CN112560600B - Traction motor rotor broken bar fault diagnosis method and device - Google Patents

Traction motor rotor broken bar fault diagnosis method and device Download PDF

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CN112560600B
CN112560600B CN202011390638.2A CN202011390638A CN112560600B CN 112560600 B CN112560600 B CN 112560600B CN 202011390638 A CN202011390638 A CN 202011390638A CN 112560600 B CN112560600 B CN 112560600B
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value
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frequency band
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CN112560600A (en
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刘先升
贾焕军
刘帅
陈小军
刘泽涛
刘景涛
祖越
张贵强
武小明
梁新辉
李巍
周立辉
夏翠军
李丹丹
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CRRC Tangshan Co Ltd
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Abstract

The invention is suitable for the technical field of transportation, and provides a traction motor rotor broken bar fault diagnosis method and device, wherein the method comprises the following steps: collecting current signals of a motor train unit traction system network side; decomposing the current signals into a preset number of frequency bands, and carrying out signal reconstruction on signals corresponding to each frequency band to obtain reconstructed signals corresponding to each frequency band; obtaining a theoretical value of a fault characteristic frequency of a traction motor rotor broken bar in a network side current; inquiring fault characteristic frequency matched with the theoretical value of the fault characteristic frequency in the reconstruction signal corresponding to each frequency band to obtain an inquiry result; the fault of the broken bar of the traction motor rotor is determined according to the query result, so that the manual participation can be completely eliminated, the fault diagnosis of the broken bar of the traction motor rotor under the running state of the train is realized, and the fault diagnosis efficiency and the fault diagnosis accuracy are improved.

Description

Traction motor rotor broken bar fault diagnosis method and device
Technical Field
The invention belongs to the technical field of transportation, and particularly relates to a traction motor rotor broken bar fault diagnosis method and device.
Background
The railway construction of China is rapidly developed, and the operation safety of trains is of great concern. The traction motor is used as one of core components in a traction transmission system of the motor train unit to provide power for the train, and once the failure occurs, the operation safety of the train is affected. Motor rotor breakage is one of the common fault types of traction motors, if the fault types cannot be found and properly handled in time, the breakage of the broken bars can cause continuous breakage of adjacent conducting bars, and the broken conducting bars and stator windings can generate scratch under the condition of high-speed running, so that the sweeping fault is caused.
At present, the most common traction motor rotor broken bar fault diagnosis method is a frequency domain analysis method, and stator current signals are generally collected for frequency domain analysis. However, because the structure and the operation environment of the traction motor are special, the unbalance of the power grid voltage, the harmonic wave of the voltage converter and the like all have influence on the stator current of the traction motor, so that the stator current frequency spectrum is complex, and the common stator current frequency spectrum analysis method is difficult to effectively diagnose the faults of the traction motor. The difference of fault characteristic values generated by the motor rotor after faults in each phase of stator current can cause difficulty in selecting a fault threshold value, and in the traditional spectrum analysis method, a person mainly diagnoses faults by observing whether a spectrum peak exists at a fault characteristic frequency in a spectrum chart, so that the fault detection efficiency is low and errors are easy to occur.
Disclosure of Invention
In view of the above, the embodiment of the invention provides a method and a device for diagnosing a broken bar fault of a traction motor rotor, which aim to solve the problems that the broken bar fault diagnosis of the traction motor rotor is difficult to effectively diagnose, the diagnosis efficiency is low and the faults are easy to occur in the prior art.
To achieve the above object, a first aspect of the embodiments of the present invention provides a method for diagnosing a broken bar fault of a traction motor rotor, including:
Collecting current signals of a motor train unit traction system network side;
decomposing the current signals into a preset number of frequency bands, and carrying out signal reconstruction on signals corresponding to each frequency band to obtain reconstructed signals corresponding to each frequency band;
obtaining a theoretical value of a fault characteristic frequency of a traction motor rotor broken bar in a network side current;
inquiring fault characteristic frequency matched with the theoretical value of the fault characteristic frequency in the reconstruction signal corresponding to each frequency band to obtain an inquiry result;
and determining the fault of the broken bar of the traction motor rotor according to the query result.
As another embodiment of the present application, the decomposing the current signal into a preset number of frequency bands, and performing signal reconstruction on a signal corresponding to each frequency band to obtain a reconstructed signal corresponding to each frequency band, includes:
processing the current signal, eliminating the influence of fundamental frequency leakage in the current signal on fault characteristics, and obtaining a processed signal;
performing wavelet packet decomposition on the processed signals respectively to obtain decomposed signals corresponding to each decomposed frequency band;
and reconstructing the signals corresponding to each frequency band to obtain the reconstructed signals corresponding to each frequency band.
