Second derivative-based asynchronous motor rotor broken bar fault detection method and system

Abstract

The invention discloses an asynchronous motor rotor broken bar fault detection method and system based on a second derivative, and the method comprises the following steps: S1, obtaining a stator current sampling data sequence # imgabs0 # of any phase of an asynchronous motor, the # imgabs1 # being an nth current signal; s2, carrying out fundamental frequency suppression on the stator current sampling data sequence # imgabs2 by using a second derivative, and constructing an edge frequency function sequence # imgabs3 #, wherein # imgabs4 # is the nth edge frequency function; s3, carrying out fast Fourier transform on the side frequency function sequence # imgabs5 # to extract a side frequency characteristic frequency spectrum; and S4, judging whether the asynchronous motor has a rotor broken bar fault or not according to the side frequency characteristic spectrum. The invention aims to simplify signal acquisition required by fault detection and accurately extract the side frequency characteristic frequency spectrum reflecting the rotor broken bar fault so as to accurately diagnose the rotor broken bar fault of the asynchronous motor.

Description

Technical Field

[0001] The present invention relates to the technical field of motor fault detection, and in particular to a rotor broken bar fault detection method and system for an asynchronous motor based on a second-order derivative. Background Art

[0002] Common sideband component detection methods include Park vector transformation, instantaneous power method and fast Fourier transform (FFT). These methods can effectively detect rotor faults to a certain extent. However, Park vector transformation and its improvement strategy are methods based on stator three-phase current signals. The instantaneous power method not only needs to collect stator current signals but also voltage signals, which has high hardware requirements and increases costs. To perform spectrum analysis on motor current, only one-phase current of the motor stator needs to be sampled. By detecting the characteristic spectrum next to the fundamental frequency reflecting the rotor broken bar fault in the current spectrum, that is, the side spectrum, it can be effectively determined whether the rotor has a broken bar fault. Generally, the following approaches are used to detect the side spectrum: First, increase the sampling time length and the number of sampling points to improve the frequency resolution and realize sideband resolution and extraction; however, this method is affected by load fluctuations, the stator current frequency fluctuates, and the FFT application effect deteriorates. Therefore, the sampling time should not be too long, or short-time Fourier transform is used for time-frequency analysis, which increases computing resources and is not conducive to on-site processing and edge computing. Second, suppress or eliminate the fundamental wave to highlight the side spectrum to achieve characteristic side spectrum detection. Existing methods such as adaptive filtering and Wiener filtering to eliminate the influence of fundamental frequency all require data background calculation and processing; while the MUSIC method based on matrix eigenvalue decomposition and the chaotic oscillator algorithm require greater computing resources. Third, the use of time-frequency analysis methods, such as Hillbert transform, wavelet transform, etc., as well as modern AI technology based on vector machines, have high requirements for computing resources and are not conducive to on-site promotion and application. Summary of the invention

[0003] Technical problem to be solved by the present invention: In view of the above-mentioned problems in the prior art, a method and system for detecting a broken rotor bar fault of an asynchronous motor based on a second-order derivative are provided. The present invention aims to simplify the signal acquisition required for fault detection, accurately extract the sideband characteristic spectrum reflecting the broken rotor bar fault, and accurately diagnose the broken rotor bar fault of the asynchronous motor.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is: A method for detecting a rotor broken bar fault of an asynchronous motor based on a second-order derivative comprises the following steps: S1, obtain the stator current sampling data sequence of any phase of the asynchronous motor ,in is the nth current signal; S2, stator current sampling data sequence Using second-order derivatives to suppress fundamental frequency and construct sideband function sequence ,in is the nth sideband function; S3, the sideband function sequence Extract the sideband characteristic spectrum through fast Fourier transform; S4, judging whether the asynchronous motor has a broken rotor bar fault according to the side frequency characteristic spectrum.

