Motor fault diagnosis method, intelligent equipment and storage medium

Abstract

The invention relates to the technical field of motors, in particular to a motor fault diagnosis method, intelligent equipment and a storage medium, and aims to solve the problem of how to accurately obtain a negative sequence component of a voltage / current fundamental frequency signal based on fast Fourier transform and spectrum leakage. And the technical problem of how to obtain the statistical mean value of the negative sequence impedance based on convolution to perform motor fault diagnosis is solved. On the basis of a three-phase voltage / current fundamental frequency signal sequence, an a-phase negative sequence component of a voltage / current fundamental frequency signal is obtained through fast Fourier transform according to frequency spectrum leakage, the fundamental frequency fluctuation characteristic of a power grid voltage / current signal can be effectively reserved, the extraction precision of the negative sequence component of the voltage / current fundamental frequency signal is improved, and the extraction accuracy of the voltage / current fundamental frequency signal is improved. Therefore, the impedance calculation is more accurate; the statistical mean value of the negative sequence impedance within the preset time length is calculated through convolution, the volatility of the negative sequence impedance calculation result is reduced, and the reliability of diagnosing the turn-to-turn short circuit fault of the motor based on the negative sequence impedance threshold value is improved.

Description

Technical Field

[0001] The present application relates to the field of motor technology, and in particular to a motor fault diagnosis method, an intelligent device and a storage medium. Background Art

[0002] As the asynchronous motor fault with the second highest incidence rate after bearing failure, turn-to-turn short-circuit fault seriously threatens the safe and stable operation of the asynchronous motor. Therefore, it is of great significance to conduct real-time online diagnosis of the turn-to-turn short-circuit fault of the asynchronous motor. At present, the negative sequence impedance analysis method is a mainstream online diagnosis method for turn-to-turn short-circuit fault. It mainly uses the negative sequence impedance of the asynchronous motor to evaluate the imbalance degree of the three-phase electrical parameters of the asynchronous motor, and then diagnose the turn-to-turn short-circuit fault.

[0003] In the application of turn-to-turn short-circuit fault diagnosis of asynchronous motors, although the negative-sequence impedance analysis method is simple and direct, the accuracy of its diagnostic results is not very ideal due to the existence of many interference factors. In actual operation, since it is difficult to accurately extract the fundamental frequency signal of the stator line current, the voltage signal and the stator line current signal are mostly used directly to calculate the negative-sequence impedance during diagnosis, which will inevitably cause deviations in the calculation results. In addition, due to the volatility of the voltage signal, the impedance calculated by the phasor method is also highly volatile, which will also interfere with the threshold judgment. Therefore, how to improve the reliability of the negative-sequence impedance analysis method in diagnosing turn-to-turn short-circuit faults has become an urgent problem to be solved.

[0004] Accordingly, the art needs a new motor fault diagnosis solution to solve the above problems. Summary of the invention

[0005] In order to overcome the above-mentioned defects, the present application is proposed to solve or at least partially solve the technical problem of how to accurately obtain the a-phase negative-sequence component of the voltage and current fundamental frequency signals with spectrum leakage based on fast Fourier transform, and calculate the statistical mean of the negative-sequence impedance based on convolution, so as to more accurately perform turn-to-turn short-circuit fault diagnosis.

[0006] In a first aspect, a motor fault diagnosis method is provided, the method comprising: Obtaining a three-phase voltage signal sequence and a three-phase current signal sequence of the motor; Acquire a three-phase voltage fundamental frequency signal sequence based on the three-phase voltage signal sequence, and acquire a three-phase current fundamental frequency signal sequence based on the three-phase current signal sequence, wherein the time lengths corresponding to the three-phase voltage fundamental frequency signal sequence and the three-phase current fundamental frequency signal sequence are both preset time lengths; Based on the three-phase voltage fundamental frequency signal sequence, an a-phase negative-sequence component sequence of the voltage fundamental frequency signal is obtained; based on the three-phase current fundamental frequency signal sequence, an a-phase negative-sequence component sequence of the current fundamental frequency signal is obtained; Based on the a-phase negative-sequence component sequence of the voltage fundamental frequency signal and the a-phase negative-sequence component sequence of the current fundamental frequency signal, a statistical mean value of the negative-sequence impedance within the preset time length is obtained by convolution; Based on the statistical mean value of the negative-sequence impedance and a preset negative-sequence impedance threshold, it is determined whether a turn-to-turn short circuit fault occurs in the motor.

[0007] In a technical solution of the above motor fault diagnosis method, the method further includes: Based on the three-phase voltage baseband signal sequence, a negative sequence component sequence of the a-phase of the voltage baseband signal is obtained by fast Fourier transform and considering spectrum leakage; Based on the three-phase current fundamental frequency signal sequence, a phase a negative sequence component sequence of the current fundamental frequency signal is obtained through fast Fourier transform and considering spectrum leakage.

