CN116413595A - Method and device for detecting eccentric rotor of synchronous reluctance motor based on vibration test - Google Patents

Abstract

The invention discloses a method and a device for detecting an eccentric rotor of a synchronous reluctance motor based on vibration test, wherein the method comprises the following steps: the method comprises the steps of performing operation test processing on a synchronous reluctance motor under different working conditions and different vibration frequencies to obtain rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor under different working conditions and different vibration frequencies; constructing a synchronous reluctance motor vibration model based on a neural network algorithm, and training the synchronous reluctance motor vibration model based on the neural network algorithm by utilizing rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor at different vibration frequencies under different working conditions to obtain a trained synchronous reluctance motor vibration model based on the neural network algorithm; and acquiring vibration amplitude data of the target synchronous electromagnetic motor under different frequencies, and inputting the vibration amplitude data of the target synchronous electromagnetic motor under different frequencies into the trained synchronous reluctance motor vibration model based on the neural network algorithm to obtain the working condition and the rotor eccentric distance of the target synchronous electromagnetic motor.

Description

A detection method of synchronous reluctance motor eccentric rotor based on vibration test and its device

technical field

The invention relates to the technical field of motors, in particular to a method and device for detecting an eccentric rotor of a synchronous reluctance motor based on vibration testing.

Background technique

In order to obtain better electromagnetic performance, the air gap length of the synchronous reluctance motor is smaller than other types of motors, generally 0.3-0.5mm. However, in the process of motor production and daily use, rotor eccentricity may occur, that is, the center of the rotor deviates from the center of the motor, or the center of the rotor deviates from the center of rotation of the motor. At this time, it will inevitably lead to uneven distribution of air gap length on the outer surface of the rotor, which will affect the performance of the motor. In severe cases, it may cause friction between the rotor and stator of the motor, and even damage the motor.

The traditional motor rotor eccentric state detection generally adopts the stator three-phase current detection method, or measures the air gap magnetic field through the magnetic induction sensor. The above two methods have certain difficulties in operation: the design air gap length of the synchronous reluctance motor is small, the rotor eccentricity within the allowable range of error has limited influence on the electromagnetic performance of the motor, and the detection effect of the stator current is not good; at the same time, The air gap is located between the stator and the rotor, and its length is generally extremely small, so it is difficult to place the sensor, so it is impossible to accurately measure the magnetic density value.

The rotor eccentricity of the synchronous reluctance motor is generally divided into static eccentricity and dynamic eccentricity. In these two eccentric states, the air gap between the stator and the rotor is not evenly distributed, thus generating or even aggravating the rotor in the air gap. unbalanced magnetic pull phenomenon. The electromagnetic force generated in the air gap acts on the stator slot and is transmitted to the motor casing through the stator slot, which will cause irregular and severe vibration of the motor casing.

Contents of the invention

The invention provides a method and device for detecting the eccentric rotor of a synchronous reluctance motor based on vibration testing, so as to solve the technical problems of low accuracy and difficult operation of the existing motor rotor eccentric detection technology.

An embodiment of the present invention provides a method for detecting an eccentric rotor of a synchronous reluctance motor based on a vibration test, including:

By performing operation test processing on the synchronous reluctance motor at different vibration frequencies under different working conditions, the rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor at different vibration frequencies under different working conditions are obtained;

Construct a synchronous reluctance motor vibration model based on a neural network algorithm, and use the rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor at different vibration frequencies under different operating conditions to analyze the synchronous reluctance motor based on a neural network algorithm. The vibration model of the resistance motor is trained, and the trained vibration model of the synchronous reluctance motor based on the neural network algorithm is obtained;

Obtaining the vibration amplitude data of the target synchronous electromagnetic motor at different frequencies, and inputting the vibration amplitude data of the target synchronous electromagnetic motor at different frequencies into the trained synchronous reluctance motor vibration model based on the neural network algorithm, The working condition and rotor eccentric distance of the target synchronous electromagnetic motor are obtained.

Preferably, the working conditions include no-eccentric working conditions, static eccentric working conditions and dynamic eccentric working conditions.

