A variable frequency motor bearing condition monitoring system and method

Abstract

This invention relates to a variable frequency motor bearing condition monitoring system and method. The system includes a high-frequency oscillating current sensor and a condition monitoring circuit. The high-frequency oscillating current sensor is non-contactly installed on the side of the variable frequency motor under test to extract the high-frequency switching oscillation current signal of the motor. The condition monitoring circuit includes a modal filtering module, a fault feature extraction module, and a bearing condition evaluation module connected in sequence. The modal filtering module extracts one or more dominant modal currents from the high-frequency switching oscillating current signal. The fault feature extraction module extracts grease condition features and mechanical fault condition features from the dominant modal currents. The bearing condition evaluation module comprehensively evaluates the bearing condition of the variable frequency motor under test based on the grease condition features and the mechanical fault condition features. Compared with the prior art, this invention can accurately and safely detect subtle changes in the bearing condition of a variable frequency motor.

Description

Technical Field

[0001] This invention belongs to the field of variable frequency motor condition monitoring, and in particular relates to a variable frequency motor bearing condition monitoring system and method. Background Technology

[0002] Variable frequency motors (VFMs) are crucial drive devices in modern industrial engineering, widely used in important fields such as rail transportation, electric vehicles, ship propulsion, and wind power generation. Online monitoring of VFMs is an important measure to improve system safety and reliability and reduce operation and maintenance costs. Bearings are an indispensable core component in VFM motor systems, and also one of the components with the highest failure rate. This is because the inner and outer raceways of the motor bearing maintain relative rotation and are continuously subjected to mechanical stress and wear, which accumulate over time and shorten the bearing's lifespan. In actual systems, some bearings may also fail due to assembly or manufacturing defects, overload operation, or insufficient lubrication.

[0003] The operating status of variable frequency motor bearings can be reflected by various system signals. Existing bearing condition monitoring methods typically compare the bearing's operating information with fault characteristic information to achieve effective bearing condition monitoring. Based on the different state variable signals, bearing condition monitoring technologies can be broadly categorized into vibration methods, current methods, and acoustic emission methods. Vibration methods monitor bearing operating status by analyzing vibration signals. Vibration sensors are generally installed on the motor housing at axial or radial positions to collect vibration signals. Vibration methods can diagnose relatively serious bearing mechanical faults, but they are not sensitive enough to identify bearing grease deterioration or early mechanical faults. Current methods monitor bearing operating status by analyzing motor current signals. When the bearing's health condition changes, the motor's air gap also changes, inducing corresponding harmonic currents in the motor stator windings. By analyzing the stator current, the harmonic components corresponding to unhealthy conditions can be extracted, achieving non-invasive bearing condition monitoring. However, in actual systems, motor harmonic currents are greatly affected by the fundamental frequency and operating conditions, making misdiagnosis prone to occur. Acoustic emission method reflects the health status of bearings through sound signals. When the bearing material is subjected to deformation or abnormal external force, it will release energy rapidly and produce a transient stress wave. However, in practical applications, acoustic emission method is easily affected by environmental noise and has high technical requirements.

[0004] In summary, a condition monitoring scheme for variable frequency motor bearings needs to be designed to sensitively and accurately identify subtle changes in the condition of variable frequency motor bearings. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a variable frequency motor bearing condition monitoring system and method to accurately and sensitively detect subtle changes in the condition of variable frequency motor bearings, thereby achieving early fault warning and condition-based maintenance.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] This invention provides a variable frequency motor bearing condition monitoring system, including a high-frequency oscillating current sensor and a condition monitoring circuit;

[0008] The high-frequency oscillating current sensor is non-contactly installed on the side of the variable frequency motor under test, and is used to extract the high-frequency switching oscillating current signal i of the variable frequency motor under test. sw ;

[0009] The condition monitoring circuit includes a modal filtering module, a fault feature extraction module, and a bearing condition assessment module connected in sequence. The modal filtering module is used to extract the high-frequency switching oscillation current signal i. sw Extract one or more dominant mode currents i mode (n); The fault feature extraction module is used to extract features from the dominant mode current i mode Extracting the grease state feature K1(n) and mechanical fault state feature K2(n) from (n), the grease state feature K1(n) is related to the dominant mode current i of the variable frequency motor under test. mode (n) The average amplitude per unit value is negatively correlated, and the mechanical fault state feature K2(n) is positively correlated with the number of effective oscillations of the dominant mode of the variable frequency motor under test; the bearing state evaluation module is used to comprehensively evaluate the bearing state of the variable frequency motor under test based on the grease state feature K1(n) and the mechanical fault state feature K2(n).