[0008] In a technical solution of the above motor fault diagnosis method, the method further includes: Performing fast Fourier transform on the three-phase baseband signal sequences respectively to obtain three-phase baseband frequency domain signal sequences, wherein the three-phase baseband signal sequences include the three-phase voltage baseband signal sequences and the three-phase current baseband signal sequences, and the three-phase baseband frequency domain signal sequences include the three-phase voltage baseband frequency domain signal sequences and the three-phase current baseband frequency domain signal sequences; Based on the three-phase voltage fundamental frequency domain signal sequence, a frequency domain signal sequence of the a-phase negative-sequence component of the voltage fundamental frequency signal is obtained by converting the vector, and an inverse fast Fourier transform is performed on the frequency domain signal sequence of the a-phase negative-sequence component of the voltage fundamental frequency signal to obtain a negative-sequence component sequence of the a-phase of the voltage fundamental frequency signal; Based on the three-phase current fundamental frequency domain signal sequence, a frequency domain signal sequence of the a-phase negative-sequence component of the current fundamental frequency signal is obtained by converting the vector, and an inverse fast Fourier transform is performed on the frequency domain signal sequence of the a-phase negative-sequence component of the current fundamental frequency signal to obtain a sequence of the a-phase negative-sequence component of the current fundamental frequency signal.

[0009] In a technical solution of the above motor fault diagnosis method, “based on the three-phase voltage fundamental frequency domain signal sequence, obtaining the frequency domain signal sequence of the a-phase negative sequence component of the voltage fundamental frequency signal by converting the vector” includes: Based on the fundamental frequency point sequence number, a preset number of sequence elements are symmetrically extracted from the three-phase voltage fundamental frequency domain signal sequence to obtain a three-phase voltage fundamental frequency domain signal basic matrix, wherein the fundamental frequency point sequence number is determined based on the fundamental frequency and the spectrum resolution, and the preset number is determined based on the spectrum leakage; Based on the three-phase voltage fundamental frequency domain signal basic matrix and the conversion vector, obtaining the frequency domain basic vector of the a-phase negative sequence component of the voltage fundamental frequency signal; The frequency domain basis vector of the a-phase negative-sequence component of the voltage baseband signal is expanded to obtain a frequency domain signal sequence of the a-phase negative-sequence component of the voltage baseband signal.

[0010] In a technical solution of the above motor fault diagnosis method, “based on the three-phase current fundamental frequency domain signal sequence, obtaining the frequency domain signal sequence of the a-phase negative sequence component of the current fundamental frequency signal by converting the vector” includes: Based on the fundamental frequency point sequence number, a preset number of sequence elements are symmetrically extracted from the three-phase current fundamental frequency domain signal sequence to obtain a three-phase current fundamental frequency domain signal basic matrix, wherein the fundamental frequency point sequence number is determined based on the fundamental frequency and the spectrum resolution, and the preset number is determined based on the spectrum leakage; Based on the three-phase current fundamental frequency domain signal basic matrix and the conversion vector, obtaining the frequency domain basic vector of the a-phase negative sequence component of the current fundamental frequency signal; The frequency domain basis vector of the a-phase negative sequence component of the current fundamental frequency signal is expanded to obtain a frequency domain signal sequence of the a-phase negative sequence component of the current fundamental frequency signal.

[0011] In a technical solution of the above motor fault diagnosis method, “obtaining the statistical mean of the negative sequence impedance within the preset time length by convolution based on the a-phase negative sequence component sequence of the voltage fundamental frequency signal and the a-phase negative sequence component sequence of the current fundamental frequency signal” includes: Reconstructing and expanding the a-phase negative-sequence component sequence of the voltage fundamental frequency signal to obtain a voltage fundamental frequency negative-sequence component sequence; Reconstructing the sequence number of the a-phase negative-sequence component sequence of the current fundamental frequency signal to obtain a current fundamental frequency negative-sequence component sequence; Based on the voltage fundamental frequency negative sequence component sequence, the current fundamental frequency negative sequence component sequence and the parameters of the convolution kernel, the statistical mean of the negative sequence impedance is obtained, wherein the parameters of the convolution kernel are obtained according to the convolution equation between the sinusoidal voltage signal and the sinusoidal current signal.

[0012] In a technical solution of the above motor fault diagnosis method, the method further includes: The convolution equation is constructed based on a convolution step size of 2.

[0013] In a technical solution of the above motor fault diagnosis method, “determining whether a turn-to-turn short circuit fault occurs in the motor based on the statistical mean of the negative sequence impedance and a preset negative sequence impedance threshold” includes: Obtaining an impedance change ratio between a statistical mean value of the negative-sequence impedance and the negative-sequence impedance threshold; When the statistical mean of the negative-sequence impedance is less than the negative-sequence impedance threshold, the turn-to-turn short circuit fault is determined based on a preset impedance variation interval.

[0014] In a second aspect, a smart device is provided, the smart device comprising at least one processor; and a memory communicatively connected to the at least one processor; Wherein, a computer program is stored in the memory, and when the computer program is executed by the at least one processor, the method described in any one of the technical solutions of the above-mentioned motor fault diagnosis method is implemented.

[0015] In a third aspect, a storage medium stores a plurality of program codes, wherein the computer program, when executed by the at least one processor, implements the method described in any one of the technical solutions of the above-mentioned motor fault diagnosis method.