Preferably, the acquisition of the vibration amplitude data of the target synchronous electromagnetic motor at different frequencies includes:

During the operation of the target electromagnetic motor, one or more acceleration sensors arranged on the shell of the target electromagnetic motor are acquired in real time to collect vibration amplitude data of the target synchronous electromagnetic motor at different frequencies in real time.

Preferably, the operation test processing of the synchronous reluctance motor at different vibration frequencies under different working conditions is obtained to obtain the rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor at different vibration frequencies under different working conditions, including :

Construct the vibration simulation model of the synchronous reluctance motor, and carry out the operation test process to the synchronous reluctance motor through the vibration simulation model of the synchronous reluctance motor, and obtain the rotor of the synchronous reluctance motor at different vibration frequencies under different working conditions Eccentric distance and vibration amplitude data.

Preferably, the vibration simulation model of the synchronous reluctance motor uses the electromagnetic force data under different working conditions as the input of the vibration simulation model of the synchronous reluctance motor, and simultaneously sets one or more acceleration The vibration amplitude data collected by the sensor is used as the output of the vibration simulation model of the synchronous reluctance motor.

Preferably, it also includes: calculating and acquiring electromagnetic force data under different working conditions, which specifically includes:

Build the first synchronous reluctance motor model under no eccentric condition, the second synchronous reluctance motor model under static eccentric condition and the third synchronous reluctance motor model under dynamic eccentric condition;

Using the first synchronous reluctance motor model to analyze the air gap magnetic density distribution of the synchronous reluctance motor, obtain the first air gap magnetic density data under the condition of no eccentricity, and according to the first air gap Calculating a first electromagnetic force density from the magnetic density data, and using the first electromagnetic force density to calculate the first electromagnetic force data under no-eccentric working conditions;

Using the second synchronous reluctance motor model to analyze the air gap magnetic density distribution of the synchronous reluctance motor, obtain the second air gap magnetic density data under the static eccentric condition, and according to the second air gap Calculating a second electromagnetic force density from the magnetic density data, and using the second electromagnetic force density to calculate second electromagnetic force data under static eccentric conditions;

Using the third synchronous reluctance motor model to analyze the air gap magnetic density distribution of the synchronous reluctance motor, obtain the third air gap magnetic density data under dynamic eccentric conditions, and according to the third air gap The magnetic density data is used to calculate a third electromagnetic force density, and the third electromagnetic force data is calculated under a dynamic eccentric working condition by using the third electromagnetic force density.

An embodiment of the present invention provides a detection device for an eccentric rotor of a synchronous reluctance motor based on a vibration test, including:

The acquisition module is used to obtain the rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor at different vibration frequencies under different working conditions by performing operation test processing on the synchronous reluctance motor at different vibration frequencies under different working conditions;

The construction and training module is used to construct a synchronous reluctance motor vibration model based on a neural network algorithm, and use the rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor at different vibration frequencies under different working conditions to analyze the The synchronous reluctance motor vibration model based on the neural network algorithm is trained, and the trained synchronous reluctance motor vibration model based on the neural network algorithm is obtained;

The detection module is used to obtain the vibration amplitude data of the target synchronous electromagnetic motor at different frequencies, and input the vibration amplitude data of the target synchronous electromagnetic motor at different frequencies into the trained synchronous reluctance based on neural network algorithm In the motor vibration model, the working condition and rotor eccentric distance of the target synchronous electromagnetic motor are obtained.

Preferably, the working conditions include no-eccentric working conditions, static eccentric working conditions and dynamic eccentric working conditions.

Preferably, the detection module is specifically used to acquire in real time the vibration of the target synchronous electromagnetic motor at different frequencies by one or more acceleration sensors disposed on the shell of the target electromagnetic motor in real time during the operation of the target electromagnetic motor Amplitude data.

Preferably, the acquisition module is specifically used to construct a vibration simulation model of the synchronous reluctance motor, and perform operation test processing on the synchronous reluctance motor through the vibration simulation model of the synchronous reluctance motor to obtain different vibrations under different working conditions Rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor in frequency.