[0010] Furthermore, the installation location of the high-frequency oscillating current sensor includes three-phase pass-through, phase pass-through, or ground pass-through.

[0011] Furthermore, the lower limit bandwidth of the high-frequency oscillating current sensor is greater than the switching frequency of the variable frequency motor under test during operation.

[0012] Furthermore, the modal filtering module uses analog bandpass filters, digital bandpass filters, FFT (Fast Fourier Transform), or time-frequency analysis algorithms to filter the high-frequency switching oscillation current signal i. sw Extract one or more dominant mode currents i mode (n).

[0013] Furthermore, the center frequency of the modal filtering module is the high-frequency switching oscillation current signal i. sw The frequency of the dominant mode.

[0014] Furthermore, the calculation method for the oil state characteristic K1(n) is as follows:

[0015] K1(n)=I mode_ave0 / I mode_ave

[0016] Among them, I mode_ave0 I represents the average amplitude of the dominant mode current of a healthy motor. mode_ave This represents the average amplitude of the dominant mode current of the variable frequency motor under test.

[0017] Furthermore, the number of effective oscillations of the dominant mode is the number of dominant mode currents whose amplitude exceeds a set threshold within a data segment.

[0018] Furthermore, the mechanical fault state characteristic K2(n) is calculated as follows:

[0019] K2(n)=N imode / N imode0

[0020] Where, N imode0 N represents the number of effective oscillations of the dominant mode of a healthy motor. imode This represents the number of effective oscillations of the dominant mode of the variable frequency motor under test.

[0021] Furthermore, the bearing condition assessment module compares the grease condition feature K1(n) and mechanical fault condition feature K2(n) of the variable frequency motor under test with the benchmark value calculated based on a healthy motor, respectively, to comprehensively assess the bearing condition of the variable frequency motor under test.

[0022] The present invention also provides a method for monitoring the condition of a variable frequency motor bearing, comprising the following steps:

[0023] S1. Install the high-frequency oscillating current sensor non-contactly on the side of the variable frequency motor under test, and extract the high-frequency switching oscillating current signal i from the variable frequency motor under test. sw ;

[0024] S2, The high-frequency switching oscillation current signal i is obtained through the modal filtering module. sw Extract one or more dominant mode currents i mode (n);

[0025] S3, using the fault feature extraction module to extract the dominant mode current i mode Extract the oil state features K1(n) and mechanical fault state features K2(n) from (n);

[0026] S4. The bearing condition assessment module comprehensively assesses the bearing condition of the variable frequency motor under test based on the grease condition feature K1(n) and the mechanical fault condition feature K2(n).

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] This invention proposes a variable frequency motor bearing condition monitoring system, including a high-frequency oscillating current sensor and a condition monitoring circuit. The high-frequency oscillating current sensor is non-contactly installed on the side of the variable frequency motor under test, without altering the main circuit hardware structure of the motor. It can extract the high-frequency switching oscillating current signal of the variable frequency motor under test without a direct electrical connection between the sensor and the main circuit of the variable frequency motor system, thus improving safety. The condition monitoring circuit includes a modal filtering module, a fault feature extraction module, and a bearing condition assessment module connected in sequence. The modal filtering module is used to extract one or more dominant modal currents from the high-frequency switching oscillating current signal; the fault feature extraction module... The extraction module is used to extract grease condition characteristics and mechanical fault condition characteristics from the dominant mode current. Specifically, the grease condition characteristics are negatively correlated with the per-unit value of the average amplitude of the dominant mode current of the variable frequency motor under test, while the mechanical fault condition characteristics are positively correlated with the number of effective oscillations of the dominant mode of the variable frequency motor under test. The bearing condition assessment module is used to comprehensively assess the bearing condition of the variable frequency motor under test based on the grease condition characteristics and mechanical fault condition characteristics. By monitoring and analyzing the condition characteristics of the high-frequency switching oscillation current signal online, the above system can sensitively reflect the slight changes in the grease deterioration and early mechanical fault condition of the motor bearing, and realize early fault warning and condition-based maintenance. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of a variable frequency motor bearing condition monitoring system.