[0016] The above one or more technical solutions of the present application have at least one or more of the following beneficial effects: the method of obtaining the a-phase negative-sequence component of the target voltage / current fundamental frequency signal based on Fourier transform and considering spectrum leakage can effectively retain the fundamental frequency fluctuation characteristics of the grid voltage / current signal, improve the extraction accuracy of the negative-sequence component of the voltage / current fundamental frequency signal, and thus make the impedance calculation more accurate; by convolutionally calculating the statistical mean of the negative-sequence impedance within a preset time length, the volatility of the negative-sequence impedance calculation result is reduced, and the reliability of diagnosing motor inter-turn short-circuit faults based on the negative-sequence impedance threshold is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The disclosure of the present application will become more easily understood with reference to the accompanying drawings. It is easy for those skilled in the art to understand that these drawings are only for illustrative purposes and are not intended to limit the scope of protection of the present application.

[0018] Figure 1 is a schematic flow chart of the main steps of a motor fault diagnosis method according to an embodiment of the present application; Figure 2 is a detailed step flow diagram of step S103 according to an embodiment of the present application; Figure 3 is a detailed step flow diagram of step S202 according to an embodiment of the present application; Figure 4 is an amplitude spectrum diagram obtained by fast Fourier transforming the time domain signals of the a-phase voltage and the a-phase current according to an embodiment of the present application; Figure 5 is a detailed step flow diagram of step S204 according to an embodiment of the present application; Figure 6 is a detailed step flow diagram of step S104 according to an embodiment of the present application; Figure 7 It is a schematic diagram of the main structure of a smart device according to an embodiment of the present application. DETAILED DESCRIPTION

[0019] Some embodiments of the present application are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present application and are not intended to limit the protection scope of the present application.

[0020] In the description of the present application, "module" and "processor" may include hardware, software or a combination of the two. A module may include hardware circuits, various suitable sensors, communication ports, memory, and may also include software parts, such as program code, or a combination of software and hardware. The processor may be a central processing unit, a microprocessor, an image processor, a digital signal processor or any other suitable processor. The processor has data and / or signal processing functions. The processor may be implemented in software, hardware or a combination of the two. Computer-readable storage media include any suitable medium that can store program code, such as a disk, a hard disk, an optical disk, a flash memory, a read-only memory, a random access memory, etc. The term "A and / or B" means all possible combinations of A and B, such as only A, only B, or A and B. The term "at least one A or B" or "at least one of A and B" has a similar meaning to "A and / or B" and may include only A, only B, or A and B. The singular terms "one" and "the" may also include plural forms.

[0021] See attached Figure 1 , Figure 1 FIG. 1 is a flow chart of the main steps of a motor fault diagnosis method according to an embodiment of the present application. Figure 1 As shown, the motor fault diagnosis method in the embodiment of the present application includes: Step S101: acquiring a three-phase voltage signal sequence and a three-phase current signal sequence of a motor; Step S102: acquiring a three-phase voltage fundamental frequency signal sequence based on the three-phase voltage signal sequence, and acquiring a three-phase current fundamental frequency signal sequence based on the three-phase current signal sequence; Step S103: acquiring a phase a negative sequence component sequence of the voltage fundamental frequency signal based on the three-phase voltage fundamental frequency signal sequence, and acquiring a phase a negative sequence component sequence of the current fundamental frequency signal based on the three-phase current fundamental frequency signal sequence; Step S104: obtaining a statistical mean of negative sequence impedance within a preset time length through convolution based on the a-phase negative sequence component sequence of the voltage fundamental frequency signal and the a-phase negative sequence component sequence of the current fundamental frequency signal; Step S105: Based on the statistical mean of the negative sequence impedance and a preset negative sequence impedance threshold, it is determined whether a turn-to-turn short circuit fault occurs in the motor.

[0022] In the embodiment of the present application, the connection mode of the three-phase asynchronous motor is star connection. In step S101, according to the preset sampling frequency and preset sampling duration , respectively, through the voltage sensor and current sensor, synchronously collect the motor stator voltage and current, and obtain the three-phase (phase a, phase b and phase c) voltage signal sequence , and , and the three-phase (phase a, phase b and phase c) current signal sequence , and .in, , By sampling frequency and sampling duration Sure.

[0023] As an example, the sampling frequency Set to 12.8KHz, sampling time Set to 3 seconds, at this time, the data length of each phase voltage signal sequence and each phase current signal sequence is , which includes data of 38,400 sampling points.

[0024] In step S102, the method of obtaining the voltage fundamental frequency signal and the current fundamental frequency signal is not limited in this application. As an example, the voltage fundamental frequency signal and the current fundamental frequency signal can be obtained by using methods such as Kalman filtering algorithm and Parker vector method.

[0025] The corresponding phase a voltage fundamental frequency signal sequence is: , The corresponding b-phase voltage baseband signal sequence is: , The corresponding c-phase voltage fundamental frequency signal sequence is ; The corresponding a-phase current fundamental frequency signal sequence is , The corresponding b-phase current fundamental frequency signal sequence is , The corresponding c-phase current fundamental frequency signal sequence is ,in, .

[0026] Considering that the base-2 fast Fourier (inverse) transform requires the amount of data to be processed to be an integer power of 2, N can be selected to be less than The value corresponding to the integer power of 2, for example, .

[0027] It should be noted that , , , , and Need to be selected synchronously and continuously, that is , , , , and The sampling moments corresponding to the sequence elements with the same sequence number should remain the same.

[0028] Step S103 specifically includes, based on the three-phase voltage fundamental frequency signal sequence, through fast Fourier transform and considering spectrum leakage, obtaining the a-phase negative sequence component sequence of the voltage fundamental frequency signal; based on the three-phase current fundamental frequency signal sequence, through fast Fourier transform and considering spectrum leakage, obtaining the a-phase negative sequence component sequence of the current fundamental frequency signal.