As another embodiment of the present application, the processing the current signal, eliminating an influence of fundamental frequency leakage in the current signal on a fault feature, to obtain a processed signal, includes:
performing Hilbert transformation on the current signal to obtain a Hilbert signal;
obtaining an envelope signal of the current signal according to the current signal and the Hilbert signal;
calculating an average envelope signal of the envelope signal according to the envelope signal;
and eliminating the average envelope signal in the envelope signal to obtain a processed signal.
As another embodiment of the present application, performing hilbert transformation on the current signal to obtain a hilbert signal includes:
according to
Figure BDA0002812627610000021
Obtaining a Hilbert signal;
wherein ,
Figure BDA0002812627610000031
representing the Hilbert signal, g (t) representing the current signal, t representing the time corresponding to the current signal;
the obtaining an envelope signal of the current signal according to the current signal and the hilbert signal includes:
according to
Figure BDA0002812627610000032
Obtaining an envelope signal of the current signal;
wherein a (t) represents an envelope signal of the current signal;
said removing said average envelope signal from said envelope signal resulting in a processed signal comprising:
According to
Figure BDA0002812627610000033
Obtaining a processed signal;
wherein A' (t) represents the processed signal,
Figure BDA0002812627610000034
representing the average envelope signal.
As another embodiment of the present application, the performing wavelet packet decomposition on the processed signals to obtain decomposed signals corresponding to each decomposed frequency band includes:
according to
Figure BDA0002812627610000035
Obtaining an ith coefficient corresponding to a 2 m-th sub-band and an ith coefficient corresponding to a (2m+1) -th sub-band of the j-th layer wavelet packet decomposition;
wherein ,di,j,2m Ith coefficient, d, representing the 2m th subband of the j-th layer wavelet packet decomposition i,j,2m+1 The ith coefficient representing the (2m+1) th subband representing the j-th layer wavelet packet decomposition, h (·) and g (·) represent the wavelet packet filter coefficients, d, respectively k,j+1,m The kth coefficients i, k, m, j of the mth subband representing the (j+1) -th layer wavelet packet decomposition are positive integers, respectively.
In another embodiment of the present application, the reconstructing the signal corresponding to each frequency band to obtain a reconstructed signal corresponding to each frequency band includes:
according to
Figure BDA0002812627610000036
Obtaining an ith coefficient of an mth sub-band of the (j+1) th layer wavelet packet after the reconstruction of the wavelet packet; />
wherein ,di,j+1,m ' the ith coefficient, d, representing the mth subband of the (j+1) -th layer wavelet packet after reconstruction of the wavelet packet k,j,2m Kth coefficient, d, representing the 2m th subband of the jth layer wavelet packet decomposition k,j,2m+1 The kth coefficient of the (2m+1) th subband representing the decomposition of the jth layer wavelet packet.
As another embodiment of the present application, after the obtaining the reconstructed signal corresponding to each frequency band, the method further includes:
respectively carrying out fast Fourier transform on the reconstructed signals corresponding to each frequency band to obtain a fast Fourier transform spectrogram corresponding to each frequency band;
inquiring the fault characteristic frequency matched with the theoretical value of the fault characteristic frequency in the reconstruction signal corresponding to each frequency band to obtain an inquiry result, wherein the inquiry result comprises the following steps:
and inquiring the fault characteristic frequency matched with the theoretical value of the fault characteristic frequency in the fast Fourier transform spectrogram corresponding to each frequency band to obtain an inquiring result.
As another embodiment of the present application, the querying, in the fast fourier transform spectrogram corresponding to each frequency band, a fault characteristic frequency matching with the theoretical value of the fault characteristic frequency, to obtain a query result includes:
sequentially inquiring whether a fault characteristic frequency matched with a theoretical value of the fault characteristic frequency exists in each fast Fourier transform spectrogram;
If the fault characteristic frequency matched with the theoretical value of the fault characteristic frequency exists in the current fast Fourier transform spectrogram, determining the fault characteristic frequency and the type of the fault characteristic frequency; and continuously searching the rest fast Fourier transform spectrograms, and determining the fault characteristic frequencies of different types from the fault characteristic frequencies to obtain all fault characteristic frequencies matched with the theoretical values of the fault characteristic frequencies in the fast Fourier transform spectrograms.