The beneficial effects of the present invention are: firstly, compared with placing the magnetic induction sensor in the narrow air gap, the operation difficulty of placing the acceleration sensor on the motor shell is relatively low; secondly, the magnetic density distribution of the air gap caused by the rotor eccentricity is not In general, a large number of magnetic induction sensors need to be placed to measure the magnetic field strength in the outer circumference of the rotor, but only three acceleration sensors are needed in the technical solution of the present invention, which greatly reduces the cost and difficulty of testing; third, the vibration amplitude of the motor casing is compared to Compared with the changes of other parameters (such as air gap magnetic density, stator current, etc.), it has more intuitive and obvious characteristics, which is convenient for state observation and data collection.

Description of drawings

Fig. 1 is a kind of detection method flow chart of synchronous reluctance motor eccentric rotor based on vibration test provided by the present invention;

2 is a schematic diagram of a detection device for an eccentric rotor of a synchronous reluctance motor based on a vibration test provided by the present invention;

Fig. 3 is a schematic diagram of static eccentricity and dynamic eccentricity of the synchronous reluctance motor rotor provided by the present invention;

Fig. 4 is the schematic diagram of the static eccentric working condition provided by the present invention;

Fig. 5 is a schematic diagram of a dynamic eccentric working condition provided by the present invention;

Fig. 6 is a comparison diagram of the air gap magnetic density when the rotor position is 0° provided by the present invention;

Fig. 7 is a comparison diagram of air gap tightness when the rotor position provided by the present invention is 90°;

Fig. 8 is a distribution diagram of electromagnetic force in the air gap under the condition that the rotor is not eccentric provided by the present invention;

Fig. 9 is a distribution diagram of electromagnetic force in the air gap under the static eccentric state of the rotor provided by the present invention;

Fig. 10 is a distribution diagram of electromagnetic force in the air gap under the dynamic eccentric state of the rotor provided by the present invention;

Fig. 11 is a comparison diagram of the vibration amplitude of the motor casing under the eccentric state of the rotor of the synchronous reluctance motor provided by the present invention;

Fig. 12 is a structural model diagram of the neural network algorithm provided by the present invention.

Detailed ways

It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In the following description, use of suffixes such as 'module', 'part' or 'unit' for denoting elements is only to facilitate description of the present invention and has no specific meaning by itself. Therefore, 'module', 'part' or 'unit' may be used in combination.

Fig. 1 is a kind of detection method flow chart of synchronous reluctance motor eccentric rotor based on vibration test provided by the present invention, as shown in Fig. 1, described method can comprise:

Step S101: Obtain the rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor at different vibration frequencies under different working conditions by performing operation test processing on the synchronous reluctance motor at different vibration frequencies under different working conditions;

Step S102: Construct a synchronous reluctance motor vibration model based on a neural network algorithm, and use the rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor at different vibration frequencies under different working conditions to analyze the vibration model based on the neural network algorithm. The synchronous reluctance motor vibration model is trained, and the trained synchronous reluctance motor vibration model based on the neural network algorithm is obtained;

Step S103: Obtain the vibration amplitude data of the target synchronous electromagnetic motor at different frequencies, and input the vibration amplitude data of the target synchronous electromagnetic motor at different frequencies into the trained synchronous reluctance motor vibration based on neural network algorithm In the model, the working condition and rotor eccentric distance of the target synchronous electromagnetic motor are obtained.

Wherein, the working conditions include no-eccentric working conditions, static eccentric working conditions and dynamic eccentric working conditions.

Specifically, the acquisition of the vibration amplitude data of the target synchronous electromagnetic motor at different frequencies includes: during the operation of the target electromagnetic motor, obtaining in real time the data collected by one or more acceleration sensors arranged on the shell of the target electromagnetic motor in real time. Vibration amplitude data of the target synchronous electromagnetic motor at different frequencies.

