High-precision identification method and system for noise source of asynchronous motor and storage medium

Abstract

The invention provides a high-precision identification method and system for a noise source of an asynchronous motor and a storage medium, and relates to the technical field of asynchronous motors. Related parameters of an inner ring, an outer ring, a retainer and a rolling body of a bearing of the motor are collected, and abnormal frequency analysis is carried out on the inner ring, the outer ring, the retainer and the rolling body; a bearing inner ring abnormal frequency index, a bearing outer ring abnormal frequency index, a rolling body abnormal frequency index and a rigidity abnormal frequency index which reflect abnormal frequencies of an inner ring, an outer ring, a retainer and a rolling body respectively are output, meanwhile, vibration signals are collected for the motor, frequency domain signals are generated after the vibration signals are processed, a frequency spectrum is obtained, and the frequency spectrum is calculated. And generating a rolling body anomaly evaluation index, a rigidity anomaly evaluation index, a bearing inner ring evaluation index and a bearing outer ring anomaly evaluation index which respectively reflect the anomaly degrees of different parts through the relationship of the frequency amplitude and in combination with the anomaly frequency index, so as to assist a worker in judging a specific bearing fault part.

Description

Technical Field

[0001] The present invention relates to the technical field of asynchronous motors, and in particular to a high-precision identification method, system and storage medium for asynchronous motor noise sources. Background Art

[0002] Asynchronous motor is a kind of electric motor widely used in industry and daily life. Its working principle is based on electromagnetic induction, and it mainly consists of two parts: stator and rotor. It is widely used in various mechanical equipment, such as pumps, fans, compressors and conveyor belts. The working principle of asynchronous motor is based on Faraday's law of electromagnetic induction. When AC current passes through the stator winding, a rotating magnetic field is generated inside the stator. The relative motion between this rotating magnetic field and the rotor generates an electromotive force, which drives the rotor to rotate. The rotor speed is usually lower than the rotating magnetic field speed of the stator, which is why it is "asynchronous".

[0003] Asynchronous motors generate noise when working. The noise is composed of various factors, including electromagnetic noise, mechanical noise, and air cooling noise. When mechanical noise is generated, staff are required to analyze and repair the motor. The staff judge the fault location based on experience and it is difficult to determine the source of the noise. At the same time, since the bearing is composed of an outer ring, an inner ring, rolling elements, and a cage, any abnormality or failure in any part will cause the bearing to be eccentric or fail, thereby generating noise. Since the abnormal point is small, it is even more difficult for staff to confirm the specific location.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0005] The object of the present invention is to provide a high-precision identification method, system and storage medium for asynchronous motor noise sources, so as to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A high-precision identification method for asynchronous motor noise sources is used to identify abnormal noise in asynchronous motor bearings. The specific steps include:

[0008] S1. Collect abnormal motor bearing parameters, including bearing inner ring diameter, rolling element diameter, contact angle, and bearing inner ring speed, perform correlation analysis on the bearing inner ring diameter, rolling element diameter, contact angle, and bearing inner ring speed, and generate abnormal frequency indexes of bearing inner and outer rings;

[0009] S2, collecting abnormal motor bearing retainer parameters, wherein the bearing retainer parameters include the inner contact area and the outer contact area of ​​the bearing retainer, performing correlation analysis on the rotation speed, the inner contact area and the outer contact area, and generating an abnormal frequency index of the bearing retainer;

[0010] S3, collecting the material elastic coefficient of the abnormal motor bearing retainer, performing correlation analysis on the material elastic coefficient and the abnormal frequency index of the bearing retainer, and generating the abnormal frequency index of the stiffness of the abnormal motor bearing retainer;

[0011] S4, performing correlation analysis on abnormal motor bearing parameters and the number of rolling elements, and generating an abnormal frequency index of rolling elements;

[0012] S5. Install an acceleration sensor on the bearing, collect vibration signals, process the vibration signals, apply FFT conversion to the processed time domain vibration signals to obtain frequency domain signals, obtain a spectrum through FFT, and display the relationship between frequency and amplitude;

[0013] S6. Collect frequency and amplitude, conduct correlation analysis, and generate rolling element abnormality evaluation index , Stiffness Abnormal Assessment Index , Bearing inner ring evaluation index , Bearing outer ring abnormality assessment index ;

[0014] S7, rolling element abnormality evaluation index , Stiffness Abnormal Assessment Index , Bearing inner ring evaluation index , Bearing outer ring abnormality assessment index With fault threshold Perform comparison and output abnormal parts.