[0029] Continue reading Figure 2 ,pass Figure 2 The detailed process flow of step S103 is described. Figure 2 It is a detailed flowchart of step S103 according to an embodiment of the present application.

[0030] In step S201, fast Fourier transform is performed on the three-phase baseband signal sequences respectively to obtain three-phase baseband frequency domain signal sequences.

[0031] The three-phase baseband signal sequence includes a three-phase voltage baseband signal sequence and a three-phase current baseband signal sequence. Accordingly, the three-phase baseband frequency domain signal sequence includes a three-phase voltage baseband frequency domain signal sequence and a three-phase current baseband frequency domain signal sequence.

[0032] Specifically, the three-phase voltage fundamental frequency signal sequence (a-phase voltage fundamental frequency signal sequence , b-phase voltage base frequency signal sequence and c-phase voltage fundamental frequency signal sequence ) to perform fast Fourier transform and obtain the three-phase voltage baseband frequency domain signal sequence.

[0033] The three-phase voltage fundamental frequency domain signal sequence includes: the a-phase voltage fundamental frequency domain signal sequence is , the frequency domain signal sequence of phase b voltage fundamental frequency is , the frequency domain signal sequence of phase c voltage fundamental frequency is ,in, .

[0034] The three-phase current fundamental frequency signal sequence (phase a current fundamental frequency signal sequence , b-phase current fundamental frequency signal sequence and the c-phase current fundamental frequency signal sequence ) to perform fast Fourier transform and obtain the three-phase current fundamental frequency domain signal sequence.

[0035] The three-phase current fundamental frequency domain signal sequence includes: the a-phase current fundamental frequency domain signal sequence is , the frequency domain signal sequence of the b-phase current fundamental frequency is , the frequency domain signal sequence of the phase c current fundamental frequency is ,in, .

[0036] In step S202, based on the three-phase voltage fundamental frequency domain signal sequence, a frequency domain signal sequence of the a-phase negative sequence component of the voltage fundamental frequency signal is obtained by converting the vector.

[0037] Continue reading Figure 3 ,pass Figure 3 The detailed process flow of step S202 is described. Figure 3 It is a detailed flowchart diagram of step S202 according to an embodiment of the present application.

[0038] In step S301, based on the fundamental frequency point number, a preset number of sequence elements are symmetrically extracted from the three-phase voltage fundamental frequency domain signal sequence to obtain a basic matrix of the three-phase voltage fundamental frequency domain signal, wherein the fundamental frequency point number is determined based on the fundamental frequency and the spectrum resolution, and the preset number is determined based on the spectrum leakage.

[0039] As attached Figure 4 As shown, Figure 4 (a) is an amplitude spectrum diagram obtained by fast Fourier transform of the a-phase voltage time domain signal according to an embodiment of the present application, wherein the ordinate is the voltage amplitude, the lower abscissa is the frequency, and the upper abscissa is the serial number value corresponding to each frequency point.

[0040] In the embodiment of the present application, the number of input data N for fast Fourier transform of the voltage baseband signal sequences of phase a, phase b and phase c is 32768, and the sampling frequency is 12.8KHz. At this time, the spectrum resolution of Fourier transform is .

[0041] Baseband frequency The corresponding base frequency point number is In the present embodiment, the baseband frequency , at this time, the base frequency point number .

[0042] Considering spectrum leakage, the frequency domain signal sequence of phase a voltage base frequency is , b-phase voltage base frequency domain signal sequence , c-phase voltage fundamental frequency domain signal sequence In the example, with the baseband frequency point number 128 as the center, a preset number (127, the value range of n is [65,191], that is, the range of baseband spectrum leakage can usually be considered to be no more than the range of values ​​of the baseband frequency point number as the center, the numbers on the left and right ends are reduced / increased by half of the baseband frequency point number, and the reduced / increased value in the embodiment of the present application is 63) of elements are extracted symmetrically to form three groups of 1x127 row vectors, and the three-phase voltage baseband frequency domain signal basic matrix is ​​obtained from these three groups of 1x127 row vectors : .

[0043] In step S302, based on the three-phase voltage fundamental frequency domain signal basic matrix and the conversion vector, the frequency domain basic vector of the a-phase negative sequence component of the voltage fundamental frequency signal is obtained.

[0044] First, construct a 1x3 transformation vector , ,in, .

[0045] Then according to the basic matrix of the three-phase voltage fundamental frequency domain signal and the conversion vector , calculate the elements with serial numbers between [65,191] of the fast Fourier transform results of the a-phase negative sequence component of the voltage fundamental frequency signal, and obtain the frequency domain basis vector of the a-phase negative sequence component of the voltage fundamental frequency signal ,in, represents the dot product of the row vector S and the matrix Bu, is a 1x127 row vector.

[0046] In step S303, the frequency domain basis vector of the negative sequence component of the a phase of the voltage fundamental frequency signal is The frequency domain signal sequence of the a-phase negative-sequence component of the voltage fundamental frequency signal is obtained by expansion (ie, the fast Fourier transform result of the a-phase negative-sequence component of the voltage fundamental frequency signal, a total of 32768 data).

