Motor fault diagnosis method for grinding wheel robot

Abstract

The invention discloses a motor fault diagnosis method for a grinding wheel grinding robot, and belongs to the technical field of equipment detection, and the method comprises the following five key steps: firstly, collecting vibration signals at different speeds; secondly, constructing an abnormal energy ratio sequence; then calculating an initial fault value; further counting the energy abnormal frequency under each speed working condition; and finally, the initial fault value is compensated in combination with the abnormal frequency, and an accurate motor fault diagnosis value is finally obtained. According to the method, the vibration signals are collected under three different rotating speed conditions of high speed, medium speed and low speed, and more comprehensive and accurate motor fault evaluation is realized through energy ratio sequence construction and abnormal frequency statistics.

Description

Technical Field

[0001] The invention relates to the technical field of equipment detection, and in particular to a motor fault diagnosis method for a grinding wheel grinding robot. Background Art

[0002] In modern industrial production, grinding wheel robots are an important surface processing equipment, and the stable operation of their motors is crucial to production efficiency and product quality. Traditional motor fault diagnosis methods mainly rely on manual detection and empirical judgment, which have many limitations. Existing technologies usually use vibration signal analysis at a single speed or simple frequency domain feature extraction to identify possible abnormalities in the motor, which is difficult to fully and accurately reflect the actual operating status of the motor.

[0003] Specifically, the existing motor fault diagnosis technology has the following main problems: First, traditional methods mostly use vibration signal analysis under fixed frequency or single working conditions, which cannot fully capture the subtle changes of the motor at different speeds. Second, the existing technology's processing method for vibration signals is relatively simple, usually only focusing on amplitude or spectrum characteristics, ignoring the importance of signal energy distribution. Therefore, the existing technology has the problem of low motor fault diagnosis accuracy. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, a motor fault diagnosis method for a grinding wheel robot provided by the present invention solves the problem of low motor fault diagnosis accuracy in the prior art.

[0005] In order to achieve the above-mentioned invention object, the technical solution adopted by the present invention is: a motor fault diagnosis method for a grinding wheel robot, comprising the following steps:

[0006] S1, respectively collecting vibration signals of the motor of the grinding wheel robot at high speed, medium speed and low speed;

[0007] S2. According to the energy ratios of the vibration signals at high speed, medium speed and low speed, a high-speed abnormal energy ratio sequence, a medium-speed abnormal energy ratio sequence and a low-speed abnormal energy ratio sequence are constructed respectively;

[0008] S3, calculating the initial fault value of the motor according to the high-speed abnormal energy ratio sequence, the medium-speed abnormal energy ratio sequence and the low-speed abnormal energy ratio sequence;

[0009] S4, respectively counting the number of elements in the high-speed abnormal energy ratio sequence, the medium-speed abnormal energy ratio sequence, and the low-speed abnormal energy ratio sequence to obtain the high-speed energy abnormal frequency, the medium-speed energy abnormal frequency, and the low-speed energy abnormal frequency;

[0010] S5. According to the high-speed energy abnormality frequency, the medium-speed energy abnormality frequency and the low-speed energy abnormality frequency, the initial fault value of the motor is compensated to obtain a motor fault diagnosis value.

[0011] Furthermore, in S1, the high speed of the motor is in the range of 3000-6000 rpm, the medium speed of the motor is in the range of 1500-3000 rpm, and the low speed of the motor is in the range of 500-1500 rpm, wherein rpm is a unit of rotation speed.

[0012] Furthermore, the S2 comprises the following sub-steps:

[0013] S21, set a sliding sequence, slide on the vibration signals corresponding to high speed, medium speed and low speed of the same time length respectively, the length of the sliding sequence is N, N is a positive integer, when N is an even number, each time advances N / 2 vibration amplitudes, when N is an odd number, each time advances (N+1) / 2 vibration amplitudes;

[0014] S22, after each sliding, calculating the vibration energy according to the vibration amplitude in the sliding sequence, and constructing a vibration energy sequence;

[0015] S23, calculating the energy ratio of each vibration energy in the vibration energy sequence;

[0016] S24, extracting energy ratio values ​​greater than an energy ratio threshold value under high-speed conditions as high-speed abnormal energy ratio values, and constructing a high-speed abnormal energy ratio value sequence, wherein the energy ratio threshold value is a threshold value set for the energy ratio value;

[0017] S25, extracting the energy ratio value greater than the energy ratio threshold value under the medium speed condition as the medium speed abnormal energy ratio value, and constructing the medium speed abnormal energy ratio value sequence;

[0018] S26. Extract the energy ratio value greater than the energy ratio threshold value in the low-speed condition as the low-speed abnormal energy ratio value, and construct a low-speed abnormal energy ratio value sequence.

