Micromotor resonance risk analysis method and system

Abstract

The invention discloses a micromotor resonance risk analysis method and system, belongs to the technical field of micromotor manufacturing, analyzes and diagnoses the resonance risk of a micromotor by combining electromagnetic excitation simulation, modal simulation and sound physical quantity acquisition, and is used for avoiding the frequency band where the micromotor generates resonance and reducing noise. And the design of a micromotor mounting structure is guided, the equipment investment cost is low, and the application range is wide.

Description

Technical Field

[0001] The present invention relates to the technical field of micromotor manufacturing, and in particular to a method and system for analyzing resonance risk of a micromotor. Background Art

[0002] Noise control in micromotors remains a long-standing technical challenge. Resonant noise caused by the coupling of electromagnetic excitation and mechanical vibration is a particularly prominent issue, particularly with the trend toward higher speeds and miniaturization. Industry practice has shown that when the natural frequency of a micromotor's structure coincides with the frequency of the electromagnetic force, the resonance effect can dramatically increase the sound pressure level. This nonlinear noise amplification phenomenon seriously impacts device quality. Current mainstream resonance risk analysis methods in the industry generally focus on modal simulation or single-dimensional experimental testing. While finite element simulation can calculate the structural natural frequency, its oversimplified boundary conditions prevent it from accurately reflecting the dynamic characteristics under actual assembly constraints, and it cannot quantify the specific impact of frequency offsets on noise energy. Experimental modal testing relies on high-precision NVH equipment such as shakers and accelerometer arrays. Full-band modal analysis of a single micromotor is time-consuming and requires significant equipment investment, making this method difficult to popularize among small and medium-sized motor manufacturers. Furthermore, existing methods only capture discrete values ​​of the natural frequency. They cannot construct frequency-noise correlation models to determine the degree of resonance risk, nor can they scientifically define a safe natural frequency threshold. This often leads to excessive frequency avoidance or ineffective optimization during the design phase. To address the above issues, the present invention combines rotating machinery excitation theory with data analysis. By actively changing the distribution of natural frequencies through structural weight changes, the changes in noise spectrum characteristics are simultaneously collected to establish a multi-dimensional frequency-sound pressure response map. This not only realizes the visual identification of resonance intervals and quantitative evaluation of noise energy, but also provides a low-cost solution to micromotor resonance. Summary of the Invention

[0003] The purpose of the present invention is to provide a method for analyzing the resonance risk of a micromotor, which solves the problems of the existing motor resonance analysis methods that the methods consider few factors and have high investment costs.

[0004] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is as follows:

[0005] A method for analyzing the resonance risk of a micromotor comprises the following steps:

[0006] S1, the natural frequency f1 of the micromotor in the original state is calculated by the micromotor modal simulation model;

[0007] S2. Perform multiple weighting treatments on the mounting hole position of the micromotor model with different weights, and simulate and calculate the natural frequency f of the micromotor after multiple weighting treatments. n , n is a natural number greater than 2;

[0008] S3. Perform noise testing on the micromotor sample and collect the noise sound pressure level I1 and octave O1 output by the micromotor sample;

[0009] S4, according to the weighting process in step S2, the micromotor sample is weighted, the noise test of the weighted micromotor is performed, and the noise sound pressure level I output by the weighted micromotor sample is collected. n with Octave O n ;

[0010] S5, according to the natural frequency f1 of the micromotor and the natural frequency f of the micromotor after counterweight n , the noise sound pressure level I1 and octave O1 output by the micromotor sample, and the noise sound pressure level I1 output by the micromotor sample after counterweighting n with Octave O n Synthesize the change curve of natural frequency f and noise value O;

[0011] S6. Simulate the electromagnetic force of the micromotor to obtain the excitation frequency data of the micromotor. In steps S3 and S4, obtain the noise sound pressure level of the micromotor. Calculate the ratio of the sound pressure level S to the total sound pressure at different excitation frequencies, arrange them in descending order, and take the top three frequency bands.