[0015] Furthermore, the vibration signal processing includes removing the DC offset in the vibration signal, filtering out the noise frequency other than 10Hz and 10kHz, and performing noise reduction processing, and performing the bearing inner ring diameter D, rolling element diameter d, and contact angle , Bearing inner ring speed Correlation analysis is performed to generate the abnormal frequency index of the inner and outer rings of the bearing. The abnormal frequency index of the inner and outer rings of the bearing includes the abnormal frequency index of the inner ring of the bearing and the abnormal frequency index of the outer ring of the bearing, and the formula based on the formula is:

[0016] in, The abnormal frequency index of the inner ring of the bearing is used to reflect the characteristic frequency generated on the vibration frequency when an abnormal point appears on the inner ring of the rotor bearing of the motor. is the bearing outer ring abnormal frequency index, which is used to reflect the characteristic frequency generated on the vibration frequency when an abnormal point appears on the outer ring of the rotor bearing of the motor. The bearing inner and outer ring abnormal frequency index is used to reflect the abnormal characteristic frequency of the inner and outer rings of the bearing, where n is the number of rolling elements, and the contact angle It is the contact angle between the rolling element and the inner ring of the bearing.

[0017] Furthermore, the speed , internal contact area and external contact area Perform correlation analysis to generate bearing retainer abnormal frequency index , the formula based on is:

[0018] in, It is the abnormal frequency index of the bearing retainer, which is used to reflect the characteristic frequency generated on the vibration frequency when an abnormal point appears on the bearing retainer of the motor.

[0019] Furthermore, the abnormal point is a hole or crack on the bearing retainer or the inner and outer rings of the bearing, which leads to an asymmetric situation.

[0020] Furthermore, the material elastic coefficient k, bearing retainer abnormal frequency index Perform correlation analysis to generate an abnormal frequency index of the stiffness of abnormal motor bearing retainers , the formula based on is:

[0021] in, It is the abnormal frequency index of the stiffness of the abnormal motor bearing retainer. The abnormal frequency index of stiffness is used to reflect the influence of the material hardness of the motor bearing retainer on the vibration frequency.

[0022] Furthermore, the correlation analysis between abnormal motor bearing parameters and the number of rolling elements is performed to generate the rolling element abnormal frequency index. , the formula based on is:

[0023] in, It is the rolling element abnormal frequency index, which is used to reflect the abnormal characteristic frequency caused by the abnormal rolling element between the inner and outer rings of the bearing. The abnormalities of the rolling element include irregular rolling element, uneven distribution of rolling element, and deviation of the rolling element shape from the preset shape.

[0024] Furthermore, the rolling element abnormal frequency index , Stiffness Abnormal Frequency Index , is the abnormal frequency index of the inner ring of the bearing , Bearing outer ring abnormal frequency index Perform correlation analysis to generate feature set X based on the following formula:

[0025] Among them, the value range of N, W, G, and GD is 1, 2, 3, ..., and the feature set X is used to reflect the bearing abnormality feature frequency set in the motor vibration frequency.