[0019] Furthermore, the formula for calculating the vibration energy in S22 is:

[0020] , where E i is the i-th vibration energy in the vibration energy sequence, x i,j is the jth vibration amplitude in the sliding sequence after the i-th sliding, where i and j are positive integers.

[0021] Furthermore, the formula for calculating the energy ratio of each vibration energy in S23 is:

[0022] , where ε i is the energy ratio of the i-th vibration energy, Ei is the i-th vibration energy in the vibration energy sequence, E i-1 is the i-1th vibration energy in the vibration energy sequence, E i+1 is the i+1th vibration energy in the vibration energy sequence, M is the number of vibration energies in the vibration energy sequence, and i is a positive integer.

[0023] Furthermore, S3 includes the following sub-steps:

[0024] S31, calculating the failure coefficient for the high-speed abnormal energy ratio sequence to obtain the high-speed failure coefficient;

[0025] S32, calculating the fault coefficient for the medium-speed abnormal energy ratio sequence to obtain the medium-speed fault coefficient;

[0026] S33, calculating the fault coefficient for the low-speed abnormal energy ratio sequence to obtain the low-speed fault coefficient;

[0027] S34, adding the high-speed fault coefficient, the medium-speed fault coefficient and the low-speed fault coefficient to obtain an initial fault value of the motor.

[0028] Furthermore, the formulas for calculating the failure coefficient in S31, S32, and S33 are all:

[0029] , where γ is the failure coefficient, ε th is the energy ratio threshold, m is a positive integer, ε m is the mth element in the sequence, L is the number of elements in the sequence, and e is a natural constant.

[0030] Furthermore, the S5 comprises the following sub-steps:

[0031] S51, calculating a low-speed compensation coefficient according to a difference between the low-speed energy abnormality frequency and the energy abnormality frequency threshold;

[0032] S52, calculating a medium-speed compensation coefficient according to a difference between the medium-speed energy abnormality frequency and the low-speed energy abnormality frequency;

[0033] S53, calculating a high-speed compensation coefficient according to a difference between the high-speed energy abnormal frequency and the medium-speed energy abnormal frequency;

[0034] S54. Compensate the initial fault value of the motor according to the low-speed compensation coefficient, the medium-speed compensation coefficient and the high-speed compensation coefficient to obtain a motor fault diagnosis value.

[0035] Furthermore, the formula for calculating the low speed compensation coefficient in S51 is:

[0036] , the formula for calculating the medium speed compensation coefficient in S52 is:

[0037] , the formula for calculating the high speed compensation coefficient in S53 is:

[0038] , where θ low is the low speed compensation coefficient, θ middle is the medium speed compensation coefficient, θ high is the high speed compensation coefficient, f low is the frequency of low-speed energy anomaly, f middle is the frequency of abnormal medium-speed energy, f high is the high-speed energy abnormal frequency, f th is the energy abnormal frequency threshold set for low-speed conditions, C is the denominator coefficient, C is greater than 0, and | | is the absolute value.

[0039] Furthermore, the compensation formula in S54 is:

[0040] , where Y is the motor fault diagnosis value, y is the motor initial fault value, θ low is the low speed compensation coefficient, θ middle is the medium speed compensation coefficient, θ high is the high speed compensation coefficient.

[0041] In summary, the beneficial effects of the present invention are:

[0042] 1. The present invention can capture subtle anomalies in the operation of the motor more comprehensively and accurately by comprehensively collecting vibration signals under three working conditions: high speed, medium speed and low speed, and analyzing the energy ratio sequence under each speed. Compared with the traditional single working condition diagnosis method, the present invention improves the accuracy and reliability of motor fault diagnosis.