[0030] Figure labeling: 1. High-frequency oscillating current sensor; 2. Condition monitoring circuit; 201. Modal filtering module; 202. Fault feature extraction module; 203. Bearing condition assessment module;

[0031] Figure 2 For testing system schematics;

[0032] Figure 3 This is a schematic diagram of the measured high-frequency current signal of the motor;

[0033] Figure 4 A schematic diagram of the extracted common-mode current 14MHz mode signal;

[0034] Figure 5 This is a schematic diagram of the bearing condition characteristic monitoring results;

[0035] Figure 6 This is a flowchart of a method for monitoring the condition of bearings in a variable frequency motor. Detailed Implementation

[0036] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0037] Example 1

[0038] This embodiment provides a variable frequency motor bearing condition monitoring system, such as Figure 1 As shown, it includes a high-frequency oscillating current sensor 1 and a status monitoring circuit 2.

[0039] The high-frequency oscillating current sensor 1 is installed non-contactly on the side of the variable frequency motor under test. Its installation position can be achieved using three-phase interconnection, phase-wire interconnection, or ground-wire interconnection. The lower bandwidth of the high-frequency oscillating current sensor 1 is greater than the switching frequency of the variable frequency motor under test to filter out interference from the fundamental and harmonic currents during motor operation. The upper bandwidth of the high-frequency oscillating current sensor 1 should be greater than 1MHz to extract the high-frequency switching oscillation current signal i from the variable frequency motor under test. sw .

[0040] The condition monitoring circuit 2 includes a modal filtering module 201, a fault feature extraction module 202, and a bearing condition assessment module 203 connected in sequence. The modal filtering module 201 uses an analog bandpass filter, a digital bandpass filter, a Fast Fourier Transform (FFT), or a time-frequency analysis algorithm to extract the fault feature from the high-frequency switching oscillation current signal i. sw Extract one or more dominant mode currents i mode (n), n=1,…,N. The center frequency of the modal filtering module 201 is the high-frequency switching oscillation current signal i. sw The frequency F of the dominant mode mode (n), n=1,…,N.

[0041] Fault feature extraction module 202 is used to extract features from dominant mode current i mode The invention extracts grease state characteristics K1(n) reflecting bearing grease deterioration and mechanical fault state characteristics K2(n) reflecting bearing mechanical failure from the grease (n). Since bearing oil film capacitance directly reflects bearing operating conditions, when grease deterioration or mechanical failure occurs, the bearing oil film undergoes characteristic changes, leading to corresponding changes in the amplitude or effective oscillation count of the dominant mode current. Therefore, this invention extracts grease state characteristics K1(n) reflecting bearing grease deterioration and mechanical fault state characteristics K2(n) from the dominant mode current i mode The two feature quantities, oil state feature K1(n) and mechanical fault state feature K2(n), are extracted from (n) to achieve sensitive and accurate fault diagnosis.

[0042] The grease state characteristics K1(n) and the dominant mode current i of the variable frequency motor under test mode(n) The average amplitude per unit value is negatively correlated, and the specific calculation method is as follows:

[0043] K1(n)=I mode_ave0 / I mode_ave

[0044] Among them, I mode_ave0 I represents the average amplitude of the dominant mode current of a healthy motor. mode_ave This represents the average amplitude of the dominant mode current of the variable frequency motor under test.

[0045] The mechanical fault state characteristic K2(n) is positively correlated with the number of effective oscillations of the dominant mode of the variable frequency motor under test. The number of effective oscillations of the dominant mode is the number of dominant mode currents whose amplitude exceeds a set threshold (in this embodiment, the set threshold is 30% of the maximum amplitude of the dominant mode current) within a data segment. The mechanical fault state characteristic K2(n) is calculated as follows:

[0046] K2(n)=N imode / N imode0

[0047] Where, N imode0 N represents the number of effective oscillations of the dominant mode of a healthy motor. imode This represents the number of effective oscillations of the dominant mode of the variable frequency motor under test.