[0026] Furthermore, the acquisition frequency and amplitude , where the amplitude Used to reflect the vibration frequency The vibration amplitude at the time of ,amplitude , perform correlation analysis on the feature set X to generate the rolling element abnormality evaluation index , Stiffness Abnormal Assessment Index , Bearing inner ring evaluation index , Bearing outer ring abnormality assessment index , the formula based on is:

[0027] Among them, rolling element abnormality evaluation index Used to reflect the rolling element failure evaluation index and stiffness abnormality evaluation index Used to reflect the fault assessment index of the bearing cage and the bearing inner ring assessment index Used to reflect the fault assessment index of the inner ring of the bearing and the abnormal assessment index of the outer ring of the bearing Used to reflect the fault assessment index of the bearing outer ring;

[0028] The rolling element abnormality evaluation index, stiffness abnormality evaluation index, bearing inner ring evaluation index, bearing outer ring abnormality evaluation index and fault threshold are compared. Compare, fault threshold It is set to 0.59. The rolling element abnormality evaluation index is used to reflect the abnormality of the rolling element, corresponding to the rolling element part; the stiffness abnormality evaluation index is used to reflect the softness abnormality of the motor bearing retainer, corresponding to the motor bearing retainer part; the bearing inner ring evaluation index is used to reflect the abnormality of the inner ring of the motor rotor bearing, corresponding to the inner ring of the bearing; the bearing outer ring abnormality evaluation index is used to reflect the abnormality of the outer ring of the motor rotor bearing, corresponding to the outer ring of the bearing; the rolling element abnormality evaluation index, stiffness abnormality evaluation index, bearing inner ring evaluation index, and bearing outer ring abnormality evaluation index are respectively compared with the fault threshold Compare, above the fault threshold An index of 0 indicates abnormality in the corresponding part.

[0029] The present invention also provides a high-precision identification system for asynchronous motor noise sources, which is used to perform a high-precision identification method for asynchronous motor noise sources, comprising:

[0030] A bearing parameter collection module is used to collect abnormal motor bearing parameters, wherein the bearing parameters include the bearing inner ring diameter, rolling element diameter, contact angle, and bearing inner ring speed;

[0031] The inner and outer ring abnormal frequency analysis module performs correlation analysis on the inner ring diameter, rolling element diameter, contact angle, and inner ring speed of the bearing to generate the inner and outer ring abnormal frequency index of the bearing

[0032] A retainer parameter acquisition module, used to acquire abnormal motor bearing retainer parameters, wherein the bearing retainer parameters include an inner contact area and an outer contact area of ​​the bearing retainer;

[0033] The bearing retainer abnormal frequency analysis module is used to perform correlation analysis on the speed, inner contact area and outer contact area, and generate the bearing retainer abnormal frequency index

[0034] A retainer material elastic coefficient collection module is used to collect the material elastic coefficient of abnormal motor bearing retainers;

[0035] The stiffness abnormal frequency analysis module is used to perform correlation analysis on the material elastic coefficient and the bearing retainer abnormal frequency index, and generate the stiffness abnormal frequency index of the abnormal motor bearing retainer;

[0036] The rolling element abnormal frequency analysis module performs correlation analysis on abnormal motor bearing parameters and the number of rolling elements, and generates a rolling element abnormal frequency index;

[0037] The signal acquisition module is used to install an acceleration sensor on the bearing, collect vibration signals, process the vibration signals, apply FFT conversion to the processed time-domain vibration signals to obtain frequency-domain signals, obtain the spectrum through FFT, and display the relationship between frequency and amplitude;

[0038] The signal analysis module collects frequency and amplitude, performs correlation analysis on them, and generates a rolling element abnormality evaluation index , Stiffness Abnormal Assessment Index , Bearing inner ring evaluation index , Bearing outer ring abnormality assessment index ;

[0039] Comparison module, rolling element abnormality evaluation index , Stiffness Abnormal Assessment Index , Bearing inner ring evaluation index , Bearing outer ring abnormality assessment index With fault threshold Perform comparison and output abnormal parts.