[0043] 2. The present invention extracts energy ratios of vibration signals at high speed, medium speed and low speed respectively, thereby screening out abnormal energy ratios and deeply analyzing signal energy distribution, thereby comprehensively reflecting the operating characteristics of the motor at different speeds.

[0044] 3. The present invention calculates the initial fault value of the motor according to the abnormal energy ratio sequence at high speed, medium speed and low speed, and then compensates the initial fault value of the motor according to the abnormal energy frequency at high speed, medium speed and low speed, considers the energy abnormality and the frequency of occurrence, comprehensively evaluates the motor fault situation, and improves the accuracy of fault diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 The present invention is a flow chart of a motor fault diagnosis method for a grinding wheel robot. DETAILED DESCRIPTION

[0046] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0047] like Figure 1 As shown, a motor fault diagnosis method for a grinding wheel robot comprises the following steps:

[0048] S1. Collect vibration signals: respectively collect vibration signals of the motor of the grinding wheel robot at high speed, medium speed and low speed;

[0049] S2. Constructing abnormal energy ratio sequences: constructing high-speed abnormal energy ratio sequences, medium-speed abnormal energy ratio sequences and low-speed abnormal energy ratio sequences respectively according to the energy ratios of the vibration signals at high speed, medium speed and low speed;

[0050] S3, calculating the initial fault value of the motor: calculating the initial fault value of the motor according to the high-speed abnormal energy ratio sequence, the medium-speed abnormal energy ratio sequence and the low-speed abnormal energy ratio sequence;

[0051] S4. Count the energy anomaly frequency: Count the number of elements in the high-speed anomaly energy ratio sequence, the medium-speed anomaly energy ratio sequence and the low-speed anomaly energy ratio sequence respectively to obtain the high-speed energy anomaly frequency, the medium-speed energy anomaly frequency and the low-speed energy anomaly frequency, wherein the high-speed energy anomaly frequency is equal to the number of elements in the high-speed anomaly energy ratio sequence, the medium-speed energy anomaly frequency is equal to the number of elements in the medium-speed anomaly energy ratio sequence, and the low-speed energy anomaly frequency is equal to the number of elements in the low-speed anomaly energy ratio sequence;

[0052] S5. Compensating the initial fault value of the motor: According to the high-speed energy abnormality frequency, the medium-speed energy abnormality frequency and the low-speed energy abnormality frequency, the initial fault value of the motor is compensated to obtain a motor fault diagnosis value.

[0053] In this embodiment, the high speed of the motor in S1 is in the range of 3000-6000 rpm, the medium speed of the motor is in the range of 1500-3000 rpm, and the low speed of the motor is in the range of 500-1500 rpm, wherein rpm is the unit of rotation speed.

[0054] In this embodiment, S2 includes the following sub-steps:

[0055] S21, set a sliding sequence, slide on the vibration signals corresponding to high speed, medium speed and low speed of the same time length respectively, the length of the sliding sequence is N, N is a positive integer, when N is an even number, each time advances N / 2 vibration amplitudes, when N is an odd number, each time advances (N+1) / 2 vibration amplitudes;

[0056] For example: the high-speed vibration signal is [0.1, 0.2, 0.15, 0.3, 0.25, 0.4, 0.35, 0.5], N=4 (even number), the first slide: [0.1, 0.2, 0.15, 0.3], the second slide: [0.15, 0.3, 0.25, 0.4], the third slide: [0.25, 0.4, 0.35, 0.5];

[0057] S22, after each sliding, calculating the vibration energy according to the vibration amplitude in the sliding sequence, and constructing a vibration energy sequence;

[0058] S23, calculating the energy ratio of each vibration energy in the vibration energy sequence;

[0059] S24, extracting energy ratio values ​​greater than an energy ratio threshold value under high-speed conditions as high-speed abnormal energy ratio values, and constructing a high-speed abnormal energy ratio value sequence, wherein the energy ratio threshold value is a threshold value set for the energy ratio value;

[0060] Step S24 is aimed at the energy ratio of each vibration energy in the vibration energy sequence under high speed conditions;

[0061] S25, extracting the energy ratio value greater than the energy ratio threshold value under the medium speed condition as the medium speed abnormal energy ratio value, and constructing the medium speed abnormal energy ratio value sequence;

[0062] Step S25 is aimed at the energy ratio of each vibration energy in the vibration energy sequence at medium speed;

[0063] S26. Extract the energy ratio value greater than the energy ratio threshold value in the low-speed condition as the low-speed abnormal energy ratio value, and construct a low-speed abnormal energy ratio value sequence.

