty, the threshold... K th This was determined based on historical monitoring data of the motor's health status.

9. The rotor inter-turn short-circuit monitoring method based on a magnetic field sensor array according to claim 8, characterized in that, The K th The method for determining this is as follows: under the healthy condition of the motor, statistically analyze multiple data points obtained from historical monitoring. HR healthy Values, multiple values HR healthy The mean of the values ​​is obtained. HR average ,but K th = HR average +n·σ where, HR healthy The second harmonic amplitude of the magnetic field waveform corresponding to the magnetic field sensor when the motor is in a healthy state. A 2 and fundamental amplitude A The ratio of 1 to n is the confidence coefficient set according to the false alarm rate requirement, and σ is the standard deviation.

10. The rotor inter-turn short-circuit monitoring method based on a magnetic field sensor array according to claim 8, characterized in that, This also includes estimating the equivalent number of short-circuit turns at suspected inter-turn short-circuit fault points as follows: N short ~h· N total n= ΔB / B healthy ΔB = B healthy - B fault in, N short The equivalent number of short-circuit turns at the suspected inter-turn short-circuit fault point. N total This represents the total number of turns in the rotor slot corresponding to the suspected inter-turn short-circuit fault point. B healthy This is the reference value for the magnetic field under healthy motor conditions. B fault The magnetic field amplitude of the magnetic field waveform corresponding to the largest waveform distortion intensity factor. ΔB The depth of magnetic field waveform distortion.

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