As another embodiment of the present application, the querying whether there is a fault feature frequency matching the theoretical value of the fault feature frequency in each fast fourier transform spectrogram sequentially includes:
determining a maximum frequency value in a frequency band taking a theoretical value of the fault characteristic frequency as a center frequency;
determining a fundamental wave frequency value in a current fast Fourier transform spectrogram;
calculating the ratio of the maximum frequency value to the fundamental frequency value, and detecting whether the ratio is larger than a first preset critical value or not;
if there is a fault characteristic frequency matching the theoretical value of the fault characteristic frequency in the current fast fourier transform spectrogram, determining the fault characteristic frequency and the type of the fault characteristic frequency, including:
When the ratio is greater than the first preset critical value, determining that the maximum frequency value is a fault characteristic frequency matched with the theoretical value of the fault characteristic frequency, and determining the type of the maximum frequency value;
after the detecting whether the ratio is greater than a first preset critical value, the method further comprises:
when the ratio is not greater than the first preset critical value, adding 1 to the decomposition level corresponding to the current search, and detecting whether the new decomposition level reaches a second preset critical value;
if the new decomposition level reaches a second preset critical value, determining the maximum frequency value as a fault characteristic frequency matched with the theoretical value of the fault characteristic frequency;
and if the new decomposition level does not reach the second preset critical value, re-determining the maximum frequency value in the frequency band taking the theoretical value of the fault characteristic frequency as the center frequency and the subsequent steps.
A second aspect of an embodiment of the present invention provides a traction motor rotor bar breakage fault diagnosis apparatus, including:
the acquisition module is used for acquiring current signals of the net side of the traction system of the motor train unit;
the signal processing module is used for decomposing the current signals into a preset number of frequency bands, and carrying out signal reconstruction on the signals corresponding to each frequency band to obtain reconstructed signals corresponding to each frequency band;
The acquisition module is used for acquiring a theoretical value of a fault characteristic frequency of the traction motor rotor broken bar in the network side current;
the query module is used for querying the fault characteristic frequency matched with the theoretical value of the fault characteristic frequency in the reconstruction signal corresponding to each frequency band to obtain a query result;
and the determining module is used for determining the fault of the broken bar of the traction motor rotor according to the query result.
Compared with the prior art, the embodiment of the invention has the beneficial effects that: compared with the prior art, the invention acquires and processes the current signals at the network side of the traction system of the motor train unit to obtain the fast Fourier transform spectrograms of the reconstructed signals in a plurality of frequency bands, and finally performs fault diagnosis by searching the fault characteristic frequency matched with the theoretical value in each fast Fourier transform spectrogram, thereby completely breaking away from the manual participation, realizing the fault diagnosis of the broken bar of the traction motor rotor under the running state of the train, and improving the fault diagnosis efficiency and the fault diagnosis accuracy.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic implementation flow chart of a fault diagnosis method for a broken bar of a traction motor rotor according to an embodiment of the present invention;
fig. 2 is a schematic diagram of obtaining a reconstructed signal corresponding to each frequency band according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of processing a current signal to eliminate the influence of fundamental frequency leakage in the current signal on fault characteristics and obtain a processed signal according to the embodiment of the present invention;
FIG. 4 is a schematic diagram of a process for searching a characteristic frequency of a motor rotor broken bar fault for each fast Fourier transform spectrogram according to an embodiment of the present invention;
fig. 5 is a schematic diagram of a traction motor rotor broken bar fault diagnosis device provided by an embodiment of the present invention;
fig. 6 is a schematic diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to illustrate the technical scheme of the invention, the following description is made by specific examples.
Fig. 1 is a schematic implementation flow chart of a fault diagnosis method for a broken bar of a traction motor rotor according to an embodiment of the present invention, which is described in detail below.
And step 101, collecting current signals of a motor train unit traction system network side.
And 102, decomposing the current signals into a preset number of frequency bands, and performing signal reconstruction on signals corresponding to each frequency band to obtain reconstructed signals corresponding to each frequency band.
Optionally, in the step 102, the current signal is decomposed into a preset number of frequency bands, and the signal corresponding to each frequency band is subjected to signal reconstruction to obtain a reconstructed signal corresponding to each frequency band, which may include the steps shown in fig. 2.
And step 201, processing the current signal, eliminating the influence of fundamental frequency leakage in the current signal on fault characteristics, and obtaining a processed signal.
Optionally, in the step 201, the current signal is processed, the influence of the fundamental frequency leakage in the current signal on the fault feature is eliminated, and the processed signal may include a step as shown in fig. 3.
Step 301, performing hilbert transformation on the current signal to obtain a hilbert signal.
Alternatively, this step may be based on
Figure BDA0002812627610000071
Obtaining a Hilbert signal;
wherein ,
Figure BDA0002812627610000072
and g (t) represents the current signal, and t represents the time corresponding to the current signal.
And step 302, obtaining an envelope signal of the current signal according to the current signal and the Hilbert signal.
Alternatively, this step may be based on
Figure BDA0002812627610000073
Obtaining an envelope signal of the current signal; wherein a (t) represents an envelope signal of the current signal.
Alternatively, it may be based on
Figure BDA0002812627610000074
Obtaining a complex number A (t) is g + A die of (t).
Step 303, calculating an average envelope signal of the envelope signal according to the envelope signal.
And step 304, eliminating the average envelope signal in the envelope signal to obtain a processed signal.