[0040] The present invention also provides a storage medium on which computer program instructions are stored. When the computer program instructions are executed by a processor, a high-precision identification method for asynchronous motor noise sources is implemented.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] The present invention collects relevant parameters of the inner ring, outer ring, cage and rolling element of the motor bearing, and performs abnormal frequency analysis on the inner ring, outer ring, cage and rolling element respectively, and outputs the bearing inner ring abnormal frequency index, bearing outer ring abnormal frequency index, rolling element abnormal frequency index and stiffness abnormal frequency index which respectively reflect the abnormal frequencies of the inner ring, outer ring, cage and rolling element. At the same time, the vibration signal of the motor is collected, and the frequency domain signal is generated after processing the vibration signal to obtain a spectrum. Through the relationship between frequency amplitude and combined with the abnormal frequency index, the rolling element abnormal evaluation index, stiffness abnormal evaluation index, bearing inner ring evaluation index and bearing outer ring abnormal evaluation index which respectively reflect the abnormal degree of different parts are generated, thereby assisting the staff to judge the specific bearing fault location. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic diagram of the overall method flow of the present invention;

[0044] Figure 2 It is a schematic diagram of the system module of the present invention. DETAILED DESCRIPTION

[0045] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0046] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0047] Example:

[0048] See also Figure 1 , the present invention provides a technical solution:

[0049] A high-precision identification method for asynchronous motor noise sources is used to identify abnormal noise in asynchronous motor bearings. The motor bearings include an outer ring, an inner ring, a cage, and a rolling element. When any of the parts is abnormal, an abnormal characteristic frequency will be generated. The present invention analyzes the characteristic frequency. The specific steps include:

[0050] Step 1: Collect abnormal motor bearing parameters, including bearing inner ring diameter, rolling element diameter, contact angle, and bearing inner ring speed. Perform correlation analysis on the bearing inner ring diameter, rolling element diameter, contact angle, and bearing inner ring speed to generate abnormal frequency indexes of bearing inner and outer rings.

[0051] The vibration signal processing includes removing the DC offset in the vibration signal, filtering out the noise frequency outside 10Hz and 10kHz, and noise reduction processing. The bearing inner ring diameter D, rolling element diameter d, contact angle , Bearing inner ring speed Correlation analysis is performed to generate the abnormal frequency index of the inner and outer rings of the bearing. The abnormal frequency index of the inner and outer rings of the bearing includes the abnormal frequency index of the inner ring of the bearing and the abnormal frequency index of the outer ring of the bearing. The formula is:

[0052] in, The abnormal frequency index of the inner ring of the bearing is used to reflect the characteristic frequency generated on the vibration frequency when an abnormal point appears on the inner ring of the rotor bearing of the motor. The abnormal frequency index of the outer ring of the bearing is used to reflect the characteristic frequency generated on the vibration frequency when an abnormal point appears on the outer ring of the rotor bearing of the motor. The abnormal frequency index of the inner and outer rings of the bearing is used to reflect the abnormal characteristic frequency of the inner and outer rings of the bearing, where n is the number of rolling elements and the contact angle is It is the contact angle between the rolling element and the inner ring of the bearing. The abnormal point is the fault point, which may be caused by asymmetry, pits, cracks and other faults.

[0053] Step 2, collecting abnormal motor bearing retainer parameters, the bearing retainer parameters include the inner contact area and the outer contact area of ​​the bearing retainer, performing correlation analysis on the rotation speed, the inner contact area and the outer contact area, and generating the bearing retainer abnormal frequency index;

[0054] Speed , internal contact area and external contact area Perform correlation analysis to generate bearing retainer abnormal frequency index , the formula based on is:

[0055] in, The abnormal frequency index of the bearing retainer is used to reflect the characteristic frequency generated on the vibration frequency when an abnormal point appears on the bearing retainer of the motor. The abnormal point is the fault point, which may be caused by asymmetry, pits, cracks and other faults.

[0056] Step 3, collecting the material elastic coefficient of the abnormal motor bearing retainer, performing correlation analysis on the material elastic coefficient and the abnormal frequency index of the bearing retainer, and generating the stiffness abnormal frequency index of the abnormal motor bearing retainer;

[0057] The hardness of the retainer will also contribute to the noise to a certain extent. When it is harder, the frequency value of the contribution is higher, and when it is softer, the frequency value of the contribution is lower.