[0012] S7. Compare and analyze the changing curves of the natural frequency f and the noise value O with the first three frequency bands to obtain treatment countermeasures;

[0013] S8. Countermeasures: Countermeasure 1: Perform structural optimization based on the micromotor modal simulation model, so that the optimized micromotor natural frequency needs to be less than the first three-order frequency band H1, or greater than the first three-order frequency band H2, where H1 and H2 are defined as: Under different counterweights, the corresponding simulation calculated natural frequency f n The ratio K of the corresponding sound pressure value to the sound pressure value at the origin is 10%, which can eliminate the noise impact caused by resonance; Countermeasure 2: Optimize the harmonic content of the winding current or adjust the pole-slot combination to weaken the electromagnetic force; Countermeasure 3: No treatment is required, and the resonance risk of the micromotor is analyzed and diagnosed by combining electromagnetic excitation simulation, modal simulation and sound physical quantity acquisition to avoid the frequency band where the micromotor resonates, reduce noise, and guide the design of the micromotor mounting structure.

[0014] Preferably, in step S3, the testing tool for collecting the noise of the micromotor for testing is a sound level meter, a microphone, an exciter or a sound sensor, which is simple to use and easy to arrange.

[0015] Furthermore, in step S2, the counterweight processing method is to cut out the mounting hole position of the micromotor model and add weights, thereby changing the weight by reducing the supporting material. When cutting, avoid the central connection area between the mounting hole and the micromotor model to reduce the impact on the support stiffness. The order of changing the counterweight is to first add the counterweight block to complete the test and then cut and reduce the weight. Through the counterweight adjustment, a sample guidance can be provided for the optimization design of the micromotor mounting structure.

[0016] Preferably, in step S2 and step S4, the number of micromotor samples is not less than 3, so as to reduce random errors and improve the accuracy of test data.

[0017] Furthermore, in step S1, the error calculation method of the micromotor modal simulation result is:

[0018] The natural frequency f of the micromotor after counterweight n With the noise value O n The frequency H corresponding to the peak value of the change curve 实测 , the theoretical fundamental frequency H of the corresponding order 理论 ,error If E>10%, the micromotor simulation model needs to be modified and the change curve needs to be resynthesized. If E≤10%, the synthesized frequency and noise value change curves can be directly used for micromotor resonance data analysis and diagnosis to determine the reliability of the data.

[0019] Furthermore, in step 6, the frequency results of the micromotor modal simulation are combined with the total sound pressure of the noise test and the corresponding noise results of the first three frequency bands to synthesize the micromotor structure natural frequency and total sound pressure, frequency band sound pressure change curve. The synthesis method is: the X-axis data is the natural frequency of the micromotor modal simulation of the first three frequency bands under different weights, and the Y-axis is the sound pressure value obtained by actual measurement of the first three frequency bands under different weights, which is used to determine the optimization direction.

[0020] Furthermore, in step 8, when one or more of the change curves of the natural frequency f, the total sound pressure O, and the sound pressure of the first three harmonic frequencies show a normal distribution, and when the simulation and test results of the micromotor in the original state are within the interval b, the interval b is defined as: H1<b<H2, and the ratio K of the sound pressure value corresponding to H1 or H2 to the sound pressure value at the origin is 10%, then the micromotor has obvious resonance. If the working state of the micromotor in the original state is closer to the peak of the curve, the greater the impact of the resonance on the noise, and the impact amplitude is the difference between the corresponding sound pressure values ​​of the micromotor H1 or H2 in the original state, the main factors affecting the noise of the micromotor are determined, and the optimization direction is provided.

[0021] Furthermore, in step 8, the resonant frequency F is confirmed: if one or more of the sound pressures in the first three frequency bands show a normal distribution as the curve changes with the natural frequency H, and the total sound pressure also shows a normal distribution as the curve changes with the natural frequency H, then the frequency at which the peak value of the frequency band sound pressure and the total sound pressure appears in the curve is the resonant frequency F, indicating the standard for judging the resonant frequency F.

[0022] Furthermore, when the natural frequency of the micromotor in its original state and the test result are within the intervals a and c, aH2, and the method for determining the positions of H1 and H2 is: the ratio K of the sound pressure value corresponding to H1 or H2 to the sound pressure value at the origin is 10%, it is necessary to analyze whether the noise is excited by electromagnetic force;<h1>

[0023] When the ratio of the sound pressure value at the peak of the natural frequency and test noise value curve of the micromotor in its original state to the sound pressure value at the origin is less than 10%, the effect of resonance on the noise is very small. After the natural frequency of the structure is shifted, the noise reduction is limited. At this time, it is necessary to analyze whether the excessive noise is caused by excessive electromagnetic excitation.