Alternatively, this step may be based on
Figure BDA0002812627610000075
Obtaining a processed signal;
wherein A' (t) represents the processed signal,
Figure BDA0002812627610000076
representing the average envelope signal.
In the present embodiment, in the course of performing the Hilbert transform, the fundamental component in the original current signal becomes a direct current component, and then the formula
Figure BDA0002812627610000081
The process of removing the direct current component is represented, so that the influence of fundamental frequency leakage on fault characteristics can be eliminated, and the fault diagnosis result can be more accurate.
And 202, respectively carrying out wavelet packet decomposition on the processed signals to obtain decomposed signals corresponding to each frequency band after decomposition.
After the processed signal a' (t) is obtained, in order to refine the frequency bin and improve the analysis effect of the signal, the processed signal may be first subjected to wavelet packet decomposition and reconstruction. Alternatively, a wavelet packet decomposition algorithm is used to divide the processed signal into 2 3 The spurious signals of each frequency band are reconstructed by using a wavelet packet reconstruction algorithm. In the wavelet packet decomposition, the signal is decomposed into a plurality of frequency bands, the number of which may be determined according to the analyzed signal and the specific situation, and in the present embodiment, the division of the processed signal into 8 frequency bands is merely an exemplary illustration.
Optionally, the wavelet packet decomposition algorithm includes: according to
Figure BDA0002812627610000082
And obtaining an ith coefficient corresponding to the (2m+1) th sub-band and an ith coefficient corresponding to the (2m+1) th sub-band of the j-th layer wavelet packet decomposition, wherein the coefficient is the decomposed digital signal.
wherein ,di,j,2m Ith coefficient, d, representing the 2m th subband of the j-th layer wavelet packet decomposition i,j,2m+1 The ith coefficient representing the (2m+1) th subband representing the j-th layer wavelet packet decomposition, h (·) and g (·) represent the wavelet packet filter coefficients, respectively, which are the unique series of coefficients related to the wavelet function, d k,j+1,m The kth coefficients i, k, m, j of the mth subband representing the (j+1) -th layer wavelet packet decomposition are positive integers, respectively.
And 203, reconstructing the signals corresponding to each frequency band to obtain reconstructed signals corresponding to each frequency band.
Optionally, the step may include: according to
Figure BDA0002812627610000083
Obtaining an ith coefficient of an mth sub-band of the (j+1) th layer wavelet packet after the reconstruction of the wavelet packet;
wherein ,di,j+1,m ' the ith coefficient, d, representing the mth subband of the (j+1) -th layer wavelet packet after reconstruction of the wavelet packet k,j,2m Kth coefficient, d, representing the 2m th subband of the jth layer wavelet packet decomposition k,j,2m+1 The kth coefficient of the (2m+1) th subband representing the decomposition of the jth layer wavelet packet.
After the reconstruction signal is obtained, step 103 is continued.
And 103, obtaining a theoretical value of the fault characteristic frequency of the traction motor rotor broken bar in the network side current.
Alternatively, this step may be performed according to f=2sf 0 Obtaining a theoretical value of a fault characteristic frequency of a traction motor rotor broken bar in a network side current;
wherein f represents the theoretical value of the fault characteristic frequency, s represents the motor slip, and f 0 Representing the stator current fundamental frequency.
Optionally, before step 103 or after step 104, the method may further include: and respectively carrying out fast Fourier transform on the reconstructed signals corresponding to each frequency band to obtain a fast Fourier transform spectrogram corresponding to each frequency band.
And 104, inquiring the fault characteristic frequency matched with the theoretical value of the fault characteristic frequency in the reconstruction signal corresponding to each frequency band to obtain an inquiring result.
Optionally, the step may include: and inquiring the fault characteristic frequency matched with the theoretical value of the fault characteristic frequency in the fast Fourier transform spectrogram corresponding to each frequency band to obtain an inquiring result.
Optionally, querying, in the fast fourier transform spectrogram corresponding to each frequency band, a fault characteristic frequency that matches the theoretical value of the fault characteristic frequency, where obtaining a query result may include:
whether a fault characteristic frequency matched with a theoretical value of the fault characteristic frequency exists in each fast Fourier transform spectrogram or not can be sequentially inquired;
if the fault characteristic frequency matched with the theoretical value of the fault characteristic frequency exists in the current fast Fourier transform spectrogram, determining the fault characteristic frequency and the type of the fault characteristic frequency; and continuously searching the rest fast Fourier transform spectrograms, and determining the fault characteristic frequencies of different types from the fault characteristic frequencies to obtain all fault characteristic frequencies matched with the theoretical values of the fault characteristic frequencies in the fast Fourier transform spectrograms.
Optionally, as shown in fig. 4, the process of searching the characteristic frequency of the motor rotor bar fault for each fast fourier transform spectrogram may include:
step 401, determining a maximum frequency value in a frequency band with the theoretical value of the fault characteristic frequency as a center frequency.