[0048] The bearing condition assessment module 203 is used to compare the grease condition characteristic K1(n) and mechanical fault condition characteristic K2(n) of the variable frequency motor under test with the benchmark value calculated based on the healthy motor, and comprehensively assess the bearing condition of the variable frequency motor under test.

[0049] The aforementioned system utilizes a non-contact current sensor to extract and analyze the high-frequency oscillation current signal of the PWM switch from the current of the variable frequency motor system under test, thereby achieving online monitoring of the bearing condition of the variable frequency motor. On the one hand, the dedicated current sensor for condition monitoring has no direct electrical connection with the main circuit of the variable frequency motor system, which will not affect the normal operation of the system and can avoid potential safety hazards; on the other hand, by monitoring and analyzing the characteristics of the high-frequency switch oscillation state online, it can sensitively reflect subtle changes in the deterioration of the motor bearing grease and the early mechanical fault state, realizing early fault warning and condition-based maintenance.

[0050] To verify the effectiveness of the above system, this embodiment combines field testing of a high-power variable frequency motor system to verify the effectiveness of the invention. For example... Figure 3 As shown, in the test system, one inverter simultaneously drives four variable frequency motors, of which the variable frequency motors are three-phase induction motors (rated voltage 1140V, rated current 190A, rated power 200kW), and the inverter capacity is 1MW.

[0051] Non-contact common-mode current sensors and ground current sensors were installed on the three-phase cables of motors 1 through 4. The output signal of each sensor was connected to an oscilloscope. The eight sensors were divided into two groups and connected to two digital oscilloscopes. The common-mode current and ground current of the four motors were measured online. Data was continuously acquired using digital oscilloscopes, recording six data segments per minute, with each data segment having a time window length of 100ms. The test lasted for 40 minutes. The measured high-frequency common-mode current signal of the motor is shown below. Figure 3 As shown.

[0052] The 14MHz common-mode current was selected as the characteristic mode to quantitatively assess the bearing health status of four motors. A second-order digital bandpass filter was used in Matlab / Simulink to extract the 14MHz mode component from the common-mode current. The results are as follows: Figure 4 As shown. Taking the healthy motor No. 1 as the benchmark, the grease condition characteristic K1 and mechanical fault condition characteristic K2 of the bearings of each motor were calculated. The test results are as follows. Figure 5 As shown, the grease in motors 2 through 4 has deteriorated to some extent (with the grease in motor 4 being in the worst condition), while motors 3 and 4 exhibit some degree of mechanical failure. The online monitoring results are consistent with the actual situation, verifying the effectiveness of the invention.

[0053] Example 2

[0054] This embodiment provides a method for monitoring the condition of a variable frequency motor bearing, applicable to the system described in Embodiment 1. For example... Figure 6 As shown, it includes the following steps:

[0055] S1. Install the high-frequency oscillating current sensor 1 non-contactly on the side of the variable frequency motor under test, and extract the high-frequency switching oscillating current signal i from the variable frequency motor under test. sw .

[0056] S2, The high-frequency switching oscillation current signal i is obtained through the mode filtering module 201. sw Extract one or more dominant mode currents i mode (n).

[0057] S3, using the fault feature extraction module 202 to extract the dominant mode current i mode Extract the oil state features K1(n) and mechanical fault state features K2(n) from (n).

[0058] S4. The bearing condition assessment module 203 comprehensively assesses the bearing condition of the variable frequency motor under test based on the grease condition characteristics K1(n) and the mechanical fault condition characteristics K2(n).

[0059] If the above methods are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0060] The above description of the embodiments is provided to enable those skilled in the art to understand and use the invention. It will be apparent to those skilled in the art that various modifications can be made to these embodiments, and the general principles described herein can be applied to other embodiments without inventive effort. Therefore, the present invention is not limited to the above embodiments, and any improvements and modifications made by those skilled in the art based on the disclosure of the present invention without departing from the scope of the invention should be within the protection scope of the present invention.