[0024] When the natural frequency of the micromotor's original state and the original state of the total sound pressure change curve are in any interval, the degree of resonance at this time is very low, or there is no resonance, then the system damping of the micromotor is large, or the electromagnetic excitation of the motor is too small. Even if the natural frequency completely overlaps with the fundamental frequency of the electromagnetic excitation, no obvious resonance phenomenon will occur. The elimination method can be used to obtain the biggest influencing factor of the micromotor noise.

[0025] A second object of the present invention is to provide a micromotor resonance risk analysis system, which solves the problem of high equipment requirements in existing micromotor resonance analysis systems.

[0026] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is as follows:

[0027] A micromotor resonance risk analysis system is used to implement the micromotor resonance risk analysis method. The system comprises a modal simulation module deployed on a computer and used to calculate the natural frequency of the micromotor; a noise testing device comprising a sound level meter, an exciter, and a spectrum analyzer for collecting noise pressure levels; and a data analysis module for synthesizing a natural frequency-noise curve and outputting resonance countermeasures. The system has low deployment cost, is applicable to a wide range of occasions, and can achieve optimization results.

[0028] The beneficial effects of the present invention are:

[0029] (1) This micromotor resonance risk analysis method integrates modal simulation and noise test data, and actively regulates the natural frequency of the structure by combining controllable counterweight disturbance. It can quickly establish a quantitative correlation between the natural frequency and the noise sound pressure level. By physically changing the natural frequency with the counterweight, a quantifiable resonance risk prediction model is established, which significantly improves the accuracy and efficiency of resonance risk identification. This method uses conventional acoustic test equipment to replace expensive NVH dedicated instruments, and can simultaneously obtain multi-band sound pressure distribution through a single noise spectrum scan, reducing equipment investment costs.

[0030] (2) The analysis method of the micromotor resonance risk is based on the analysis of the frequency-sound pressure response spectrum, which can accurately define the natural frequency safety threshold range, quantify the noise amplification factor caused by resonance, and provide a clear frequency avoidance range and electromagnetic force suppression direction for the micromotor structure optimization design. The installation structure in the experiment can be directly applied to the structural design, avoiding the material waste and extended iteration cycle caused by the traditional trial and error method.

[0031] (3) The analysis method of the micromotor resonance risk can complete all data collection work by using only conventional simulation methods and sound measurement equipment, reducing the investment in equipment and manpower. Compared with traditional modal analysis, it shortens the test time and greatly improves the technical implementation feasibility of small and medium-sized micromotor enterprises. It can be applied in a wide range of areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A flow chart of the method for analyzing the resonance risk of a micromotor provided by the present invention;

[0033] Figure 2 A schematic diagram of the counterweight cutout area of ​​the micromotor resonance risk analysis method provided by the present invention;

[0034] Figure 3 Noise test provided by the present invention - octave sound pressure level and total sound pressure diagram;

[0035] Figure 4 A curve diagram showing the change of the natural frequency based on modal simulation and the test noise value provided by the present invention;

[0036] Figure 5 The natural frequency diagram based on modal simulation provided by the present invention;

[0037] Figure 6 The natural frequency interval distribution diagram based on modal simulation provided by the present invention;

[0038] Figure 7 This is a curve diagram of the change of modal simulation natural frequency and experimental noise value under different fundamental frequencies provided by the present invention. DETAILED DESCRIPTION

[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the application without making any creative efforts shall fall within the scope of protection of the present invention.

[0040] Example 1

[0041] like Figure 1-Figure 7 As shown, this embodiment discloses a method for analyzing the resonance risk of a micromotor, comprising the following steps:

[0042] S1, calculating the natural frequency f1 of the micromotor in the original state by the micromotor modal simulation model, and performing finite element analysis by computer simulation using simulation software such as Ansys software to obtain the natural frequency f1 of the micromotor;

[0043] S2. Perform multiple weighting treatments on the mounting hole position of the micromotor model with different weights, and simulate and calculate the natural frequency f of the micromotor after multiple weighting treatments. n , n is a natural number greater than 2, and the counterweight is achieved by increasing or decreasing the external mass of the micromotor without changing the structure and mass of the micromotor itself, thereby ensuring the stability of the micromotor's operating state and improving the accuracy of the collected data;