Optionally, before this step, the method may further include: initializing a flag bit m and a decomposition layer number n so that all decomposition layers in the current fast Fourier transform spectrogram can be traversed. Alternatively, the purpose of setting the flag bit here is to determine whether there is a fault characteristic frequency matching with the theoretical value of the fault characteristic frequency in the current fft spectrum chart according to the value of the flag bit, and when there is a fault characteristic frequency, the value of the output flag bit m is set to 1, and when there is no flag bit, the value of the output flag bit m is an initialized value, for example, the value of the initialized flag bit m is 0.
Step 402, determining fundamental frequency values in a current fast fourier transform spectrogram.
Step 403, calculating the ratio of the maximum frequency value to the fundamental frequency value.
Step 404, detecting whether the ratio is greater than a first preset threshold.
Optionally, the first preset critical value, that is, the fault threshold, may be set according to actual requirements, and in this embodiment, the value of the first preset critical value is not limited.
Optionally, step 405 is performed when the ratio is greater than the first preset threshold, and step 406 is performed when the ratio is not greater than the first preset threshold.
Step 405, determining the maximum frequency value as the fault characteristic frequency matching the theoretical value of the fault characteristic frequency, and determining the type of the maximum frequency value.
Alternatively, in this step, the value of the flag bit m may be set to 1 and output, which indicates that there is a fault characteristic frequency matching with the theoretical value of the fault characteristic frequency in the current fast fourier transform spectrum chart.
Step 406, adding 1 to the decomposition level corresponding to the current search when the ratio is not greater than the first preset critical value, and detecting whether the new decomposition level reaches a second preset critical value;
optionally, the second preset threshold may be set according to actual requirements, which in this embodiment is not limited to the value of the first preset threshold.
Step 407, ending the flow if the new decomposition level reaches a second preset threshold;
optionally, in this step, if the new decomposition level reaches a second preset critical value, it is indicated that no fault characteristic frequency matching with the theoretical value of the fault characteristic frequency is found in the current fast fourier transform spectrogram, and the flag bit m is output, where the value of m is the initialized value.
Optionally, if the new decomposition level does not reach the second preset threshold, the step 401 and the subsequent steps are re-executed.
And 105, determining the fault of the broken bar of the traction motor rotor according to the query result.
According to the traction motor rotor broken bar fault diagnosis method, the network side current signals of the traction system of the motor train unit are collected and processed to obtain the fast Fourier transform spectrograms of the reconstructed signals in a plurality of frequency bands, and finally fault diagnosis is carried out by searching the fault characteristic frequency matched with the theoretical value in each fast Fourier transform spectrogram, so that manual participation can be completely eliminated, fault diagnosis of the traction motor rotor broken bar in a running state of a train is realized, fault diagnosis efficiency and fault diagnosis accuracy are improved, compared with the fault diagnosis method based on analysis of stator current signals in the prior art, the traction motor rotor broken bar fault diagnosis method provided by the embodiment is easier to measure the fault characteristic signals, is easier to reasonably set a fault threshold value, avoids misdiagnosis and is convenient to implement.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.
Corresponding to the method for diagnosing a broken bar fault of a traction motor rotor described in the above embodiments, fig. 5 shows an exemplary diagram of a device for diagnosing a broken bar fault of a traction motor rotor according to an embodiment of the present invention. As shown in fig. 5, the apparatus may include: an acquisition module 501, a signal processing module 502, an acquisition module 503, a query module 504 and a determination module 505.
The acquisition module 501 is used for acquiring current signals of a motor train unit traction system network side;
the signal processing module 502 is configured to decompose the current signal into a preset number of frequency bands, and perform signal reconstruction on a signal corresponding to each frequency band to obtain a reconstructed signal corresponding to each frequency band;
an obtaining module 503, configured to obtain a theoretical value of a fault characteristic frequency of a broken bar of a traction motor rotor in a network side current;
a query module 504, configured to query, in the reconstructed signal corresponding to each frequency band, a fault characteristic frequency that matches the theoretical value of the fault characteristic frequency, so as to obtain a query result;
a determining module 505, configured to determine a fault of the traction motor rotor broken bar according to the query result.
Optionally, the signal processing module 502 may be configured to:
processing the current signal, eliminating the influence of fundamental frequency leakage in the current signal on fault characteristics, and obtaining a processed signal;
Performing wavelet packet decomposition on the processed signals respectively to obtain decomposed signals corresponding to each decomposed frequency band;
and reconstructing the signals corresponding to each frequency band to obtain the reconstructed signals corresponding to each frequency band.
Optionally, the signal processing module 502 processes the current signal, eliminates the influence of fundamental frequency leakage in the current signal on fault characteristics, and when obtaining a processed signal, may be used to:
performing Hilbert transformation on the current signal to obtain a Hilbert signal;
obtaining an envelope signal of the current signal according to the current signal and the Hilbert signal;
calculating an average envelope signal of the envelope signal according to the envelope signal;
and eliminating the average envelope signal in the envelope signal to obtain a processed signal.