[0064] Step S26 is aimed at the energy ratio of each vibration energy in the vibration energy sequence under low speed conditions.

[0065] When setting the sliding sequence, the present invention advances N / 2 or (N+1) / 2 vibration amplitudes each time to ensure signal continuity while avoiding completely repeated sampling. By slightly staggering the sampling windows, subtle features that may be missed by completely overlapping windows can be captured.

[0066] In the present invention, there are three kinds of vibration signals, namely, high speed, medium speed and low speed, and therefore, there are also three vibration energy sequences.

[0067] In this embodiment, the formula for calculating the vibration energy in S22 is:

[0068] , where E i is the i-th vibration energy in the vibration energy sequence, x i,j is the jth vibration amplitude in the sliding sequence after the i-th sliding, where i and j are positive integers.

[0069] In this embodiment, the formula for calculating the energy ratio of each vibration energy in S23 is:

[0070] , where ε i is the energy ratio of the i-th vibration energy, E i is the i-th vibration energy in the vibration energy sequence, E i-1 is the i-1th vibration energy in the vibration energy sequence, E i+1 is the i+1th vibration energy in the vibration energy sequence, M is the number of vibration energies in the vibration energy sequence, and i is a positive integer.

[0071] The present invention counts the vibration energy corresponding to the sliding sequence after each sliding, reflecting the vibration condition of the signal, and then compares each vibration energy with the mean value of the vibration energy and the neighborhood vibration energy E i-1 and E i+1 By comparison, the energy ratio is obtained to reflect the energy bulge.

[0072] When calculating the energy ratio of the first vibration energy in the vibration energy sequence, there is only one neighborhood vibration energy E i+1 Therefore, only the energy of each vibration, the mean value of the vibration energy, and the neighborhood vibration energy E are considered. i+1 When calculating the energy ratio of the last vibration energy in the vibration energy sequence, there is only one neighborhood vibration energy E i-1 Therefore, only the energy of each vibration, the mean value of the vibration energy, and the neighborhood vibration energy E are considered. i-1 ratio.

[0073] In this embodiment, S3 includes the following sub-steps:

[0074] S31, calculating the failure coefficient for the high-speed abnormal energy ratio sequence to obtain the high-speed failure coefficient;

[0075] S32, calculating the fault coefficient for the medium-speed abnormal energy ratio sequence to obtain the medium-speed fault coefficient;

[0076] S33, calculating the fault coefficient for the low-speed abnormal energy ratio sequence to obtain the low-speed fault coefficient;

[0077] S34, adding the high-speed fault coefficient, the medium-speed fault coefficient and the low-speed fault coefficient to obtain an initial fault value of the motor.

[0078] In this embodiment, the formulas for calculating the fault coefficient in S31, S32, and S33 are all:

[0079] , where γ is the failure coefficient, ε th is the energy ratio threshold, m is a positive integer, ε m is the mth element in the sequence, L is the number of elements in the sequence, and e is a natural constant.

[0080] The present invention calculates the fault coefficient according to the difference between each abnormal energy ratio in the sequence and the energy ratio threshold. When the difference is larger, the abnormality of the abnormal energy ratio is larger and more significant compared with the energy of other parts. The present invention also sets an enhancement coefficient. , further enhancing the abnormal situation so that the more significant energy part has a more significant failure coefficient.

[0081] In this embodiment, the energy ratio values ​​obtained through step S23 at high speed are used to construct a high-speed energy ratio sequence, the energy ratio values ​​obtained through step S23 at medium speed are used to construct a medium-speed energy ratio sequence, and the energy ratio values ​​obtained through step S23 at low speed are used to construct a low-speed energy ratio sequence; through step S24, high-speed abnormal energy ratios are screened from the high-speed energy ratio sequence to construct a high-speed abnormal energy ratio sequence, through step S25, medium-speed abnormal energy ratios are screened from the medium-speed energy ratio sequence to construct a medium-speed abnormal energy ratio sequence, and through step S26, low-speed abnormal energy ratios are screened from the low-speed energy ratio sequence to construct a low-speed abnormal energy ratio sequence.