[0044] S3. Conduct noise testing on the micromotor sample and collect the noise sound pressure level I1 and octave O1 output by the micromotor sample. The octave is a way to divide the sound frequency range into several frequency bands. In the field of acoustics, in order to facilitate the analysis and research of sound frequencies, the wide frequency range is divided into different frequency bands, and each frequency band is an octave. For example, the audible sound frequency range of the human ear is from 20Hz to 20,000Hz, which is divided into a series of octave bands.

[0045] S4, according to the weighting process in step S2, the micromotor sample is weighted, and the noise test of the weighted micromotor is performed, and the noise sound pressure level I output by the micromotor sample after each weighting is collected. n with Octave O n ;

[0046] S5, according to the natural frequency f1 of the micromotor and the natural frequency f of the micromotor after counterweight n , the noise sound pressure level I1 and octave O1 output by the micromotor sample, and the noise sound pressure level I1 output by the micromotor sample after counterweighting n with Octave O n A curve of the change of the natural frequency H and the noise value O is synthesized, where the natural frequency H is the horizontal axis and the noise value O is the vertical axis;

[0047] S6. Simulate the electromagnetic force of the micromotor to obtain the excitation frequency data of the micromotor. In steps S3 and S4, obtain the noise sound pressure level of the micromotor. Calculate the ratio of the sound pressure level to the total sound pressure at different excitation frequencies, arrange them in order from low to high, and take the top three frequency bands, and name them D1, D2, and D3, respectively.

[0048] S7. Compare and analyze the changing curves of the natural frequency f and the noise value O with the first three frequency bands D1, D2, and D3 to obtain treatment countermeasures;

[0049] S8. Countermeasures: Countermeasure 1: Perform structural optimization based on the micromotor modal simulation model, so that the optimized micromotor natural frequency needs to be less than the first three-order frequency band H1, or greater than the first three-order frequency band H2, where H1 and H2 are defined as: Under different counterweights, the corresponding simulation calculated natural frequency f n The ratio K of the corresponding sound pressure value to the sound pressure value at the origin is 10%, where H1 is located in the low-frequency stage of the rising change curve of the natural frequency f and the noise value O, and H2 is located in the high-frequency stage of the falling change curve, which can eliminate the noise influence caused by resonance; Countermeasure 2: Optimize the harmonic content of the winding current or adjust the pole-slot combination to weaken the electromagnetic force; Countermeasure 3: No treatment is required.

[0050] Among them, sound pressure is the actual fluctuation that describes the air pressure, and the unit is Pa;

[0051] Total sound pressure, the physical superposition result of the effective sound pressure values ​​generated by multiple sound sources at the same point, unit: Pa;

[0052] Sound pressure level, a logarithmic measure of the effective value of the sound pressure of a single sound or a single sound source relative to a reference value, in dB;

[0053] Total sound pressure level, a logarithmic measure of the effective value of the total sound pressure produced by multiple sound sources at the same point, in dB.

[0054] Preferably, in step S3, the test tool for collecting noise of the micromotor for testing is a sound level meter, a microphone, an exciter or a sound sensor, which has low sampling requirements, facilitates optimization analysis in different scenarios, reduces the cost of personnel and equipment, and is suitable for use by small and medium-sized micromotor manufacturers.

[0055] Furthermore, in step S2, the counterweight processing method is to cut out the mounting hole position of the micromotor model and add weights, thereby changing the weight by reducing the supporting material, avoiding the central connection area between the mounting hole and the micromotor model during cutting, and reducing the impact on the support stiffness. The order of changing the counterweight is to first add the counterweight block to complete the test and then cut it out. The counterweight is changed by cutting, and the design of the micromotor mounting structure is completed simultaneously, which reduces the workload of repeated design and ensures that the optimization results can be reproduced in actual production and use, thereby ensuring the accuracy of the implementation of the optimization results.

[0056] Preferably, in step S2 and step S4, the number of micromotor samples is not less than 3. The more data collected, the more accurate the optimization result. Appropriate micromotor samples can be selected for testing according to actual needs.