[0047] based on , construct 4 sets of row vectors , , and According to the characteristics of the spectrum obtained by Fourier transform, , and The values ​​of the sequence elements in are all 0. The corresponding number of sequence elements is 65. The corresponding number of sequence elements is 32385. The corresponding number of sequence elements is 64.

[0048] for , first obtain The conjugate complex number of each sequence element in gives The conjugate row vector of , then After reversing all sequence elements in , we get ,in The sequence number range of the sequence elements in is [32768-191,32768-65], that is, [32577,32703].

[0049] As an example, , The corresponding serial number is 65. The conjugate row vector of , then After reversing all sequence elements in , we get ,in, The corresponding serial number is 32768-191, that is, 32577. The corresponding serial number is 32768-65, that is, 32703.

[0050] according to , , , and The five row vectors are combined in the order of to obtain a row vector of 1x32768, which is the frequency domain signal sequence of the a-phase negative-sequence component of the voltage fundamental frequency signal that retains the fundamental frequency fluctuation characteristics, and is also the Fourier transform result of the a-phase negative-sequence component of the voltage fundamental frequency signal.

[0051] In step S203, the frequency domain signal sequence of the a-phase negative sequence component of the voltage baseband signal obtained in step S303 is subjected to an inverse fast Fourier transform, and the real part of the inverse fast Fourier transform result is taken to obtain the a-phase negative sequence component sequence of the voltage baseband signal. ,in, .

[0052] In step S204, based on the frequency domain signal sequence of the three-phase current fundamental frequency, a frequency domain signal sequence of the a-phase negative sequence component of the current fundamental frequency signal is obtained by converting the vector.

[0053] Continue reading Figure 5 ,pass Figure 5 The detailed process flow of step S204 is described. Figure 5 It is a detailed flowchart diagram of step S204 according to an embodiment of the present application.

[0054] In step S501, based on the fundamental frequency point number, a preset number of sequence elements are symmetrically extracted from the three-phase current fundamental frequency domain signal sequence to obtain a basic matrix of the three-phase current fundamental frequency domain signal, wherein the fundamental frequency point number is determined based on the fundamental frequency and the spectrum resolution, and the preset number is determined based on the spectrum leakage.

[0055] As attached Figure 4 As shown, Figure 4 (b) is an amplitude spectrum obtained by fast Fourier transform of the a-phase current time domain signal according to an embodiment of the present application, wherein the ordinate is the current amplitude, the lower abscissa is the frequency, and the upper abscissa is the serial number value corresponding to each frequency point.

[0056] In the embodiment of the present application, the number of input data N for fast Fourier transform of the current baseband signal sequences of phase a, phase b and phase c is also 32768, and the sampling frequency The same is 12.8KHz. At this time, the spectrum resolution of Fourier transform is .

[0057] Baseband frequency The corresponding base frequency point number is In the present embodiment, the baseband frequency , at this time, the base frequency point number .

[0058] Also consider the spectrum leakage, respectively in the a phase current base frequency domain signal sequence , b-phase current fundamental frequency domain signal sequence , c-phase current fundamental frequency domain signal sequence In the example, with the baseband frequency point number 128 as the center, a preset number (127, the value range of n is [65, 191], that is, the range of baseband spectrum leakage can usually be considered to be no more than the range of the value of the baseband frequency point number with the baseband frequency point number as the center, and the numbers on the left and right ends are reduced / increased by half of the baseband frequency point number, and the reduced / increased value in the embodiment of the present application is 63) of elements are extracted symmetrically to form 3 groups of 1x127 row vectors, and the three-phase current baseband frequency domain signal basic matrix is ​​obtained from these 3 groups of 1x127 row vectors. : .

[0059] In step S502, based on the three-phase current fundamental frequency domain signal basic matrix and the conversion vector, the frequency domain basic vector of the a-phase negative sequence component of the current fundamental frequency signal is obtained.

[0060] First, construct a 1x3 transformation vector , ,in, .

[0061] Then according to the basic matrix of the three-phase current fundamental frequency domain signal and the conversion vector , calculate the elements with serial numbers between [65,191] of the fast Fourier transform results of the negative sequence component of the a phase of the current fundamental frequency signal, and obtain the frequency domain basis vector of the negative sequence component of the a phase of the current fundamental frequency signal ,in, Represents the row vector S and the matrix The dot product of is a 1x127 row vector.

[0062] In step S503, the frequency domain basis vector of the negative sequence component of the a-phase of the current fundamental frequency signal is The frequency domain signal sequence of the a-phase negative-sequence component of the current fundamental frequency signal is obtained by expansion (ie, the fast Fourier transform result of the a-phase negative-sequence component of the current fundamental frequency signal, a total of 32768 data).

[0063] based on , construct 4 sets of row vectors , , and According to the characteristics of the spectrum obtained by Fourier transform, , and The values ​​of the sequence elements in are all 0. The corresponding number of sequence elements is 65. The corresponding number of sequence elements is 32385. The corresponding number of sequence elements is 64.

[0064] for , first obtain The conjugate complex number of each sequence element in gives The conjugate row vector of , then After reversing all sequence elements in , we get ,in The sequence number range of the sequence elements in is [32768-191,32768-65], that is, [32577,32703].

[0065] As an example, , The corresponding serial number is 65. The conjugate row vector of , then After reversing all sequence elements in , we get ,in, The corresponding serial number is 32768-191, that is, 32577. The corresponding serial number is 32768-65, which is 32703.