Optionally, the signal processing module 502 is based on
Figure BDA0002812627610000121
Obtaining a Hilbert signal;
wherein ,
Figure BDA0002812627610000122
representing the Hilbert signal, g (t) representing the current signal, t representing the time corresponding to the current signal;
the signal processing module 502 is based on
Figure BDA0002812627610000123
Obtaining an envelope signal of the current signal;
wherein a (t) represents an envelope signal of the current signal;
The signal processing module 502 is based on
Figure BDA0002812627610000124
Obtaining a processed signal;
wherein A 'is'(t) represents the processed signal,
Figure BDA0002812627610000125
representing the average envelope signal.
Optionally, when the signal processing module 502 performs wavelet packet decomposition on the processed signals to obtain decomposed signals corresponding to each decomposed frequency band, the signal processing module may be configured to:
according to
Figure BDA0002812627610000131
Obtaining an ith coefficient corresponding to a 2 m-th sub-band and an ith coefficient corresponding to a (2m+1) -th sub-band of the j-th layer wavelet packet decomposition;
wherein ,di,j,2m Ith coefficient, d, representing the 2m th subband of the j-th layer wavelet packet decomposition i,j,2m+1 The ith coefficient representing the (2m+1) th subband representing the j-th layer wavelet packet decomposition, h (·) and g (·) represent the wavelet packet filter coefficients, d, respectively k,j+1,m The kth coefficients i, k, m, j of the mth subband representing the (j+1) -th layer wavelet packet decomposition are positive integers, respectively.
Optionally, the signal processing module 502 may reconstruct the signal corresponding to each frequency band, and when obtaining a reconstructed signal corresponding to each frequency band, may be used to:
according to
Figure BDA0002812627610000132
Obtaining an ith coefficient of an mth sub-band of the (j+1) th layer wavelet packet after the reconstruction of the wavelet packet;
wherein ,di,j+1,m ' the ith coefficient, d, representing the mth subband of the (j+1) -th layer wavelet packet after reconstruction of the wavelet packet k,j,2m Kth coefficient, d, representing the 2m th subband of the jth layer wavelet packet decomposition k,j,2m+1 The kth coefficient of the (2m+1) th subband representing the decomposition of the jth layer wavelet packet.
Optionally, after the obtaining the reconstructed signal corresponding to each frequency band, the signal processing module 502 is further configured to:
respectively carrying out fast Fourier transform on the reconstructed signals corresponding to each frequency band to obtain a fast Fourier transform spectrogram corresponding to each frequency band;
the query module 504 queries the reconstructed signal corresponding to each frequency band for a fault characteristic frequency that matches the theoretical value of the fault characteristic frequency, and when obtaining a query result, may be used to:
and inquiring the fault characteristic frequency matched with the theoretical value of the fault characteristic frequency in the fast Fourier transform spectrogram corresponding to each frequency band to obtain an inquiring result.
Optionally, the querying module 504 queries, in the fast fourier transform spectrogram corresponding to each frequency band, a fault characteristic frequency that matches the theoretical value of the fault characteristic frequency, and when obtaining a query result, may be configured to:
sequentially inquiring whether a fault characteristic frequency matched with a theoretical value of the fault characteristic frequency exists in each fast Fourier transform spectrogram;
If the fault characteristic frequency matched with the theoretical value of the fault characteristic frequency exists in the current fast Fourier transform spectrogram, determining the fault characteristic frequency and the type of the fault characteristic frequency; and continuously searching the rest fast Fourier transform spectrograms, and determining the fault characteristic frequencies of different types from the fault characteristic frequencies to obtain all fault characteristic frequencies matched with the theoretical values of the fault characteristic frequencies in the fast Fourier transform spectrograms.
Optionally, when the querying module 504 queries whether there is a fault feature frequency matching the theoretical value of the fault feature frequency in each fast fourier transform spectrogram in sequence, the querying module may be configured to:
determining a maximum frequency value in a frequency band taking a theoretical value of the fault characteristic frequency as a center frequency;
determining a fundamental wave frequency value in a current fast Fourier transform spectrogram;
calculating the ratio of the maximum frequency value to the fundamental frequency value, and detecting whether the ratio is larger than a first preset critical value or not;
and when the ratio is greater than the first preset critical value, determining that the maximum frequency value is a fault characteristic frequency matched with the theoretical value of the fault characteristic frequency, and determining the type of the maximum frequency value;
When the ratio is not greater than the first preset critical value, adding 1 to the decomposition level corresponding to the current search, and detecting whether the new decomposition level reaches a second preset critical value;
if the new decomposition level reaches a second preset critical value, determining the maximum frequency value as a fault characteristic frequency matched with the theoretical value of the fault characteristic frequency;
and if the new decomposition level does not reach the second preset critical value, re-determining the maximum frequency value in the frequency band taking the theoretical value of the fault characteristic frequency as the center frequency and the subsequent steps.