Further, by performing operation test processing on the synchronous reluctance motor at different vibration frequencies under different working conditions, the rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor at different vibration frequencies under different working conditions include : Construct the vibration simulation model of synchronous reluctance motor, and carry out operation test process to synchronous reluctance motor through the vibration simulation model of described synchronous reluctance motor, obtain the synchronous reluctance motor on different vibration frequencies under different working conditions Rotor eccentric distance and vibration amplitude data.

Wherein, the vibration simulation model of the synchronous reluctance motor is to use the electromagnetic force data under different working conditions as the input of the vibration simulation model of the synchronous reluctance motor, and simultaneously set one or more acceleration sensors on the electromagnetic motor shell The collected vibration amplitude data is used as the output of the vibration simulation model of the synchronous reluctance motor.

The embodiment of the present invention also includes: calculating and obtaining the electromagnetic force data under different working conditions, which specifically includes: respectively building the first synchronous reluctance motor model under the non-eccentric working condition and the second synchronous reluctance motor model under the static eccentric working condition The motor model and the third synchronous reluctance motor model under the dynamic eccentric working condition; the air gap flux density distribution of the synchronous reluctance motor is analyzed by using the first synchronous reluctance motor model, and it is obtained that under the non-eccentric working condition The first air-gap magnetic density data, and calculate the first electromagnetic force density according to the first air-gap magnetic density data, and use the first electromagnetic force density to calculate the first electromagnetic force data under no eccentric working conditions; Using the second synchronous reluctance motor model to analyze the air gap magnetic density distribution of the synchronous reluctance motor, obtain the second air gap magnetic density data under the static eccentric condition, and according to the second air gap Calculate the second electromagnetic force density from the flux density data, and use the second electromagnetic force density to calculate the second electromagnetic force data under static eccentric conditions; use the third synchronous reluctance motor model to analyze the synchronous reluctance motor Analyze the air-gap flux density distribution to obtain the third air-gap flux-density data under dynamic eccentric conditions, and calculate the third electromagnetic force density according to the third air-gap flux-density data, and use the third electromagnetic Force density calculates the third electromagnetic force data under dynamic eccentric conditions.

Figure 2 is a schematic diagram of a detection device for an eccentric rotor of a synchronous reluctance motor based on a vibration test provided by the present invention. As shown in Figure 2, it includes: an acquisition module for synchronous magnetic The resistance motor is subjected to running test processing, and the rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor on different vibration frequencies under different working conditions are obtained; the construction and training module is used to construct the synchronous reluctance motor vibration based on the neural network algorithm model, and use the rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor at different vibration frequencies under different working conditions to train the synchronous reluctance motor vibration model based on the neural network algorithm, and obtain a trained Synchronous reluctance motor vibration model based on neural network algorithm; detection module, used to obtain the vibration amplitude data of the target synchronous electromagnetic motor at different frequencies, and input the vibration amplitude data of the target synchronous electromagnetic motor at different frequencies to the In the trained synchronous reluctance motor vibration model based on the neural network algorithm, the working condition and rotor eccentric distance of the target synchronous electromagnetic motor are obtained.

Wherein, the working conditions include no-eccentric working conditions, static eccentric working conditions and dynamic eccentric working conditions.

Further, the detection module is specifically used to acquire in real time the vibration of the target synchronous electromagnetic motor at different frequencies by one or more acceleration sensors disposed on the shell of the target electromagnetic motor in real time during operation of the target electromagnetic motor Amplitude data.

Wherein, the acquisition module is specifically used to construct a vibration simulation model of the synchronous reluctance motor, and perform operation test processing on the synchronous reluctance motor through the vibration simulation model of the synchronous reluctance motor, and obtain different vibration frequencies under different working conditions The rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor mentioned above.

Below in conjunction with accompanying drawing 3-accompanying drawing 12, the technical content of the present invention is explained

During the operation of the motor, the uneven air gap magnetic density distribution in the air gap will generate electromagnetic force in the tangential and radial directions of the rotor, which will act on the inner wall of the stator slot and be transmitted to the rotor through the transmission of the stator. motor housing, and eventually motor vibrations on the motor housing.