[0066] according to , , , and The five row vectors are combined in the order of to obtain a row vector of 1x32768, which is the frequency domain signal sequence of the a-phase negative-sequence component of the current fundamental frequency signal that retains the fundamental frequency fluctuation characteristics, and is also the Fourier transform result of the a-phase negative-sequence component of the current fundamental frequency signal.

[0067] In step S205, the frequency domain signal sequence of the a-phase negative sequence component of the current baseband signal obtained in step S503 is subjected to an inverse fast Fourier transform, and the real part of the inverse fast Fourier transform result is taken to obtain the a-phase negative sequence component sequence of the current baseband signal. ,in, .

[0068] Through the above-mentioned method of obtaining the a-phase negative-sequence component of the voltage / current fundamental frequency signal based on Fourier transform and taking into account spectrum leakage, compared with the traditional method of estimating the negative-sequence component of the voltage / current fundamental frequency signal based on the phasor method, the method of the present application can effectively retain the fundamental frequency fluctuation characteristics of the power grid voltage / current signal, improve the extraction accuracy of the negative-sequence component of the voltage / current fundamental frequency signal, thereby making the impedance calculation more accurate.

[0069] Next, combine Figure 6 , illustrating a method for obtaining the statistical mean of the negative sequence impedance. Figure 6 It is a detailed flowchart diagram of step S104 according to an embodiment of the present application.

[0070] In step S601, the negative sequence component sequence of the voltage baseband signal is reconstructed and expanded to obtain the voltage baseband negative sequence component sequence ,in, .

[0071] Specifically, Make up The voltage fundamental frequency negative sequence component sequence can be obtained by taking the front end of all elements in ,in, ,at this time, The number of elements in is (N+1), that is, 32769.

[0072] In step S602, the sequence number of the negative sequence component sequence of the current fundamental frequency signal is reconstructed to obtain the current fundamental frequency negative sequence component sequence ,in, .

[0073] Specifically, The sampling time of all elements in is moved back by one sampling interval to obtain the current fundamental frequency negative sequence component sequence: ,in, , ,at this time, The number of elements in is still N, that is, 32768.

[0074] In step S603, based on the voltage fundamental frequency negative sequence component sequence, the current fundamental frequency negative sequence component sequence and the parameters of the convolution kernel, the statistical mean of the negative sequence impedance within the preset time length is obtained. The convolution kernel is obtained according to the convolution equation between the sinusoidal voltage signal and the sinusoidal current signal.

[0075] In the embodiment of the present application, the preset time length is the current fundamental frequency negative sequence component sequence The corresponding time length, that is, the preset time length is Seconds, that is, to obtain the statistical mean of the negative sequence impedance within a time length of 2.56 seconds.

[0076] The difference between the voltage fundamental frequency signal and the current fundamental frequency signal of the asynchronous motor is caused by the impedance of the asynchronous motor. Since convolution can adjust the amplitude and phase of the sinusoidal signal, the relationship between the voltage fundamental frequency signal (sinusoidal voltage signal) and the current fundamental frequency signal (sinusoidal current signal) can be expressed by the following convolution equation: (Formula 1) in, ( Take any integer) to form the convolution kernel .

[0077] Since the voltage fundamental frequency signal and the current fundamental frequency signal in this application have causality, when When taking a negative integer, Considering that the convolution with a step size of 2 can achieve the adjustment of the amplitude and phase of the voltage baseband signal, therefore, in the embodiment of the present application, the convolution kernel Select a convolution kernel with a parameter number of 2 ,Right now .

[0078] In the embodiment of the present application, according to Formula 1, the convolution kernel is selected When the voltage fundamental frequency negative sequence component sequence within the preset time length and the negative sequence component sequence of the current fundamental frequency With the following relationship: (Formula 2).

[0079] Multiplying both ends of equation 2 by the Nx2 voltage fundamental frequency negative sequence component matrix, we can get: .

[0080] Right now, (Formula 3).

[0081] Dividing both sides of the equal sign in equation 3 by N, we get: (Formula 4).

[0082] According to formula 4, the convolution kernel can be obtained Parameters within a preset time and ,Right now, .

[0083] According to the obtained convolution kernel Parameters and , and then visualize the relationship between the voltage fundamental frequency signal and the current fundamental frequency signal within the preset time length based on formula 1, and obtain: (Formula 5) in, is the amplitude of the voltage fundamental frequency signal, is the amplitude of the current fundamental frequency signal, is the phase angle of the voltage signal, is the phase difference between the voltage signal and the current signal caused by impedance.

[0084] The left side of Equation 5 is expanded by trigonometric function to: (Formula 6).

[0085] The right side of Equation 5 is expanded by trigonometric function to: (Formula 7).

[0086] For any n, Equation 6 and Equation 7 are equal, so we have the following equation: (Formula 8) (Formula 9).

[0087] Formula 8 and Formula 9 are squared and added to obtain: (Formula 10) in, It is the statistical mean of the negative sequence impedance within the preset time period.

[0088] It should be noted that, in other embodiments, those skilled in the art may also select other values ​​of the convolution step length, for example, the value of the convolution step length is 3, 4, or other values, and at this time, the statistical mean of the negative sequence impedance within the preset time length may also be obtained by convolution. Without departing from the principles of the present application, the schemes after these changes are equivalent to the technical schemes described in the present application, and therefore will also fall within the protection scope of the present application.