[0005] Optionally, in step S2, the stator current sampling data sequence Perform fundamental frequency suppression and construct sideband function sequence include: S2.1, stator current sampling data sequence Digital filtering is performed to suppress random noise; S2.2, stator current sampling data sequence after digital filtering Perform a fast Fourier transform to extract the angular frequency of the fundamental frequency and spectrum amplitude ; S2.3, stator current sampling data sequence Perform a second-order difference operation to find the second-order derivative of the current; S2.4, insert zero values ​​into the sequence of the second-order derivative of the current and adjust the sequence length to make it consistent with the original stator current sampling data sequence Align, then multiply by the scale parameter Get a new sequence ,in is the angular frequency of the fundamental frequency; S2.5, according to Constructing a sequence of sideband functions ,in is the nth sideband function, is the nth current signal, for In the new sequence Align the corresponding signals in the middle.

[0006] Optionally, the digital filtering in step S2.1 refers to digital filtering using a moving average filtering method.

[0007] Optionally, the function expression of the second-order derivative of the current obtained by performing the second-order difference operation in step S2.3 is: , In the above formula, is the second-order derivative of the current, For the A current signal, For the A current signal, is the nth current signal, is the sampling period.

[0008] Optionally, in step S3, the sideband function sequence Extracting sideband feature spectra through fast Fourier transform includes: S3.1, sideband function sequence Obtain the spectrum amplitude of the sideband function through fast Fourier transform ; S3.2, from the spectrum amplitude Determine the left frequency The corresponding left spectrum frequency and right frequency The corresponding right spectrum frequency , according to the spectrum frequency on the left and the right spectrum frequency Calculate the left spectrum amplitude and the right spectrum amplitude as the sideband characteristic spectrum.

[0009] Optionally, step S3.2 includes: S3.2.1, from the spectrum amplitude Based on and Determine the left frequency and right frequency ,in is the fundamental frequency, is the slip rate of the asynchronous motor; S3.2.2, according to and Calculate the left frequency The corresponding left spectrum frequency and right frequency The corresponding right spectrum frequency ; S3.2.3, according to the spectrum frequency on the left and the right spectrum frequency , calculate the spectrum amplitude on the left according to the following formula and the right spectrum amplitude As the sideband eigenspectrum: , , In the above formula, is the spectrum amplitude Center left frequency The spectrum amplitude of is the spectrum amplitude Center right frequency The spectrum amplitude of is the angular frequency of the fundamental frequency.

[0010] Optionally, in step S4, judging whether the asynchronous motor has a broken rotor bar fault according to the sideband characteristic spectrum includes: and the right spectrum amplitude The larger of the two ; Calculate the larger value The spectrum amplitude of the fundamental frequency The dB difference between , if the larger value The spectrum amplitude of the fundamental frequency The dB difference between If the value is greater than the preset threshold, it is determined that the asynchronous motor has a broken rotor bar fault.

[0011] In addition, the present invention also provides a rotor broken bar fault detection system for an asynchronous motor based on second-order derivatives, comprising a microprocessor and a memory connected to each other, wherein the microprocessor is programmed or configured to execute the rotor broken bar fault detection method for an asynchronous motor based on second-order derivatives.

[0012] In addition, the present invention also provides a computer-readable storage medium, in which a computer program or instruction is stored. The computer program or instruction is programmed or configured to execute the rotor broken bar fault detection method of the asynchronous motor based on the second-order derivative through a processor.

[0013] In addition, the present invention also provides a computer program product, comprising a computer program or instructions, wherein the computer program or instructions are programmed or configured to execute the rotor broken bar fault detection method of an asynchronous motor based on second-order derivatives through a processor.

[0014] Compared with the prior art, the present invention mainly has the following advantages: 1. The present invention is based on the stator current sampling data sequence of any phase of the asynchronous motor The broken rotor bar fault detection of the asynchronous motor can be realized, the amount of data required is small, the acquisition is simple and convenient, and the signal acquisition required for fault detection can be simplified.