[0058] Material elastic coefficient k, bearing retainer abnormal frequency index Perform correlation analysis to generate an abnormal frequency index of the stiffness of abnormal motor bearing retainers , the formula based on is:

[0059] in, It is the abnormal frequency index of the stiffness of the abnormal motor bearing retainer. The abnormal frequency index of stiffness is used to reflect the influence of the material hardness of the motor bearing retainer on the vibration frequency.

[0060] Step 4, performing correlation analysis on abnormal motor bearing parameters and the number of rolling elements, and generating a rolling element abnormal frequency index;

[0061] Correlation analysis of abnormal motor bearing parameters and rolling element quantity is performed to generate rolling element abnormal frequency index , the formula based on is:

[0062] in, It is the rolling element abnormal frequency index, which is used to reflect the abnormal characteristic frequency caused by the abnormal rolling element between the inner and outer rings of the bearing. The abnormalities of the rolling element include irregular rolling element, uneven distribution of rolling element, and deviation of the rolling element shape from the preset shape.

[0063] Abnormal frequency index of rolling element , Stiffness Abnormal Frequency Index , is the abnormal frequency index of the inner ring of the bearing , Bearing outer ring abnormal frequency index Perform correlation analysis to generate feature set X based on the following formula:

[0064] The feature set X is a set of all abnormal feature frequencies, which is used to reflect all fault frequencies of the bearing;

[0065] Among them, the value ranges of N, W, G, and GD are 1, 2, 3, ..., and the feature set X is used to reflect the bearing abnormality feature frequency set in the motor vibration frequency.

[0066] Step 5: Install an acceleration sensor on the bearing, collect vibration signals, process the vibration signals, apply FFT conversion to the processed time domain vibration signals to obtain frequency domain signals, obtain the spectrum through FFT, and display the relationship between frequency and amplitude;

[0067] Step 6: Collect frequency and amplitude, perform correlation analysis, and generate rolling element abnormality evaluation index , Stiffness Abnormal Assessment Index , Bearing inner ring evaluation index , Bearing outer ring abnormality assessment index ;

[0068] Step 7: Rolling element abnormality evaluation index , Stiffness Abnormal Assessment Index , Bearing inner ring evaluation index , Bearing outer ring abnormality assessment index With fault threshold Perform comparison and output abnormal parts.

[0069] Collection frequency and amplitude , where the amplitude Used to reflect the vibration frequency The vibration amplitude at the time, the subscript represents the corresponding vibration frequency, ,amplitude , perform correlation analysis on the feature set X to generate the rolling element abnormality evaluation index , Stiffness Abnormal Assessment Index , Bearing inner ring evaluation index , Bearing outer ring abnormality assessment index , the formula based on is:

[0070] Among them, rolling element abnormality evaluation index Used to reflect the rolling element failure evaluation index and stiffness abnormality evaluation index Used to reflect the fault assessment index of the bearing cage and the bearing inner ring assessment index Used to reflect the fault assessment index of the inner ring of the bearing and the abnormal assessment index of the outer ring of the bearing Used to reflect the fault assessment index of the bearing outer ring;

[0071] The rolling element abnormality evaluation index, stiffness abnormality evaluation index, bearing inner ring evaluation index, bearing outer ring abnormality evaluation index and fault threshold are compared. Compare, fault threshold It is set to 0.59. The rolling element abnormality evaluation index is used to reflect the abnormality of the rolling element, corresponding to the rolling element part; the stiffness abnormality evaluation index is used to reflect the softness abnormality of the motor bearing retainer, corresponding to the motor bearing retainer part; the bearing inner ring evaluation index is used to reflect the abnormality of the inner ring of the motor rotor bearing, corresponding to the inner ring of the bearing; the bearing outer ring abnormality evaluation index is used to reflect the abnormality of the outer ring of the motor rotor bearing, corresponding to the outer ring of the bearing; the rolling element abnormality evaluation index, stiffness abnormality evaluation index, bearing inner ring evaluation index, and bearing outer ring abnormality evaluation index are respectively compared with the fault threshold Compare, above the fault threshold The higher the index is, the higher the corresponding part is. The higher the value of the rolling element abnormality assessment index, the stiffness abnormality assessment index, the bearing inner ring assessment index, and the bearing outer ring abnormality assessment index is, the higher the degree of failure of the corresponding bearing part is.