[0057] Furthermore, in step S1, the error calculation method of the micromotor modal simulation result is:

[0058] The natural frequency f of the micromotor after counterweight n With the noise value O n The frequency H corresponding to the peak value of the change curve 实测 , the theoretical fundamental frequency H of the corresponding order 理论 , If E>10%, the micromotor simulation model needs to be modified and the frequency and noise value change curves need to be resynthesized. If E≤10%, the synthesized frequency and noise value change curves can be directly used for micromotor resonance data analysis and diagnosis, indicating the reliability of the data results.

[0059] Furthermore, in step 6, the frequency results of the micromotor modal simulation are combined with the total sound pressure of the noise test and the corresponding noise results of the first three frequency bands to synthesize the micromotor structure natural frequency and total sound pressure, frequency band sound pressure change curve. The synthesis method is: the data on the X-axis is the natural frequency of the micromotor modal simulation of the first three frequency bands under different weights, and the Y-axis is the value obtained by actual measurement of the first three frequency bands under different weights.

[0060] Furthermore, in step 8, when one or more of the change curves of the natural frequency f, the total sound pressure O, and the sound pressure of the first three harmonic frequencies show a normal distribution, and when the simulation and test results of the micromotor in the original state are within the interval b, the interval b is defined as: H1<b<H2, where H1 and H2 are defined as: under different counterweights, the corresponding simulation calculated natural frequency f nThe ratio K of the corresponding sound pressure value to the sound pressure value at the origin is 10%, where H1 is located in the low-frequency stage of the rising change curve of the natural frequency f and the noise value O, and H2 is located in the high-frequency stage of the falling change curve, indicating that the micromotor has obvious resonance. If the working state of the micromotor in the original state is closer to the peak of the curve, it means that the resonance has a greater impact on the noise. The impact amplitude is the difference in the sound pressure values ​​of the micromotor H1 or H2 in the original state. The noise results of the micromotor are judged by analyzing the data. The normal distribution includes the standard normal distribution and the quasi-normal distribution.

[0061] Furthermore, in step 8, the resonant frequency F is confirmed: if one or more of the sound pressure curves of the first three frequency bands and the natural frequency H show a normal distribution, and the total sound pressure curve and the natural frequency H also show a normal distribution, then the frequency at which the peak value of the frequency band sound pressure and the total sound pressure appears in the curve is the resonant frequency F;

[0062] When the natural frequency of the micromotor in its original state and the test result are within the interval a and c, the intervals a and c are defined as: aH2, where the method for determining the positions of H1 and H2 is: the ratio K of the sound pressure value corresponding to H1 or H2 to the sound pressure value at the origin is 10%, see<h1> Figure 5 , then the degree of resonance at this time is very low, and the impact on noise is very small. After the natural frequency of the structure is offset, the reduction of noise is limited. At this time, it is necessary to analyze whether the noise is generated by electromagnetic force excitation, and obtain the largest influencing factor of the micromotor noise through the elimination method.

[0063] When the peak value of the curve between the natural frequency of the original state of the micromotor and the test noise value is small or has no obvious peak value, the effect of resonance on the noise is very small. After the natural frequency of the structure is offset, the noise reduction is limited. At this time, it is necessary to analyze whether the excessive noise is caused by excessive electromagnetic force excitation.

[0064] When the natural frequency and total sound pressure change curve of the micromotor in its original state is Figure 6 In the shapes of curves 5 and 6, the peak at the fundamental frequency is very small, or there is no obvious peak. The original state of the natural frequency and the total sound pressure change curve is in any interval. At this time, the degree of resonance is very low, or there is no resonance. The system damping of the micromotor is large, or the electromagnetic excitation of the motor is too small. Even if the natural frequency completely overlaps with the fundamental frequency of the electromagnetic excitation, no obvious resonance phenomenon will occur.

[0065] Table 1-1

[0066]

[0067]

[0068] Refer to Table 1-1. Noise data was collected after the micromotor model was weighted up and down to obtain the data in the table.

[0069] See also Figure 4 , the simulation accuracy of the first two natural frequencies corresponding to counterweight 3 are:

[0070] First stage: |1314-1200|÷1200=9.5%

[0071] Second order: |2224-2400|÷2400=7.3%.