[0015] 2. Broken rotor bars of asynchronous motors are one of the common motor faults. When a motor has a broken rotor bar fault, the frequency of the motor stator current is The characteristic component of is the fundamental frequency (base frequency), is the slip rate. In the spectrum of the stator current, the fundamental frequency The left frequency appears on both sides and right frequency Therefore, the present invention can effectively extract the fault feature and accurately detect the motor rotor fault by judging whether the asynchronous motor has a broken rotor bar fault according to the sideband characteristic spectrum.

[0016] 3. Due to the left frequency of the usual fault characteristic frequency , right frequency With base frequency Very close, directly use the conventional fast Fourier transform (FFT) algorithm for spectrum analysis, because the base frequency The sideband is relatively strong, the sideband is weak, and there is spectrum leakage. The sideband is annihilated by the baseband, resulting in the sideband being unable to be detected. At the same time, the fast Fourier transform FFT can only be effectively applied when the stator current and the load remain relatively stable. Therefore, the current sampling time should not be too long. It is not feasible to improve the frequency resolution by increasing the sampling data length to achieve the purpose of distinguishing and detecting the sideband. The present invention includes a stator current sampling data sequence. Using second-order derivatives to suppress fundamental frequency and construct sideband function sequence , and then the sideband function sequence The sideband characteristic spectrum is extracted by fast Fourier transform, and the sideband characteristic spectrum reflecting the broken rotor bar fault can be accurately extracted by fundamental frequency suppression to improve the motor current sampling signal processing algorithm. The sideband characteristic spectrum of the broken rotor bar fault is extracted with high precision to accurately diagnose the broken rotor bar fault of the asynchronous motor and realize high-sensitivity monitoring of the broken rotor bar fault.

[0017] 4. The present invention has the advantages of simplicity and low computational complexity, can achieve high-precision monitoring of broken rotor bar faults and is particularly beneficial for on-site edge computing scenarios with limited computing power. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Schematic diagram of the basic flow of the method of the embodiment of the present invention.

[0019] Figure 2 Detailed flowchart of the method of the embodiment of the present invention.

[0020] Figure 3 This is a spectrum diagram directly obtained from the sampled data in an embodiment of the present invention.

[0021] Figure 4 In the embodiment of the present invention, the sideband function sequence is based on The spectrum diagram obtained by the spectrum.

[0022] Figure 5 The left frequency in the embodiment of the present invention signal spectrum. DETAILED DESCRIPTION

[0023] The detection principle of the rotor bar fault detection method of the asynchronous motor based on the second-order derivative of the present invention is as follows: the motor current is subjected to spectrum analysis, and the fault characteristic spectrum is extracted to effectively determine whether the motor has stator winding turn-to-turn fault, rotor bar fault, bearing fault, etc. For the rotor bar fault, the stator current spectrum characteristic is the frequency of the stator current near the base frequency. and The side spectrum of , is the base frequency (power supply frequency), is the slip rate; due to the fundamental frequency The signal is very strong, the characteristic frequency signal is relatively weak, there is spectrum leakage in the fast Fourier transform FFT, the characteristic spectrum next to the fundamental frequency is annihilated, it is difficult to detect the characteristic spectrum, and the monitoring sensitivity does not meet the requirements. For this reason, the monitoring data is preprocessed, the fundamental frequency is suppressed first, the characteristic frequency signal is highlighted, and then the fast Fourier transform FFT is performed to extract the characteristic spectrum reflecting the rotor broken bar fault, so as to accurately diagnose the motor rotor broken bar fault. The present invention will be further described in detail in conjunction with the embodiments below.