[0072] The abnormal point is the pit or crack on the bearing retainer or the inner and outer rings of the bearing, resulting in an asymmetric situation, that is, the failure point.

[0073] See also Figure 2 The present invention also provides a high-precision identification system for asynchronous motor noise sources, which is used to perform a high-precision identification method for asynchronous motor noise sources, including:

[0074] The bearing parameter collection module is used to collect abnormal motor bearing parameters, including bearing inner ring diameter, rolling element diameter, contact angle, and bearing inner ring speed;

[0075] The inner and outer ring abnormal frequency analysis module performs correlation analysis on the inner ring diameter, rolling element diameter, contact angle, and inner ring speed of the bearing to generate the inner and outer ring abnormal frequency index of the bearing

[0076] A retainer parameter collection module is used to collect abnormal motor bearing retainer parameters, the bearing retainer parameters include the inner contact area and the outer contact area of ​​the bearing retainer;

[0077] The bearing retainer abnormal frequency analysis module is used to perform correlation analysis on the speed, inner contact area and outer contact area, and generate the bearing retainer abnormal frequency index

[0078] A retainer material elastic coefficient collection module is used to collect the material elastic coefficient of abnormal motor bearing retainers;

[0079] The stiffness abnormal frequency analysis module is used to perform correlation analysis on the material elastic coefficient and the bearing retainer abnormal frequency index, and generate the stiffness abnormal frequency index of the abnormal motor bearing retainer;

[0080] The rolling element abnormal frequency analysis module performs correlation analysis on abnormal motor bearing parameters and the number of rolling elements, and generates a rolling element abnormal frequency index;

[0081] The signal acquisition module is used to install an acceleration sensor on the bearing, collect vibration signals, process the vibration signals, apply FFT conversion to the processed time-domain vibration signals to obtain frequency-domain signals, obtain the spectrum through FFT, and display the relationship between frequency and amplitude;

[0082] The signal analysis module collects frequency and amplitude, performs correlation analysis on them, and generates a rolling element abnormality evaluation index , Stiffness Abnormal Assessment Index , Bearing inner ring evaluation index , Bearing outer ring abnormality assessment index ;

[0083] Comparison module, rolling element abnormality evaluation index , Stiffness Abnormal Assessment Index , Bearing inner ring evaluation index , Bearing outer ring abnormality assessment index With fault threshold Perform comparison and output abnormal parts.

[0084] The present invention also provides a storage medium on which computer program instructions are stored. When the computer program instructions are executed by a processor, a high-precision identification method for asynchronous motor noise sources is implemented.

[0085] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0086] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0087] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0088] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A high-precision identification method for asynchronous motor noise sources, used to identify abnormal noise in asynchronous motor bearings, characterized in that: The specific steps include: S1. Collect abnormal motor bearing parameters, including bearing inner ring diameter, rolling element diameter, contact angle, and bearing inner ring speed, perform correlation analysis on the bearing inner ring diameter, rolling element diameter, contact angle, and bearing inner ring speed, and generate abnormal frequency indexes of bearing inner and outer rings; S2, collecting abnormal motor bearing retainer parameters, wherein the bearing retainer parameters include the inner contact area and the outer contact area of ​​the bearing retainer, performing correlation analysis on the rotation speed, the inner contact area and the outer contact area, and generating an abnormal frequency index of the bearing retainer; S3, collecting the material elastic coefficient of the abnormal motor bearing retainer, performing correlation analysis on the material elastic coefficient and the abnormal frequency index of the bearing retainer, and generating the abnormal frequency index of the stiffness of the abnormal motor bearing retainer; S4, performing correlation analysis on abnormal motor bearing parameters and the number of rolling elements, and generating an abnormal frequency index of rolling elements; S5. Install an acceleration sensor on the bearing, collect vibration signals, process the vibration signals, apply FFT conversion to the processed time domain vibration signals to obtain frequency domain signals, obtain a spectrum through FFT, and display the relationship between frequency and amplitude; S6. Collect frequency and amplitude, conduct correlation analysis, and generate rolling element abnormality evaluation index , Stiffness Abnormal Assessment Index , Bearing inner ring evaluation index , Bearing outer ring abnormality assessment index ; S7, rolling element abnormality evaluation index , Stiffness Abnormal Assessment Index , Bearing inner ring evaluation index , Bearing outer ring abnormality assessment index With fault threshold Perform comparison and output abnormal parts.