[0072] See also Figure 7 The change curves of the total sound pressure of the first two orders and the sound pressure of the first-order frequency band are normally distributed. If the micromotor sample test and test results are between segments 1 and 6, obvious resonance occurs at this time, and the cause of the resonance is the natural frequency resonance of the micromotor structure near the fundamental frequency. The improvement measure is to optimize the motor structure so that the simulated natural frequency of the micromotor avoids the frequency range corresponding to 1 to 6; if the micromotor sample test and test results are between segments 7 and 8, the micromotor does not have obvious resonance at this time, and the micromotor structure does not need to be optimized, meeting the factory requirements.

[0073] This application uses electromagnetic excitation simulation, modal simulation, a simple microphone, and mobile phone audio testing software to complete accurate analysis and diagnosis of resonance risks, thereby accurately analyzing the extent of the impact of resonance on noise, as well as the range of natural frequencies that need to be staggered in modal simulation calculations after structural optimization. It has low requirements for test equipment, a wide range of applicability, and has promotional value.

[0074] Example 2

[0075] This embodiment also discloses a micromotor resonance risk analysis system for implementing a micromotor resonance risk analysis method. The system comprises a modal simulation module deployed on a computer for calculating the natural frequency of the micromotor; a noise testing device comprising a sound level meter, an exciter, and a spectrum analyzer for collecting noise pressure levels; and a data analysis module for synthesizing a natural frequency-noise curve and outputting a resonance countermeasure. The system uses a computer for data collection, processing, and analysis, resulting in high computational efficiency and easy deployment.

[0076] Based on the disclosure and teachings of the above description, those skilled in the art may also make changes and modifications to the above embodiments. Therefore, the present invention is not limited to the specific embodiments disclosed and described above, and any modifications and variations of the present invention should also fall within the scope of protection of the claims of the present invention. In addition, although certain specific terms are used in this description, these terms are only for convenience of description and do not constitute any limitation to the present invention.

Claims

1. A method for analyzing the resonance risk of a micromotor, characterized in that: The following steps are involved: S1, the natural frequency f1 of the micromotor in the original state is calculated by the micromotor modal simulation model; S2. Perform multiple weighting treatments on the mounting hole position of the micromotor model with different weights, and simulate and calculate the natural frequency f of the micromotor after multiple weighting treatments. n , n is a natural number greater than 2; S3. Perform noise testing on the micromotor sample and collect the noise sound pressure level I1 and octave O1 output by the micromotor sample; S4, according to the weighting process in step S2, the micromotor sample is weighted, the noise test of the weighted micromotor is performed, and the noise sound pressure level I output by the weighted micromotor sample is collected. n with Octave O n ; S5, according to the natural frequency f1 of the micromotor and the natural frequency f of the micromotor after counterweight n , the noise sound pressure level I1 and octave O1 output by the micromotor sample, and the noise sound pressure level I1 output by the micromotor sample after counterweighting n with Octave O n Synthesize the change curve of natural frequency F and noise value O; S6. Simulate the electromagnetic force of the micromotor to obtain the excitation frequency data of the micromotor. In steps S3 and S4, obtain the noise sound pressure level of the micromotor. Calculate the ratio of the sound pressure level to the total sound pressure at different excitation frequencies, arrange them in order from low to high, and select the top three frequency bands. S7. Compare and analyze the changing curves of the natural frequency f and the noise value O with the first three frequency bands to obtain treatment countermeasures; S8. Countermeasures: Countermeasure 1: Perform structural optimization based on the micromotor modal simulation model, so that the optimized micromotor natural frequency needs to be less than the first three-order frequency band H1, or greater than the first three-order frequency band H2, where H1 and H2 are defined as: Under different counterweights, the corresponding simulation calculated natural frequency f n The ratio K of the corresponding sound pressure value to the sound pressure value at the origin is 10%, which can eliminate the noise caused by resonance; Countermeasure 2: Optimize the harmonic content of the winding current or adjust the pole-slot match to weaken the electromagnetic force; Countermeasure 3: No treatment is required.

2. The method for analyzing the resonance risk of a micromotor according to claim 1, wherein: In step S3, the testing tool for collecting the noise of the micromotor for testing is a sound level meter, a microphone, an exciter or a sound sensor.