[0024] like Figure 1 As shown, the rotor broken bar fault detection method of an asynchronous motor based on the second-order derivative of this embodiment includes the following steps: S1, obtain the stator current sampling data sequence of any phase of the asynchronous motor ,in is the nth current signal; S2, stator current sampling data sequence Using second-order derivatives to suppress fundamental frequency and construct sideband function sequence ,in is the nth sideband function; S3, the sideband function sequence Extract the sideband characteristic spectrum through fast Fourier transform; S4, judging whether the asynchronous motor has a broken rotor bar fault according to the side frequency characteristic spectrum.

[0025] The stator current sampling data sequence of any phase of the asynchronous motor in step S1 of this embodiment The sampling frequency =10kHz, sampling time 10 seconds, the sampling data sequence is recorded as , =1,2,3,...,N, length N =100000.

[0026] like Figure 2 As shown, in step S2 of this embodiment, the stator current sampling data sequence Perform fundamental frequency suppression and construct sideband function sequence include: S2.1, stator current sampling data sequence Digital filtering is performed to suppress random noise; S2.2, stator current sampling data sequence after digital filtering Perform fast Fourier transform to extract the baseband frequency Angular frequency and spectrum amplitude ; S2.3, stator current sampling data sequence Perform a second-order difference operation to find the second-order derivative of the current; S2.4, insert zero values ​​into the sequence of the second-order derivative of the current and adjust the sequence length to make it consistent with the original stator current sampling data sequence Align, then multiply by the scale parameter Get a new sequence ,in is the angular frequency of the fundamental frequency; S2.5, according to Constructing a sequence of sideband functions ,in is the nth sideband function, is the nth current signal, for In the new sequence The corresponding signal is aligned in the middle. Sideband function sequence The fundamental frequency has been basically eliminated, and it is called the side frequency function sequence.

[0027] The digital filtering in step S2.1 may adopt a filtering method that can suppress random noise as needed. For example, as an optional implementation, the digital filtering in step S2.1 of this embodiment refers to digital filtering using a moving average filtering method.

[0028] In step S2.3 of this embodiment, the function expression of the second-order derivative of the current obtained by performing the second-order difference operation is: , In the above formula, is the second-order derivative of the current, For the A current signal, For the A current signal, is the nth current signal, is the sampling period, =10 -4 s.

[0029] The stator current of an asynchronous motor with a broken rotor bar fault can be expressed as: , (1) In the above formula, is the stator current at time t, is the amplitude of the fundamental frequency, is the angular frequency of the fundamental frequency, is the phase of the fundamental frequency, Left frequency The current amplitude, is the frequency of the left spectrum, Left frequency The phase of Right frequency The current value, is the right spectrum frequency, Right frequency The phase of the left frequency The current amplitude and right frequency Current value In terms of Very big and Very small, the second-order derivative of equation (1) is obtained: , (2) It can be seen that the stator current at time t is The second derivative of has the same properties as the original function.

[0030] If the stator current at time t The second derivative of , then: , (3) Adding equation (1) and equation (3) together, we get: , (4) , (5) In the above formula, This is the sideband function in the frequency domain. Discretizing it will give the nth sideband function. , thus we can obtain the sideband function sequence According to equations (4) and (5), the sideband function sequence There are only two side frequency components in and , the powerful fundamental wave has been suppressed, and the left frequency The amplitude is , right frequency The amplitude is .

[0031] like Figure 1 As shown, in step S3 of this embodiment, the sideband function sequence Extracting sideband feature spectra through fast Fourier transform includes: S3.1, sideband function sequence Obtain the spectrum amplitude of the sideband function through fast Fourier transform ; S3.2, from the spectrum amplitude Determine the left frequency The corresponding left spectrum frequency and right frequency The corresponding right spectrum frequency , according to the spectrum frequency on the left and the right spectrum frequency Calculate the left spectrum amplitude and the right spectrum amplitude as the sideband characteristic spectrum.