[0089] In step S105, the impedance change ratio between the statistical mean of the negative sequence impedance and the negative sequence impedance threshold is obtained. Specifically, .

[0090] When the statistical mean of the negative sequence impedance is less than the negative sequence impedance threshold, a turn-to-turn short circuit fault is determined based on a preset impedance variation interval, wherein the impedance variation interval may be one or more.

[0091] When the impedance variation interval [q, 1) is one, when the statistical mean of the negative sequence impedance belongs to the impedance variation interval [q, 1), it is determined that a turn-to-turn short circuit fault occurs in the motor. As an example, q can be set to 20%.

[0092] When there are multiple impedance change intervals, including impedance change interval 1 [q1, q2) and impedance change interval 2 [q2, 1), each impedance change interval corresponds to a fault type of inter-turn short circuit fault.

[0093] When the statistical mean of the negative sequence impedance belongs to the impedance variation interval 1 [q1, q2), it is determined that the motor has a turn-to-turn short circuit fault, and the fault type is a minor fault; when the statistical mean of the negative sequence impedance belongs to the impedance variation interval 2 [q2, 1), it is determined that the motor has a turn-to-turn short circuit fault, and the fault type is a serious fault. As an example, q1 can be set to 20% and q2 can be set to 40%.

[0094] In the embodiment of the present application, the negative sequence impedance threshold can be set according to the historical data of the asynchronous motor impedance measurement, for example, the impedance average value within a period of historical time. In addition, as the asynchronous motor is used, the negative sequence impedance threshold is regularly updated to obtain a negative sequence impedance threshold that can reflect the latest status of the asynchronous motor stator.

[0095] The present application calculates the statistical mean of the negative-sequence impedance within a preset time period through convolution, thereby reducing the volatility of the negative-sequence impedance calculation results and improving the reliability of motor turn-to-turn short-circuit fault diagnosis based on negative-sequence impedance.

[0096] Another aspect of the present application also provides a smart device.

[0097] In an embodiment of an intelligent device according to the present application, the intelligent device may include at least one processor; and a memory connected to the at least one processor in communication; wherein a computer program is stored in the memory, and when the computer program is executed by the at least one processor, the motor fault diagnosis method described in any of the above embodiments is implemented. Figure 7 , Figure 7 exemplarily shows that the smart device 7 includes a memory 71 and a processor 72, and the memory 71 and the processor 72 are communicatively connected via a bus.

[0098] Furthermore, the present application also provides a storage medium.

[0099] In a storage medium embodiment according to the present application, the storage medium can be configured to store a program for executing the motor fault diagnosis method of the above method embodiment, and the program can be loaded and run by the processor to implement the above motor fault diagnosis method. For ease of explanation, only the parts related to the embodiment of the present application are shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present application. The storage medium can be a storage device formed by various electronic devices. As an example, the storage medium in the embodiment of the present application is a non-temporary storage medium.

[0100] Those skilled in the art should be able to appreciate that, although the various steps in the above embodiments are described in a specific order, those skilled in the art can understand that, in order to achieve the effects of the present application, different steps do not have to be executed in such an order, and they can be executed simultaneously (in parallel) or in other orders. These adjusted schemes are equivalent technical schemes to the technical schemes described in the present application, and therefore will also fall within the scope of protection of the present application.

[0101] So far, the technical solution of the present application has been described in conjunction with an embodiment shown in the accompanying drawings, but it is easy for those skilled in the art to understand that the protection scope of the present application is obviously not limited to these specific embodiments. Without departing from the principles of the present application, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present application.

Claims

1. A motor fault diagnosis method, characterized in that: The method comprises: Obtaining a three-phase voltage signal sequence and a three-phase current signal sequence of the motor; Acquire a three-phase voltage fundamental frequency signal sequence based on the three-phase voltage signal sequence, and acquire a three-phase current fundamental frequency signal sequence based on the three-phase current signal sequence, wherein the time lengths corresponding to the three-phase voltage fundamental frequency signal sequence and the three-phase current fundamental frequency signal sequence are both preset time lengths; Based on the three-phase voltage fundamental frequency signal sequence, an a-phase negative-sequence component sequence of the voltage fundamental frequency signal is obtained; based on the three-phase current fundamental frequency signal sequence, an a-phase negative-sequence component sequence of the current fundamental frequency signal is obtained; Based on the a-phase negative-sequence component sequence of the voltage fundamental frequency signal and the a-phase negative-sequence component sequence of the current fundamental frequency signal, a statistical mean value of the negative-sequence impedance within the preset time length is obtained by convolution; Based on the statistical mean value of the negative-sequence impedance and a preset negative-sequence impedance threshold, it is determined whether a turn-to-turn short circuit fault occurs in the motor.

2. The motor fault diagnosis method according to claim 1, characterized in that: The method further comprises: Based on the three-phase voltage baseband signal sequence, a negative sequence component sequence of the a-phase of the voltage baseband signal is obtained by fast Fourier transform and considering spectrum leakage; Based on the three-phase current fundamental frequency signal sequence, a phase a negative sequence component sequence of the current fundamental frequency signal is obtained through fast Fourier transform and considering spectrum leakage.