2. The high-precision identification method for asynchronous motor noise source according to claim 1 is characterized in that: The vibration signal processing includes removing the DC offset in the vibration signal, filtering out the noise frequency other than 10Hz and 10kHz, and noise reduction processing, and calculating the bearing inner ring diameter D, rolling element diameter d, contact angle , bearing inner ring speed Correlation analysis is performed to generate the abnormal frequency index of the inner and outer rings of the bearing. The abnormal frequency index of the inner and outer rings of the bearing includes the abnormal frequency index of the inner ring of the bearing and the abnormal frequency index of the outer ring of the bearing, and the formula based on the formula is: in, The abnormal frequency index of the inner ring of the bearing is used to reflect the characteristic frequency generated on the vibration frequency when an abnormal point appears on the inner ring of the rotor bearing of the motor. is the bearing outer ring abnormal frequency index, which is used to reflect the characteristic frequency generated on the vibration frequency when an abnormal point appears on the outer ring of the rotor bearing of the motor. The bearing inner and outer ring abnormal frequency index is used to reflect the abnormal characteristic frequency of the inner and outer rings of the bearing, where n is the number of rolling elements, and the contact angle It is the contact angle between the rolling element and the inner ring of the bearing.

3. The high-precision identification method for asynchronous motor noise source according to claim 2 is characterized in that: Speed , internal contact area and external contact area Perform correlation analysis to generate bearing retainer abnormal frequency index , the formula based on is: in, It is the abnormal frequency index of the bearing retainer, which is used to reflect the characteristic frequency generated on the vibration frequency when an abnormal point appears on the bearing retainer of the motor.

4. The high-precision identification method for asynchronous motor noise source according to claim 3 is characterized in that: The abnormal point is a hole or crack on the bearing retainer or the inner and outer rings of the bearing, resulting in an asymmetric situation.

5. The high-precision identification method for asynchronous motor noise source according to claim 2 is characterized in that: Material elastic coefficient k, bearing retainer abnormal frequency index Perform correlation analysis to generate an abnormal frequency index of the stiffness of abnormal motor bearing retainers , the formula based on is: in, It is the abnormal frequency index of the stiffness of the abnormal motor bearing retainer. The abnormal frequency index of stiffness is used to reflect the influence of the material hardness of the motor bearing retainer on the vibration frequency.

6. The high-precision identification method of asynchronous motor noise source according to claim 2 is characterized in that: Correlation analysis of abnormal motor bearing parameters and rolling element quantity is performed to generate rolling element abnormal frequency index , the formula based on is: in, It is the rolling element abnormal frequency index, which is used to reflect the abnormal characteristic frequency caused by the abnormal rolling element between the inner and outer rings of the bearing. The abnormalities of the rolling element include irregular rolling element, uneven distribution of rolling element, and deviation of the rolling element shape from the preset shape.

7. The high-precision identification method for asynchronous motor noise source according to any one of claims 4 to 6, characterized in that: Abnormal frequency index of rolling element , Stiffness Abnormal Frequency Index , is the abnormal frequency index of the inner ring of the bearing , Bearing outer ring abnormal frequency index Perform correlation analysis to generate feature set X based on the following formula: Among them, the value range of N, W, G, and GD is 1, 2, 3, ..., and the feature set X is used to reflect the bearing abnormality feature frequency set in the motor vibration frequency.