[0032] Step S3.2 in this embodiment includes: S3.2.1, from the spectrum amplitude Based on and Determine the left frequency and right frequency ,in is the fundamental frequency, is the slip rate of the asynchronous motor; spectrum amplitude Center left frequency The spectrum amplitude is: , (6) in, For the original data Spectral amplitude; right frequency The spectrum amplitude is: , (7) in, Sideband Actual spectrum amplitude.

[0033] Therefore, it is only necessary to convert the spectrum amplitude Center left frequency Frequency Amplitude Multiply , you can get the left frequency The left spectrum amplitude of ; The spectrum Center right frequency Frequency Amplitude Multiply , we can get the spectrum amplitude on the right side ; S3.2.2, according to and Calculate the left frequency The corresponding left spectrum frequency and right frequency The corresponding right spectrum frequency ; S3.2.3, according to the spectrum frequency on the left and the right spectrum frequency , calculate the spectrum amplitude on the left according to the following formula and the right spectrum amplitude As the sideband eigenspectrum: , (8) , (9) In the above formula, is the spectrum amplitude Center left frequency The spectrum amplitude of is the spectrum amplitude Center right frequency The spectrum amplitude of is the angular frequency of the fundamental frequency.

[0034] like Figure 1 As shown, in step S4 of this embodiment, judging whether the asynchronous motor has a broken rotor bar fault according to the sideband characteristic spectrum includes: and the right spectrum amplitude The larger of the two ; Calculate the larger value The spectrum amplitude of the fundamental frequency The dB difference between , if the larger value The spectrum amplitude of the fundamental frequency The dB difference between If the value is greater than the preset threshold, it is determined that the asynchronous motor has a broken rotor bar fault. The preset threshold can be selected according to actual needs. For example, as an optional implementation, the preset threshold in this embodiment is -48dB, that is, if , it is determined that the asynchronous motor has a broken rotor bar fault.

[0035] In order to verify the rotor broken bar fault detection method of the asynchronous motor based on the second-order derivative in this embodiment, a simulation verification method is adopted in this embodiment. During the simulation verification, the stator current of the motor stator phase A is assumed to be: , (10) In addition, the fundamental frequency =50Hz, left frequency =49.0Hz, right frequency =51.0Hz, sampling frequency =10kHz, sampling time 10 seconds, sampling data length N=100000. If the sampling data is directly subjected to fast Fourier transform FFT, its spectrum is obtained as follows Figure 3 Although the sampling window length is increased, that is, the number of sampling points N is increased, the left frequency and right frequency In this embodiment, according to the derivative property of the sine function, after performing second-order difference processing on the sampled data sequence, a new sequence is constructed that basically eliminates the fundamental frequency component, that is, the side frequency function sequence . For the sideband function sequence Fast Fourier transform (FFT) can effectively extract the characteristic edge spectrum of the motor rotor broken bar fault and calculate the criterion index (larger value) The spectrum amplitude of the fundamental frequency The dB difference between ), it is possible to accurately determine whether the motor rotor has a broken bar fault. In this embodiment, based on the sideband function sequence The spectrum of Figure 4 As shown. The fundamental frequency is calculated as The spectrum amplitude =43.7976, left spectrum amplitude =0.1618, right spectrum amplitude =0.2487, larger value The spectrum amplitude of the fundamental frequency The dB difference between , it is determined that there is a broken rotor bar fault.

[0036] In order to verify the effectiveness of the rotor bar fault detection method of an asynchronous motor based on the second-order derivative in extracting the amplitude of the side frequency component, the simulation signal is set: After sampling, do a fast Fourier transform FFT and get the left frequency The signal spectrum is Figure 5 As shown, the obtained frequency is the left frequency The spectrum amplitude of the signal is =0.1610, which is substantially the same as the side spectrum amplitude extracted by the rotor broken bar fault detection method of the asynchronous motor based on the second-order derivative in this embodiment. It can be seen that the rotor broken bar fault detection method of the asynchronous motor based on the second-order derivative in this embodiment can meet the requirements of rotor broken bar fault feature extraction and diagnosis.