According to the traction motor rotor broken bar fault diagnosis device, the network side current signals of the traction system of the motor train unit are collected and processed to obtain the fast Fourier transform spectrograms of the reconstructed signals in a plurality of frequency bands, and finally fault diagnosis is carried out by searching the fault characteristic frequency matched with the theoretical value in each fast Fourier transform spectrogram, so that manual participation can be completely separated, fault diagnosis of the traction motor rotor broken bar in a running state of a train is realized, fault diagnosis efficiency and fault diagnosis accuracy are improved, compared with the fault diagnosis method based on analysis of stator current signals in the prior art, the fault diagnosis method for the traction motor rotor broken bar is easier to measure the fault characteristic signals, is easier to reasonably set a fault threshold value, avoids misdiagnosis and is convenient to implement.
Fig. 6 is a schematic diagram of a terminal device according to an embodiment of the present invention. As shown in fig. 6, the terminal device 600 of this embodiment includes: a processor 601, a memory 602, and a computer program 603, such as a traction motor rotor breakage fault diagnosis program, stored in said memory 602 and executable on said processor 601. The steps of the embodiment of the method for diagnosing a broken bar fault of a rotor of a traction motor, such as steps 101 to 105 shown in fig. 1, or steps shown in fig. 2, 3 and 4, are implemented when the processor 601 executes the computer program 603, and the functions of the modules in the embodiments of the apparatus, such as the functions of the modules 501 to 505 shown in fig. 5, are implemented when the processor 601 executes the computer program 603.
By way of example, the computer program 603 may be partitioned into one or more program modules that are stored in the memory 602 and executed by the processor 601 to implement the present invention. The one or more program modules may be a series of computer program instruction segments capable of performing a specific function for describing the execution of the computer program 603 in the traction motor rotor bar fault diagnosis device or terminal apparatus 600. For example, the computer program 603 may be divided into an acquisition module 501, a signal processing module 502, an acquisition module 503, a query module 504, and a determination module 505, where specific functions of the modules are shown in fig. 5, and are not described in detail herein.
The terminal device 600 may be a computing device such as a desktop computer, a notebook computer, a palm computer, and a cloud server. The terminal device may include, but is not limited to, a processor 601, a memory 602. It will be appreciated by those skilled in the art that fig. 6 is merely an example of a terminal device 600 and is not limiting of the terminal device 600, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., the terminal device may also include input and output devices, network access devices, buses, etc.
The processor 601 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 602 may be an internal storage unit of the terminal device 600, for example, a hard disk or a memory of the terminal device 600. The memory 602 may also be an external storage device of the terminal device 600, for example, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the terminal device 600. Further, the memory 602 may also include both an internal storage unit and an external storage device of the terminal device 600. The memory 602 is used for storing the computer program and other programs and data required by the terminal device 600. The memory 602 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other manners. For example, the apparatus/terminal device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical function division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. . Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.

Claims (7)

1. A traction motor rotor breakage fault diagnosis method, comprising:
collecting current signals of a motor train unit traction system network side;
decomposing the current signals into a preset number of frequency bands, carrying out signal reconstruction on signals corresponding to each frequency band to obtain reconstructed signals corresponding to each frequency band, and respectively carrying out fast Fourier transformation on the reconstructed signals corresponding to each frequency band to obtain a fast Fourier transformation spectrogram corresponding to each frequency band;
obtaining a theoretical value of a fault characteristic frequency of a traction motor rotor broken bar in a network side current;
inquiring fault characteristic frequency matched with the theoretical value of the fault characteristic frequency in the reconstruction signal corresponding to each frequency band to obtain an inquiry result;
Determining the fault of the broken bar of the traction motor rotor according to the query result;
inquiring the fault characteristic frequency matched with the theoretical value of the fault characteristic frequency in the reconstruction signal corresponding to each frequency band to obtain an inquiry result, wherein the inquiry result comprises the following steps:
determining a maximum frequency value in a frequency band taking a theoretical value of the fault characteristic frequency as a center frequency;
determining a fundamental wave frequency value in a current fast Fourier transform spectrogram;
calculating the ratio of the maximum frequency value to the fundamental frequency value, and detecting whether the ratio is larger than a first preset critical value or not;
when the ratio is greater than the first preset critical value, determining that the maximum frequency value is a fault characteristic frequency matched with the theoretical value of the fault characteristic frequency, and determining the type of the maximum frequency value;
when the ratio is not greater than the first preset critical value, adding 1 to the decomposition level corresponding to the current search, and detecting whether the new decomposition level reaches a second preset critical value;
if the new decomposition level reaches a second preset critical value, determining the maximum frequency value as a fault characteristic frequency matched with the theoretical value of the fault characteristic frequency;
And if the new decomposition level does not reach the second preset critical value, re-determining the maximum frequency value in the frequency band taking the theoretical value of the fault characteristic frequency as the center frequency and the subsequent steps.