[0082] In this embodiment, the energy ratio threshold is set to 1.5 times the average energy ratio of the sequence. For the high-speed case, the energy ratio threshold is 1.5 times the average energy ratio of the high-speed energy ratio sequence, named the high-speed energy ratio threshold; for the medium-speed case, the energy ratio threshold is 1.5 times the average energy ratio of the medium-speed energy ratio sequence, named the medium-speed energy ratio threshold; for the low-speed case, the energy ratio threshold is 1.5 times the average energy ratio of the low-speed energy ratio sequence, named the low-speed energy ratio threshold. Therefore, in the fault coefficient formula, when the sequence is a high-speed abnormal energy ratio sequence, the energy ratio threshold is the high-speed energy ratio threshold; when the sequence is a medium-speed abnormal energy ratio sequence, the energy ratio threshold is the medium-speed energy ratio threshold, and when the sequence is a low-speed abnormal energy ratio sequence, the energy ratio threshold is the low-speed energy ratio threshold. At the same time, the energy ratio threshold in S24 is the high-speed energy ratio threshold, the energy ratio threshold in S25 is the medium-speed energy ratio threshold, and the energy ratio threshold in S26 is the low-speed energy ratio threshold.

[0083] In this embodiment, the energy ratio threshold of the same magnitude may be set for the three situations of high speed, medium speed and low speed.

[0084] In this embodiment, S5 includes the following sub-steps:

[0085] S51, calculating a low-speed compensation coefficient according to a difference between the low-speed energy abnormality frequency and the energy abnormality frequency threshold;

[0086] S52, calculating a medium-speed compensation coefficient according to a difference between the medium-speed energy abnormality frequency and the low-speed energy abnormality frequency;

[0087] S53, calculating a high-speed compensation coefficient according to a difference between the high-speed energy abnormal frequency and the medium-speed energy abnormal frequency;

[0088] S54. Compensate the initial fault value of the motor according to the low-speed compensation coefficient, the medium-speed compensation coefficient and the high-speed compensation coefficient to obtain a motor fault diagnosis value.

[0089] In this embodiment, the energy abnormality frequency threshold is the threshold of the energy abnormality frequency set for low-speed conditions. This value can be set specifically based on experience or needs. When the fault detection accuracy requirement is high, the energy abnormality frequency threshold can be set to be less than or equal to 5. When the fault detection accuracy requirement is low, the energy abnormality frequency threshold can be set to be greater than 5.

[0090] In this embodiment, the formula for calculating the low speed compensation coefficient in S51 is:

[0091] , the formula for calculating the medium speed compensation coefficient in S52 is:

[0092] , the formula for calculating the high speed compensation coefficient in S53 is:

[0093] , where θ low is the low speed compensation coefficient, θ middle is the medium speed compensation coefficient, θ high is the high speed compensation coefficient, f low is the low-speed energy abnormal frequency, f middle is the frequency of medium-speed energy anomaly, f high is the high-speed energy abnormal frequency, f th is the energy abnormal frequency threshold set for low-speed conditions, C is the denominator coefficient, C is greater than 0, and | | is the absolute value.

[0094] In this embodiment, the compensation formula in S54 is:

[0095] , where Y is the motor fault diagnosis value, y is the motor initial fault value, θlow is the low speed compensation coefficient, θ middle is the medium speed compensation coefficient, θ high is the high speed compensation coefficient.