[0037] In summary, the method of this embodiment is based on the stator current sampling data sequence of any phase of the asynchronous motor The rotor bar fault detection of asynchronous motor can be realized, the amount of data required is small, the acquisition is simple and convenient, and the signal acquisition required for fault detection can be simplified. When the motor has a rotor bar fault, the frequency of the motor stator current is The characteristic component of is the fundamental frequency (base frequency), is the slip rate. In the spectrum of the stator current, the fundamental frequency The left frequency appears on both sides and right frequency Therefore, the present invention can effectively extract the fault characteristics and accurately detect the motor rotor fault by judging whether the asynchronous motor has a broken rotor bar fault based on the side frequency characteristic spectrum. , right frequency With base frequency Very close, directly use the conventional fast Fourier transform (FFT) algorithm for spectrum analysis, because the base frequency The sideband is relatively strong, the sideband is weak, and there is spectrum leakage. The sideband is annihilated by the baseband, resulting in the sideband being unable to be detected. At the same time, the fast Fourier transform FFT can only be effectively applied when the stator current and load remain relatively stable. Therefore, the current sampling time should not be too long. It is not feasible to improve the frequency resolution by increasing the sampling data length to achieve the purpose of distinguishing and detecting the sideband. The method of this embodiment includes sampling the stator current data sequence Using second-order derivatives to suppress fundamental frequency and construct sideband function sequence , and then the sideband function sequence The sideband characteristic spectrum is extracted by fast Fourier transform, and the sideband characteristic spectrum reflecting the rotor bar fault can be accurately extracted by fundamental frequency suppression to improve the motor current sampling signal processing algorithm, and the sideband characteristic spectrum of the rotor bar fault is extracted with high precision to accurately diagnose the rotor bar fault of the asynchronous motor and realize high-sensitivity monitoring of the rotor bar fault. The method of this embodiment has the advantages of simplicity and small amount of calculation, can realize high-precision monitoring of the rotor bar fault, and is particularly beneficial to the on-site edge computing scenario with limited computing power.

[0038] In addition, the present embodiment also provides a rotor bar broken fault detection system for an asynchronous motor based on second-order derivatives, comprising a microprocessor and a memory connected to each other, wherein the microprocessor is programmed or configured to execute the rotor bar broken fault detection method for an asynchronous motor based on second-order derivatives.

[0039] In addition, this embodiment also provides a computer-readable storage medium, in which a computer program or instruction is stored. The computer program or instruction is programmed or configured to execute the rotor broken bar fault detection method of the asynchronous motor based on the second-order derivative through a processor.

[0040] In addition, this embodiment also provides a computer program product, including a computer program or instructions, which are programmed or configured to execute the rotor broken bar fault detection method of an asynchronous motor based on second-order derivatives through a processor.

[0041] Those skilled in the art should understand that the technical solutions provided by the embodiments of the present application may be in the form of methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the process Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0042] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A method for detecting a broken rotor bar fault of an asynchronous motor based on second-order derivatives, characterized in that: The steps include: S1, obtain the stator current sampling data sequence of any phase of the asynchronous motor ,in is the nth current signal; S2, stator current sampling data sequence Using second-order derivatives to suppress fundamental frequency and construct sideband function sequence ,in is the nth sideband function; S3, the sideband function sequence Extract the sideband characteristic spectrum through fast Fourier transform; S4, judging whether the asynchronous motor has a broken rotor bar fault according to the side frequency characteristic spectrum.