When the motor rotor is running normally, its rotation center is concentric with the stator. At this time, the air gap between the rotor and the stator is evenly distributed, and the corresponding electromagnetic force is also uniform. When the rotor is installed improperly, or the rotor is worn due to long-term work, or other faults occur, the center of the rotor will be offset. At this time, the distribution of the air gap between the rotor and the stator will become uneven, and the corresponding electromagnetic The force is also uneven, which has a certain impact on the vibration amplitude and regularity of the motor casing. By observing and recording the vibration amplitude and regularity of the motor under normal working conditions, and comparing it with the vibration amplitude and regularity of the rotor eccentric working condition, the rotor eccentric fault can be detected by the motor vibration test method. Specific steps are as follows:

(1) For the eccentricity fault of the synchronous reluctance motor rotor, the radial section of the motor is taken as the research object, as shown in Figure 3, the rotor eccentricity condition is divided into two types: static eccentricity and dynamic eccentricity, among which: static eccentricity condition Under the condition of dynamic eccentricity, the center of the rotor deviates from the center of the motor (that is, the center of the stator), and the rotor rotates around the center of the rotor. (that is, the center of the stator circle) for circular motion;

(2) Build the electromagnetic model of the motor under the conditions of no eccentricity, static eccentricity and dynamic eccentricity of the rotor. First, analyze the air gap magnetic density distribution of the motor. Since the motor air gap magnetic density B _g can be obtained by the following formula:

Among them, U _s represents the magnetomotive force of the stator, U _r represents the magnetomotive force of the rotor, L _g represents the length of the air gap, and μ ₀ represents the vacuum magnetic permeability.

It can be seen from Fig. 3 that under the condition of no eccentricity of the rotor, the length L _g of the air gap is evenly distributed, that is, the length of the air gap is equal everywhere in the space;

Under the condition of static eccentricity, the length L _g of the air gap is unevenly distributed, and the length of the space is not equal, and does not change with the rotation of the rotor, that is, L _g (θ _s ) remains unchanged, and θ _s is the reference coordinate of the stator The position of each point on the lower circle is set, and the distance of rotor eccentricity is δ, as shown in Figure 4, then:

L _g (θ _s )＝L _g -δcos(θ _s )

Under the condition of dynamic eccentricity, the length L _g of the air gap is not uniformly distributed, and the length of the space is not equal, and changes with the rotation of the rotor. θ _m is the rotation angle of the rotor. Similarly, the eccentric distance of the rotor is set as δ, as shown in Figure 5, then:

L _g (θ _s )＝L _g -δcos(θ _s -θ _m )

When the air gap length changes, the distribution of the air gap magnetic density will change. Figure 6 shows the air gap magnetic density distribution of the motor electromagnetic model under the conditions of no eccentricity, static eccentricity and dynamic eccentricity when the rotor rotation angle is 0 Finite element simulation results (at this time, the air gap magnetic density distribution of static eccentricity and dynamic eccentricity is the same); Fig. 7 shows the air gap of the motor electromagnetic model under the conditions of no eccentricity, static eccentricity and dynamic eccentricity when the rotor rotation angle is 90°. Finite element simulation results of gap flux density distribution.

(3) Assume that at any moment, the rotor rotation angle is θ _m , that is, the rotor position is θ _m ; at this time, the magnetic density at any point in the air gap is represented by B _g (θ _s ). At this position, decompose B _g (θ _s ) along the radial and tangential directions of this point on the rotor, then:

B _r (θ _s )＝B _g (θ _s )cosθ _m

Bθ(θ _s )＝B _g (θ _s )sinθ _m

According to the air gap magnetic density obtained above, the electromagnetic force density in the air gap can be solved by using the Maxwell stress tensor formula, such as:

Among them, σ is the electromagnetic force density in the radial direction of the rotor, τ is the electromagnetic force density in the tangential direction of the rotor, B _r is the component of the air gap magnetic density in the radial direction of the rotor, and B _θ is the air gap magnetic density in Component in the tangential direction of the rotor.