[0096] The vibration signal itself will be affected by other components. Therefore, some energy anomalies are affected by other noises. In order to eliminate the influence of other vibrations and further improve the fault diagnosis accuracy, the present invention first calculates the low-speed compensation coefficient according to the difference between the low-speed energy anomaly frequency and the energy anomaly frequency threshold. When the low-speed energy anomaly frequency is less than the energy anomaly frequency threshold, the low-speed compensation coefficient is negative, and the motor failure probability is low. When the low-speed energy anomaly frequency is greater than the energy anomaly frequency threshold, the low-speed compensation coefficient is positive, and the motor failure probability is high. At medium and high speeds, when the motor itself fails, As the speed increases, the energy abnormality frequency should be greater. If the energy abnormality frequency decreases as the speed increases, the probability of motor failure is small, and it is a vibration abnormality caused by other vibrations. Therefore, the present invention calculates the medium-speed compensation coefficient according to the difference between the medium-speed energy abnormality frequency and the low-speed energy abnormality frequency, and calculates the high-speed compensation coefficient according to the difference between the high-speed energy abnormality frequency and the medium-speed energy abnormality frequency, reflecting whether the number of abnormal energy ratios increases with the increase of rotation speed under different speed conditions. If it is a motor failure, the number of abnormal energy ratios should increase with the increase of rotation speed.

[0097] The present invention combines a low-speed compensation coefficient, a medium-speed compensation coefficient and a high-speed compensation coefficient to compensate for an initial fault value of a motor, thereby improving the accuracy of motor fault diagnosis.

[0098] The present invention can capture subtle anomalies in the operation of the motor more comprehensively and accurately by comprehensively collecting vibration signals under three working conditions: high speed, medium speed and low speed, and analyzing the energy ratio sequence under each speed. Compared with the traditional single working condition diagnosis method, the present invention improves the accuracy and reliability of motor fault diagnosis.

[0099] The present invention extracts energy ratios of vibration signals at high speed, medium speed and low speed respectively, thereby screening out abnormal energy ratios, deeply analyzing signal energy distribution, and thus comprehensively reflecting the operating characteristics of the motor at different speeds.

[0100] The present invention calculates the initial fault value of the motor according to the abnormal energy ratio sequence at high speed, medium speed and low speed, and then compensates the initial fault value of the motor according to the energy abnormality frequency at high speed, medium speed and low speed, considers the energy abnormality and the frequency of occurrence, comprehensively evaluates the motor fault situation, and improves the accuracy of fault diagnosis.

[0101] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A motor fault diagnosis method for a grinding wheel robot, characterized in that: The following steps are involved: S1, respectively collecting vibration signals of the motor of the grinding wheel robot at high speed, medium speed and low speed; S2. According to the energy ratios of the vibration signals at high speed, medium speed and low speed, a high-speed abnormal energy ratio sequence, a medium-speed abnormal energy ratio sequence and a low-speed abnormal energy ratio sequence are constructed respectively; S3, calculating the initial fault value of the motor according to the high-speed abnormal energy ratio sequence, the medium-speed abnormal energy ratio sequence and the low-speed abnormal energy ratio sequence; S4, respectively counting the number of elements in the high-speed abnormal energy ratio sequence, the medium-speed abnormal energy ratio sequence, and the low-speed abnormal energy ratio sequence to obtain the high-speed energy abnormal frequency, the medium-speed energy abnormal frequency, and the low-speed energy abnormal frequency; S5. According to the high-speed energy abnormality frequency, the medium-speed energy abnormality frequency and the low-speed energy abnormality frequency, the initial fault value of the motor is compensated to obtain a motor fault diagnosis value.

2. The motor fault diagnosis method of the grinding wheel robot according to claim 1, characterized in that: In the S1, the high speed of the motor is in the range of 3000-6000 rpm, the medium speed of the motor is in the range of 1500-3000 rpm, and the low speed of the motor is in the range of 500-1500 rpm, wherein rpm is the unit of rotation speed.