3. The method for analyzing the resonance risk of a micromotor according to claim 1, wherein: In step S2, the counterweight processing method is to cut off the mounting hole position of the micromotor model and add weights, thereby changing the weight by reducing the supporting material. When cutting, avoid the central connection area between the mounting hole and the micromotor model to reduce the impact on the support stiffness. The order of changing the counterweight is to first add the counterweight block to complete the test and then cut off the weight reduction operation.

4. The method for analyzing the resonance risk of a micromotor according to claim 3, wherein: In step S2 and step S4, the number of micromotor samples is no less than 3.

5. The method for analyzing the resonance risk of a micromotor according to claim 1, wherein: The error calculation method of the micromotor modal simulation results in step S1 is: The natural frequency f of the micromotor after counterweight n With the noise value O n The frequency H corresponding to the peak value of the change curve 实测 , the theoretical fundamental frequency H of the corresponding order 理论 ,error If E>10%, the micromotor simulation model needs to be modified and the change curve needs to be resynthesized. If E≤10%, the synthesized frequency and noise value change curves can be directly used for micromotor resonance data analysis and diagnosis.

6. The method for analyzing the resonance risk of a micromotor according to claim 5, wherein: In step 6, the frequency results of the micromotor modal simulation are combined with the total sound pressure of the noise test and the corresponding noise results of the first three frequency bands to synthesize the change curves of the micromotor structure natural frequency, total sound pressure, and frequency band sound pressure. The synthesis method is: the data on the X-axis is the natural frequency of the micromotor modal simulation of the first three frequency bands under different weights, and the Y-axis is the value obtained by actual measurement of the first three frequency bands under different weights.

7. The method for analyzing the resonance risk of a micromotor according to claim 6, wherein: In step 8, when one or more of the change curves of the natural frequency f, the total sound pressure O, and the sound pressure of the first three harmonic frequencies show a normal distribution, and when the simulation and test results of the micromotor in the original state are within interval b, interval b is defined as: H1<b<H2, and the ratio K of the sound pressure value corresponding to H1 or H2 to the sound pressure value at the origin is 10%, then the micromotor has obvious resonance. If the working state of the micromotor in the original state is closer to the peak of the curve, the greater the impact of the resonance on the noise, and the impact amplitude is the difference between the corresponding sound pressure values ​​of the micromotor H1 or H2 in the original state.

8. The method for analyzing the resonance risk of a micromotor according to claim 7, wherein: In step 8, the resonant frequency F is confirmed: if one or more of the sound pressure curves in the first three frequency bands vary with the natural frequency H and the total sound pressure curve also varies with the natural frequency H and shows a normal distribution, then the frequency at which the peak value of the frequency band sound pressure and the total sound pressure appears in the curve is the resonant frequency F.

9. The method for analyzing the resonance risk of a micromotor according to claim 1, wherein: When the natural frequency of the micromotor in its original state and the test result are within the interval a and c, the intervals a and c are defined as: a<H1, c>H2, where the position of H1 and H2 is determined by the ratio K of the sound pressure value corresponding to H1 or H2 to the sound pressure value at the origin is 10%, then it is necessary to analyze whether the noise is excited by electromagnetic force. When the ratio of the sound pressure value at the peak of the natural frequency and test noise value curve of the micromotor in its original state to the sound pressure value at the origin is less than 10%, the effect of resonance on the noise is very small. After the natural frequency of the structure is shifted, the noise reduction is limited. At this time, it is necessary to analyze whether the excessive noise is caused by excessive electromagnetic excitation. When the natural frequency of the micromotor's original state and the original state of the total sound pressure change curve are in any interval, the degree of resonance is very low, or there is no resonance, then the system damping of the micromotor is large, or the electromagnetic excitation of the motor is small, even if the natural frequency completely overlaps with the fundamental frequency of the electromagnetic excitation, no obvious resonance phenomenon will occur.

10. A micromotor resonance risk analysis system, used to implement the micromotor resonance risk analysis method according to any one of claims 1 to 9, characterized in that: Modal simulation module: deployed on a computer, used to calculate the natural frequency of the micromotor; noise testing device: contains a sound level meter, an exciter, and a spectrum analyzer, used to collect noise sound pressure levels; data analysis module: used to synthesize the natural frequency-noise curve and output resonance countermeasures.

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