3. The motor fault diagnosis method according to claim 2, characterized in that: The method further comprises: Performing fast Fourier transform on the three-phase baseband signal sequences respectively to obtain three-phase baseband frequency domain signal sequences, wherein the three-phase baseband signal sequences include the three-phase voltage baseband signal sequences and the three-phase current baseband signal sequences, and the three-phase baseband frequency domain signal sequences include the three-phase voltage baseband frequency domain signal sequences and the three-phase current baseband frequency domain signal sequences; Based on the three-phase voltage fundamental frequency domain signal sequence, a frequency domain signal sequence of the a-phase negative-sequence component of the voltage fundamental frequency signal is obtained by converting the vector, and an inverse fast Fourier transform is performed on the frequency domain signal sequence of the a-phase negative-sequence component of the voltage fundamental frequency signal to obtain a negative-sequence component sequence of the a-phase of the voltage fundamental frequency signal; Based on the three-phase current fundamental frequency domain signal sequence, a frequency domain signal sequence of the a-phase negative-sequence component of the current fundamental frequency signal is obtained by converting the vector, and an inverse fast Fourier transform is performed on the frequency domain signal sequence of the a-phase negative-sequence component of the current fundamental frequency signal to obtain a sequence of the a-phase negative-sequence component of the current fundamental frequency signal.

4. The motor fault diagnosis method according to claim 3, characterized in that: "Based on the three-phase voltage fundamental frequency domain signal sequence, obtaining the frequency domain signal sequence of the a-phase negative sequence component of the voltage fundamental frequency signal by converting the vector" includes: Based on the fundamental frequency point sequence number, a preset number of sequence elements are symmetrically extracted from the three-phase voltage fundamental frequency domain signal sequence to obtain a three-phase voltage fundamental frequency domain signal basic matrix, wherein the fundamental frequency point sequence number is determined based on the fundamental frequency and the spectrum resolution, and the preset number is determined based on the spectrum leakage; Based on the three-phase voltage fundamental frequency domain signal basic matrix and the conversion vector, obtaining the frequency domain basic vector of the a-phase negative sequence component of the voltage fundamental frequency signal; The frequency domain basis vector of the a-phase negative-sequence component of the voltage baseband signal is expanded to obtain a frequency domain signal sequence of the a-phase negative-sequence component of the voltage baseband signal.

5. The motor fault diagnosis method according to claim 3, characterized in that: "Based on the three-phase current fundamental frequency domain signal sequence, obtaining the frequency domain signal sequence of the a-phase negative sequence component of the current fundamental frequency signal by converting the vector" includes: Based on the fundamental frequency point sequence number, a preset number of sequence elements are symmetrically extracted from the three-phase current fundamental frequency domain signal sequence to obtain a three-phase current fundamental frequency domain signal basic matrix, wherein the fundamental frequency point sequence number is determined based on the fundamental frequency and the spectrum resolution, and the preset number is determined based on the spectrum leakage; Based on the three-phase current fundamental frequency domain signal basic matrix and the conversion vector, obtaining the frequency domain basic vector of the a-phase negative sequence component of the current fundamental frequency signal; The frequency domain basis vector of the a-phase negative sequence component of the current fundamental frequency signal is expanded to obtain a frequency domain signal sequence of the a-phase negative sequence component of the current fundamental frequency signal.

6. The motor fault diagnosis method according to claim 1, characterized in that: “Acquiring the statistical mean of the negative-sequence impedance within the preset time length by convolution based on the a-phase negative-sequence component sequence of the voltage fundamental frequency signal and the a-phase negative-sequence component sequence of the current fundamental frequency signal” includes: Reconstructing and expanding the a-phase negative-sequence component sequence of the voltage fundamental frequency signal to obtain a voltage fundamental frequency negative-sequence component sequence; Reconstructing the sequence number of the a-phase negative-sequence component sequence of the current fundamental frequency signal to obtain a current fundamental frequency negative-sequence component sequence; Based on the voltage fundamental frequency negative sequence component sequence, the current fundamental frequency negative sequence component sequence and the parameters of the convolution kernel, the statistical mean of the negative sequence impedance is obtained, wherein the parameters of the convolution kernel are obtained according to the convolution equation between the sinusoidal voltage signal and the sinusoidal current signal.

7. The motor fault diagnosis method according to claim 6, characterized in that: The method further comprises: The convolution equation is constructed based on a convolution step size of 2.

8. The motor fault diagnosis method according to claim 1, characterized in that: “Judging whether a turn-to-turn short circuit fault occurs in the motor based on the statistical mean value of the negative-sequence impedance and a preset negative-sequence impedance threshold” includes: Obtaining an impedance change ratio between a statistical mean value of the negative-sequence impedance and the negative-sequence impedance threshold; When the statistical mean of the negative-sequence impedance is less than the negative-sequence impedance threshold, the turn-to-turn short circuit fault is determined based on a preset impedance variation interval.

9. A smart device, characterized in that: include: at least one processor; and, a memory communicatively coupled to the at least one processor; Wherein, a computer program is stored in the memory, and when the computer program is executed by the at least one processor, the motor fault diagnosis method according to any one of claims 1 to 8 is implemented.

10. A storage medium storing a plurality of program codes, characterized in that: The program code is suitable for being loaded and run by a processor to execute the motor fault diagnosis method according to any one of claims 1 to 8.

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