8. The high-precision identification method for asynchronous motor noise source according to claim 7, characterized in that: Collection frequency and amplitude , where the amplitude Used to reflect the vibration frequency The vibration amplitude at the time of ,amplitude , perform correlation analysis on the feature set X to generate the rolling element abnormality evaluation index , Stiffness Abnormal Assessment Index , Bearing inner ring evaluation index , Bearing outer ring abnormality assessment index , the formula based on is: Among them, rolling element abnormality evaluation index Used to reflect the rolling element failure evaluation index and stiffness abnormality evaluation index Used to reflect the fault assessment index of the bearing cage and the bearing inner ring assessment index Used to reflect the fault assessment index of the inner ring of the bearing and the abnormal assessment index of the outer ring of the bearing Used to reflect the fault assessment index of the bearing outer ring; The rolling element abnormality evaluation index, stiffness abnormality evaluation index, bearing inner ring evaluation index, bearing outer ring abnormality evaluation index and fault threshold are compared. Compare, fault threshold It is set to 0.

59. The rolling element abnormality evaluation index is used to reflect the abnormality of the rolling element, corresponding to the rolling element part; the stiffness abnormality evaluation index is used to reflect the softness abnormality of the motor bearing retainer, corresponding to the motor bearing retainer part; the bearing inner ring evaluation index is used to reflect the abnormality of the inner ring of the motor rotor bearing, corresponding to the inner ring of the bearing; the bearing outer ring abnormality evaluation index is used to reflect the abnormality of the outer ring of the motor rotor bearing, corresponding to the outer ring of the bearing; the rolling element abnormality evaluation index, stiffness abnormality evaluation index, bearing inner ring evaluation index, and bearing outer ring abnormality evaluation index are respectively compared with the fault threshold Compare, above the fault threshold An index of 0 indicates abnormality in the corresponding part.

9. A high-precision identification system for asynchronous motor noise sources, used to execute the high-precision identification method for asynchronous motor noise sources according to claim 1, characterized in that: include: A bearing parameter collection module is used to collect abnormal motor bearing parameters, wherein the bearing parameters include the bearing inner ring diameter, rolling element diameter, contact angle, and bearing inner ring speed; The inner and outer ring abnormal frequency analysis module performs correlation analysis on the inner ring diameter, rolling element diameter, contact angle, and inner ring speed of the bearing to generate the inner and outer ring abnormal frequency index of the bearing A retainer parameter acquisition module, used to acquire abnormal motor bearing retainer parameters, wherein the bearing retainer parameters include an inner contact area and an outer contact area of ​​the bearing retainer; The bearing retainer abnormal frequency analysis module is used to perform correlation analysis on the speed, inner contact area and outer contact area, and generate the bearing retainer abnormal frequency index A retainer material elastic coefficient collection module is used to collect the material elastic coefficient of abnormal motor bearing retainers; The stiffness abnormal frequency analysis module is used to perform correlation analysis on the material elastic coefficient and the bearing retainer abnormal frequency index, and generate the stiffness abnormal frequency index of the abnormal motor bearing retainer; The rolling element abnormal frequency analysis module performs correlation analysis on abnormal motor bearing parameters and the number of rolling elements, and generates a rolling element abnormal frequency index; The signal acquisition module is used to install an acceleration sensor on the bearing, collect vibration signals, process the vibration signals, apply FFT conversion to the processed time-domain vibration signals to obtain frequency-domain signals, obtain the spectrum through FFT, and display the relationship between frequency and amplitude; The signal analysis module collects frequency and amplitude, performs correlation analysis on them, and generates a rolling element abnormality evaluation index , Stiffness Abnormal Assessment Index , Bearing inner ring evaluation index , Bearing outer ring abnormality assessment index ; Comparison module, rolling element abnormality evaluation index , Stiffness Abnormal Assessment Index , Bearing inner ring evaluation index , Bearing outer ring abnormality assessment index With fault threshold Perform comparison and output abnormal parts.

10. A storage medium, characterized in that: The storage medium stores computer program instructions, which implement the method described in claim 1 when executed by a processor.

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