Since the tangential component of the air-gap flux density is generally much smaller than the radial component of the air-gap flux density, the tangential component can be omitted in the analysis, thus the electromagnetic force density f _m can be obtained as:

According to the electromagnetic force density f _m and the area S _slot on the inner wall of the stator slot where it acts, the electromagnetic force distribution acting on the inner diameter circle of the stator can be calculated. The electromagnetic force acts on the inner wall of the stator slot on the inner diameter of the stator, and through the transmission of the stator silicon steel sheet, finally acts on the motor casing to generate vibration.

Figure 8 shows the time-space distribution diagram of the electromagnetic force in the air gap of the electromagnetic model of the motor under the condition of no eccentricity; Figure 9 shows the time-space distribution of the electromagnetic force in the air gap of the electromagnetic model of the motor under the static eccentric condition Fig. 10 shows the time-space distribution diagram of the electromagnetic force in the air gap of the electromagnetic model of the motor under the dynamic eccentric condition.

(4) In the vibration module of the finite element simulation, the electromagnetic force obtained above is used as the model input, acts on the slot opening of the motor stator, and the acceleration of each point of the motor casing is used as the output to measure the vibration amplitude of the motor. A comparison of the vibration amplitudes at each vibration frequency of the motor under the conditions of no eccentricity, static eccentricity and dynamic eccentricity can be obtained as shown in FIG. 9 .

(5) As shown in Figure 11, collect and organize the above rotor eccentricity distance and the corresponding vibration data of the motor casing, and build a synchronous reluctance motor vibration model based on the neural network algorithm, as shown in Figure 12, realize the algorithm for the rotor eccentricity distance, Self-learning of data such as the vibration amplitude of the motor casing.

(6) Measure the difference between the experimental value and the simulated value through the motor bench test. First, securely fix the motor test bench, randomly select 1-3 points on the motor casing, and place acceleration sensors respectively to measure the vibration amplitude of the motor at each frequency (the experiment here is only measured under the condition of no eccentricity) vibration amplitude of the motor casing).

(7) Use the neural network algorithm to further collect and organize the vibration data of the motor casing obtained in the bench test, and compare and self-learn with the vibration amplitude data of the motor casing obtained in the finite element simulation under non-eccentric conditions.

(8) By measuring the vibration amplitude of the motor casing at different speeds and frequencies, and automatically comparing it with the empirical data in the system, the analysis shows that the motor is working in the non-eccentric working condition, static eccentric working condition or dynamic eccentric working condition .

The preferred embodiments of the present invention have been described above with reference to the accompanying drawings, and the scope of rights of the present invention is not limited thereby. Any modifications, equivalent replacements and improvements made by those skilled in the art without departing from the scope and essence of the present invention shall fall within the scope of rights of the present invention.

Claims (10)

1. The method for detecting the eccentric rotor of the synchronous reluctance motor based on the vibration test is characterized by comprising the following steps of:

the method comprises the steps of performing operation test processing on a synchronous reluctance motor under different working conditions and different vibration frequencies to obtain rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor under different working conditions and different vibration frequencies;

constructing a synchronous reluctance motor vibration model based on a neural network algorithm, and training the synchronous reluctance motor vibration model based on the neural network algorithm by utilizing rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor at different vibration frequencies under different working conditions to obtain a trained synchronous reluctance motor vibration model based on the neural network algorithm;

and acquiring vibration amplitude data of the target synchronous electromagnetic motor under different frequencies, and inputting the vibration amplitude data of the target synchronous electromagnetic motor under different frequencies into the trained synchronous reluctance motor vibration model based on the neural network algorithm to obtain the working condition and the rotor eccentric distance of the target synchronous electromagnetic motor.

2. The method of claim 1, wherein the operating conditions include a no-eccentricity operating condition, a static-eccentricity operating condition, and a dynamic-eccentricity operating condition.

3. The method of claim 1, wherein the acquiring vibration amplitude data for the target synchronous electromagnetic motor at different frequencies comprises:

and during the operation of the target electromagnetic motor, acquiring one or more acceleration sensors arranged on the shell of the target electromagnetic motor in real time to acquire vibration amplitude data of the target synchronous electromagnetic motor under different frequencies.