2. The method for detecting a broken rotor bar fault of an asynchronous motor based on second-order derivative according to claim 1, characterized in that: In step S2, the stator current sampling data sequence Perform fundamental frequency suppression and construct sideband function sequence include: S2.1, stator current sampling data sequence Digital filtering is performed to suppress random noise; S2.2, stator current sampling data sequence after digital filtering Perform a fast Fourier transform to extract the angular frequency of the fundamental frequency and spectrum amplitude ; S2.3, stator current sampling data sequence Perform a second-order difference operation to find the second-order derivative of the current; S2.4, insert zero values ​​into the sequence of the second-order derivative of the current and adjust the sequence length to make it consistent with the original stator current sampling data sequence Align, then multiply by the scale parameter Get a new sequence ,in is the angular frequency of the fundamental frequency; S2.5, according to Constructing a sequence of sideband functions ,in is the nth sideband function, is the nth current signal, for In the new sequence Align the corresponding signals in the middle.

3. The method for detecting a broken rotor bar fault of an asynchronous motor based on second-order derivative according to claim 2, characterized in that: The digital filtering in step S2.1 refers to digital filtering using a moving average filtering method.

4. The method for detecting a broken rotor bar fault of an asynchronous motor based on second-order derivative according to claim 2, characterized in that: The function expression of the second-order derivative of the current obtained by performing the second-order difference operation in step S2.3 is: ， In the above formula, is the second-order derivative of the current, For the A current signal, For the A current signal, is the nth current signal, is the sampling period.

5. The method for detecting a broken rotor bar fault of an asynchronous motor based on second-order derivative according to claim 1, characterized in that: In step S3, the sideband function sequence Extracting sideband feature spectra through fast Fourier transform includes: S3.1, sideband function sequence Obtain the spectrum amplitude of the sideband function through fast Fourier transform ; S3.2, from the spectrum amplitude Determine the left frequency The corresponding left spectrum frequency and right frequency The corresponding right spectrum frequency , according to the spectrum frequency on the left and the right spectrum frequency Calculate the left spectrum amplitude and the right spectrum amplitude as the sideband characteristic spectrum.

6. The method for detecting a broken rotor bar fault of an asynchronous motor based on second-order derivatives according to claim 5, characterized in that: Step S3.2 includes: S3.2.1, from the spectrum amplitude Based on and Determine the left frequency and right frequency ,in is the fundamental frequency, is the slip rate of the asynchronous motor; S3.2.2, according to and Calculate the left frequency The corresponding left spectrum frequency and right frequency The corresponding right spectrum frequency ; S3.2.3, according to the spectrum frequency on the left and the right spectrum frequency , calculate the spectrum amplitude on the left according to the following formula and the right spectrum amplitude As the sideband eigenspectrum: ， ， In the above formula, is the spectrum amplitude Center left frequency The spectrum amplitude of is the spectrum amplitude Center right frequency The spectrum amplitude of is the angular frequency of the fundamental frequency.

7. The method for detecting a broken rotor bar fault of an asynchronous motor based on second-order derivatives according to claim 5, characterized in that: In step S4, judging whether the asynchronous motor has a broken rotor bar fault according to the sideband characteristic spectrum includes: and the right spectrum amplitude The larger of the two ; Calculate the larger value The spectrum amplitude of the fundamental frequency The dB difference between , if the larger value The spectrum amplitude of the fundamental frequency The dB difference between If the value is greater than the preset threshold, it is determined that the asynchronous motor has a broken rotor bar fault.

8. A rotor bar fault detection system for an asynchronous motor based on second-order derivatives, comprising a microprocessor and a memory connected to each other, characterized in that: The microprocessor is programmed or configured to execute the rotor broken bar fault detection method of an asynchronous motor based on second-order derivatives as claimed in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program or instruction stored therein, characterized in that: The computer program or instruction is programmed or configured to execute the rotor broken bar fault detection method of an asynchronous motor based on second-order derivatives as claimed in any one of claims 1 to 7 through a processor.

10. A computer program product comprising a computer program or instructions, characterized in that The computer program or instruction is programmed or configured to execute the rotor broken bar fault detection method of an asynchronous motor based on second-order derivatives as claimed in any one of claims 1 to 7 through a processor.

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