3. The motor fault diagnosis method of the grinding wheel robot according to claim 1, characterized in that: The S2 comprises the following sub-steps: S21, set a sliding sequence, slide on the vibration signals corresponding to high speed, medium speed and low speed of the same time length respectively, the length of the sliding sequence is N, N is a positive integer, when N is an even number, each time advances N / 2 vibration amplitudes, when N is an odd number, each time advances (N+1) / 2 vibration amplitudes; S22, after each sliding, calculating the vibration energy according to the vibration amplitude in the sliding sequence, and constructing a vibration energy sequence; S23, calculating the energy ratio of each vibration energy in the vibration energy sequence; S24, extracting energy ratio values ​​greater than an energy ratio threshold value under high-speed conditions as high-speed abnormal energy ratio values, and constructing a high-speed abnormal energy ratio value sequence, wherein the energy ratio threshold value is a threshold value set for the energy ratio value; S25, extracting the energy ratio value greater than the energy ratio threshold value under the medium speed condition as the medium speed abnormal energy ratio value, and constructing the medium speed abnormal energy ratio value sequence; S26. Extract the energy ratio value greater than the energy ratio threshold value in the low-speed condition as the low-speed abnormal energy ratio value, and construct a low-speed abnormal energy ratio value sequence.

4. The motor fault diagnosis method of the grinding wheel robot according to claim 3 is characterized in that: The formula for calculating the vibration energy in S22 is: , where E i is the i-th vibration energy in the vibration energy sequence, x i,j is the jth vibration amplitude in the sliding sequence after the i-th sliding, where i and j are positive integers.

5. The motor fault diagnosis method of the grinding wheel robot according to claim 3 is characterized in that: The formula for calculating the energy ratio of each vibration energy in S23 is: , where ε i is the energy ratio of the i-th vibration energy, E i is the i-th vibration energy in the vibration energy sequence, E i-1 is the i-1th vibration energy in the vibration energy sequence, E i+1 is the i+1th vibration energy in the vibration energy sequence, M is the number of vibration energies in the vibration energy sequence, and i is a positive integer.

6. The motor fault diagnosis method of the grinding wheel robot according to claim 1, characterized in that: The S3 comprises the following sub-steps: S31, calculating the failure coefficient for the high-speed abnormal energy ratio sequence to obtain the high-speed failure coefficient; S32, calculating the fault coefficient for the medium-speed abnormal energy ratio sequence to obtain the medium-speed fault coefficient; S33, calculating the fault coefficient for the low-speed abnormal energy ratio sequence to obtain the low-speed fault coefficient; S34, adding the high-speed fault coefficient, the medium-speed fault coefficient and the low-speed fault coefficient to obtain an initial fault value of the motor.

7. The motor fault diagnosis method of the grinding wheel robot according to claim 6, characterized in that: The formulas for calculating the failure coefficient in S31, S32, and S33 are all: , where γ is the failure coefficient, ε th is the energy ratio threshold, m is a positive integer, ε m is the mth element in the sequence, L is the number of elements in the sequence, and e is a natural constant.

8. The motor fault diagnosis method of the grinding wheel robot according to claim 1, characterized in that: The S5 comprises the following sub-steps: S51, calculating a low-speed compensation coefficient according to a difference between the low-speed energy abnormality frequency and the energy abnormality frequency threshold; S52, calculating a medium-speed compensation coefficient according to a difference between the medium-speed energy abnormality frequency and the low-speed energy abnormality frequency; S53, calculating a high-speed compensation coefficient according to a difference between the high-speed energy abnormal frequency and the medium-speed energy abnormal frequency; S54. Compensate the initial fault value of the motor according to the low-speed compensation coefficient, the medium-speed compensation coefficient and the high-speed compensation coefficient to obtain a motor fault diagnosis value.

9. The motor fault diagnosis method of the grinding wheel robot according to claim 8, characterized in that: The formula for calculating the low speed compensation coefficient in S51 is: , the formula for calculating the medium speed compensation coefficient in S52 is: , the formula for calculating the high speed compensation coefficient in S53 is: , where θ low is the low speed compensation coefficient, θ middle is the medium speed compensation coefficient, θ high is the high speed compensation coefficient, f low is the low-speed energy abnormal frequency, f middle is the frequency of medium-speed energy anomaly, f high is the high-speed energy abnormal frequency, f th is the energy abnormal frequency threshold set for low-speed conditions, C is the denominator coefficient, C is greater than 0, and | | is the absolute value.

10. The motor fault diagnosis method of the grinding wheel robot according to claim 8, characterized in that: The compensation formula in S54 is: , where Y is the motor fault diagnosis value, y is the motor initial fault value, θ low is the low speed compensation coefficient, θ middle is the medium speed compensation coefficient, θ high is the high speed compensation coefficient.

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