4. A method according to claim 3, wherein the obtaining rotor eccentricity and vibration amplitude data of the synchronous reluctance motor at different vibration frequencies under different working conditions by performing operation test processing on the synchronous reluctance motor at different vibration frequencies under different working conditions comprises:

and constructing a vibration simulation model of the synchronous reluctance motor, and performing operation test processing on the synchronous reluctance motor through the vibration simulation model of the synchronous reluctance motor to obtain rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor under different vibration frequencies under different working conditions.

5. The method according to claim 4, wherein the vibration simulation model of the synchronous reluctance motor takes electromagnetic force data under different working conditions as input of the vibration simulation model of the synchronous reluctance motor, and takes vibration amplitude data acquired by one or more acceleration sensors arranged on a shell of the electromagnetic motor as output of the vibration simulation model of the synchronous reluctance motor.

6. The method as recited in claim 5, further comprising: calculating and acquiring electromagnetic force data under different working conditions, wherein the electromagnetic force data specifically comprises:

respectively building a first synchronous reluctance motor model under a non-eccentric working condition, a second synchronous reluctance motor model under a static eccentric working condition and a third synchronous reluctance motor model under a dynamic eccentric working condition;

analyzing the air gap flux density distribution of the synchronous reluctance motor by using the first synchronous reluctance motor model to obtain first air gap flux density data under the non-eccentric working condition, calculating first electromagnetic force density according to the first air gap flux density data, and calculating first electromagnetic force data under the non-eccentric working condition by using the first electromagnetic force density;

analyzing the air gap flux density distribution of the synchronous reluctance motor by using the second synchronous reluctance motor model to obtain second air gap flux density data under a static eccentric working condition, calculating second electromagnetic force density according to the second air gap flux density data, and calculating second electromagnetic force data under the static eccentric working condition by using the second electromagnetic force density;

and analyzing the air gap flux density distribution of the synchronous reluctance motor by using the third synchronous reluctance motor model to obtain third air gap flux density data under a dynamic eccentric working condition, calculating third electromagnetic force density according to the third air gap flux density data, and calculating third electromagnetic force data under the dynamic eccentric working condition by using the third electromagnetic force density.

7. Detection device of synchronous reluctance motor eccentric rotor based on vibration test, characterized by comprising:

the acquisition module is used for obtaining rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor under different working conditions and different vibration frequencies by carrying out operation test treatment on the synchronous reluctance motor under different working conditions and different vibration frequencies;

the building and training module is used for building a synchronous reluctance motor vibration model based on a neural network algorithm, and training the synchronous reluctance motor vibration model based on the neural network algorithm by utilizing rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor under different vibration frequencies under different working conditions to obtain a trained synchronous reluctance motor vibration model based on the neural network algorithm;

the detection module is used for acquiring vibration amplitude data of the target synchronous electromagnetic motor under different frequencies, and inputting the vibration amplitude data of the target synchronous electromagnetic motor under different frequencies into the trained synchronous reluctance motor vibration model based on the neural network algorithm to obtain working conditions and rotor eccentric distance of the target synchronous electromagnetic motor.

8. The apparatus of claim 7, wherein the operating conditions comprise a no-eccentricity operating condition, a static-eccentricity operating condition, and a dynamic-eccentricity operating condition.

9. The device according to claim 7, wherein the detection module is specifically configured to acquire, in real time, vibration amplitude data of the target synchronous electromagnetic motor at different frequencies during operation of the target electromagnetic motor, wherein the one or more acceleration sensors are provided on the target electromagnetic motor housing.

10. The device of claim 9, wherein the acquisition module is specifically configured to construct a vibration simulation model of the synchronous reluctance motor, and perform operation test processing on the synchronous reluctance motor through the vibration simulation model of the synchronous reluctance motor, so as to obtain rotor eccentric distance and vibration amplitude data of the synchronous reluctance motor at different vibration frequencies under different working conditions.

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