Claims

1. A variable frequency motor bearing condition monitoring system, characterized in that, It includes a high-frequency oscillating current sensor (1) and a status monitoring circuit (2); The high-frequency oscillating current sensor (1) is installed non-contactly on the side of the variable frequency motor under test, and is used to extract the high-frequency switching oscillating current signal of the variable frequency motor under test. i sw ; The condition monitoring circuit (2) includes a modal filtering module (201), a fault feature extraction module (202), and a bearing condition assessment module (203) connected in sequence. The modal filtering module (201) is used to extract the fault feature from the high-frequency switching oscillation current signal. i sw Extract one or more dominant mode currents i mode ( n The fault feature extraction module (202) is used to extract fault features from the dominant mode current. i mode ( n Extracting oil state characteristics K 1( n ) and mechanical failure state characteristics K 2( n The oil state characteristics K 1( n ) and the dominant mode current of the variable frequency motor under test i mode ( n The average amplitude per unit value is negatively correlated with the mechanical fault state characteristics. K 2( n The number of effective oscillations of the dominant mode of the variable frequency motor under test is positively correlated with the bearing condition assessment module (203); the bearing condition assessment module (203) is used to assess the bearing condition characteristics based on the grease condition characteristics. K 1( n and the mechanical fault state characteristics K 2( n A comprehensive assessment of the bearing condition of the variable frequency motor under test is conducted.

2. The variable frequency motor bearing condition monitoring system according to claim 1, characterized in that, The high-frequency oscillating current sensor (1) can be installed in three-phase loop, phase wire loop, or ground wire loop.

3. The variable frequency motor bearing condition monitoring system according to claim 1, characterized in that, The lower limit bandwidth of the high-frequency oscillating current sensor (1) is greater than the switching frequency of the variable frequency motor under test during operation.

4. The variable frequency motor bearing condition monitoring system according to claim 1, characterized in that, The modal filtering module (201) uses an analog bandpass filter, a digital bandpass filter, an FFT (Fast Fourier Transform), or a time-frequency analysis algorithm to filter the high-frequency switching oscillation current signal. i sw One or more dominant mode currents are extracted. i mode ( n ).

5. The variable frequency motor bearing condition monitoring system according to claim 1, characterized in that, The center frequency of the modal filtering module (201) is the high-frequency switching oscillation current signal. i sw The frequency of the dominant mode.

6. The variable frequency motor bearing condition monitoring system according to claim 1, characterized in that, The characteristics of the oil state K 1( n The calculation method for ) is as follows: K 1( n )= I mode_ave0 / I mode_ave in, I mode_ave0 The average amplitude of the dominant mode current of a healthy motor. I mode_ave This represents the average amplitude of the dominant mode current of the variable frequency motor under test.

7. The variable frequency motor bearing condition monitoring system according to claim 1, characterized in that, The number of effective oscillations of the dominant mode is the number of dominant mode currents whose amplitude exceeds a set threshold within a data segment.

8. The variable frequency motor bearing condition monitoring system according to claim 1, characterized in that, The mechanical failure state characteristics K 2( n The calculation method for ) is as follows: K 2( n ) = N imode / N imode0 in, N imode0 The effective number of dominant mode oscillations of a healthy motor. N imode This represents the number of effective oscillations of the dominant mode of the variable frequency motor under test.

9. The variable frequency motor bearing condition monitoring system according to claim 1, characterized in that, The bearing condition assessment module (203) will evaluate the grease condition characteristics of the variable frequency motor under test. K 1( n ) and mechanical failure state characteristics K 2( n The bearing condition of the variable frequency motor under test is comprehensively evaluated by comparing it with the benchmark value calculated based on the healthy motor.

10. A method for monitoring the condition of a variable frequency motor bearing, based on the variable frequency motor bearing condition monitoring system as described in claim 1, characterized in that, Includes the following steps: S1. Install the high-frequency oscillating current sensor (1) non-contactly on the side of the variable frequency motor under test, and extract the high-frequency switching oscillating current signal of the variable frequency motor under test. i sw ; S2, The high-frequency switching oscillation current signal is filtered by the modal filtering module (201). i sw Extract one or more dominant mode currents i mode ( n ); S3, using the fault feature extraction module (202) to extract the dominant mode current i mode ( n Extracting oil state characteristics K 1( n ) and mechanical failure state characteristics K 2( n ); S4, Bearing condition assessment module (203) based on the grease condition characteristics K 1( n and the mechanical fault state characteristics K 2( n A comprehensive assessment of the bearing condition of the variable frequency motor under test is conducted.

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