2. The traction motor rotor breakage fault diagnosis method according to claim 1, wherein the decomposing the current signal into a preset number of frequency bands, and performing signal reconstruction on the signal corresponding to each frequency band to obtain a reconstructed signal corresponding to each frequency band, includes:
processing the current signal, eliminating the influence of fundamental frequency leakage in the current signal on fault characteristics, and obtaining a processed signal;
performing wavelet packet decomposition on the processed signals respectively to obtain decomposed signals corresponding to each decomposed frequency band;
and reconstructing the decomposition signals corresponding to each frequency band to obtain the reconstruction signals corresponding to each frequency band.
3. The method for diagnosing a fault of a broken bar of a rotor of a traction motor according to claim 2, wherein the processing the current signal to eliminate an influence of fundamental frequency leakage in the current signal on a fault characteristic, and obtaining a processed signal comprises:
Performing Hilbert transformation on the current signal to obtain a Hilbert signal;
obtaining an envelope signal of the current signal according to the current signal and the Hilbert signal;
calculating an average envelope signal of the envelope signal according to the envelope signal;
and eliminating the average envelope signal in the envelope signal to obtain a processed signal.
4. The traction motor rotor bar break fault diagnosis method as claimed in claim 3, wherein said performing hilbert transformation on said current signal to obtain a hilbert signal comprises:
according to
Figure QLYQS_1
Obtaining a Hilbert signal;
wherein ,
Figure QLYQS_2
representing the Hilbert signal,/A->
Figure QLYQS_3
Representing the current signal,/->
Figure QLYQS_4
Representing the time corresponding to the current signal;
the obtaining an envelope signal of the current signal according to the current signal and the hilbert signal includes:
according to
Figure QLYQS_5
Obtaining an envelope signal of the current signal;
wherein ,
Figure QLYQS_6
an envelope signal representative of the current signal;
said removing said average envelope signal from said envelope signal resulting in a processed signal comprising:
according to
Figure QLYQS_7
Obtaining a processed signal;
wherein ,
Figure QLYQS_8
Representing the processed signal, +_>
Figure QLYQS_9
Representing the average envelope signal.
5. The traction motor rotor breakage fault diagnosis method as claimed in claim 3, wherein the performing wavelet packet decomposition on the processed signals to obtain decomposed signals corresponding to each decomposed frequency band comprises:
according to
Figure QLYQS_10
Get->
Figure QLYQS_11
Layer wavelet packet decomposition 2 +.>
Figure QLYQS_12
The corresponding +.>
Figure QLYQS_13
Personal coefficients and->
Figure QLYQS_14
The corresponding +.>
Figure QLYQS_15
A coefficient;
wherein ,
Figure QLYQS_23
indicate->
Figure QLYQS_19
Layer wavelet packet decomposition 2 +.>
Figure QLYQS_25
The%>
Figure QLYQS_22
Coefficient of->
Figure QLYQS_24
Indicate->
Figure QLYQS_29
Layer wavelet packet decomposition +.>
Figure QLYQS_33
The%>
Figure QLYQS_28
Coefficient of->
Figure QLYQS_32
and />
Figure QLYQS_17
Respectively representing wavelet packet filter coefficients, +.>
Figure QLYQS_27
Indicate->
Figure QLYQS_18
Layer wavelet packet decomposition +.>
Figure QLYQS_30
The%>
Figure QLYQS_20
Coefficient of->
Figure QLYQS_26
、/>
Figure QLYQS_16
、/>
Figure QLYQS_31
、/>
Figure QLYQS_21
Respectively positive integers.
6. The method for diagnosing a broken bar fault of a rotor of a traction motor according to claim 5, wherein the reconstructing the decomposed signal corresponding to each frequency band to obtain the reconstructed signal corresponding to each frequency band comprises:
according to
Figure QLYQS_34
Obtaining the reconstructed wavelet packetFirst->
Figure QLYQS_35
Layer wavelet packet->
Figure QLYQS_36
The%>
Figure QLYQS_37
A coefficient;
wherein ,
Figure QLYQS_40
representing +. >
Figure QLYQS_42
Layer wavelet packet->
Figure QLYQS_45
The%>
Figure QLYQS_41
The number of coefficients is set to be the number of coefficients,
Figure QLYQS_43
indicate->
Figure QLYQS_46
Layer wavelet packet decomposition 2 +.>
Figure QLYQS_48
The%>
Figure QLYQS_38
Coefficient of->
Figure QLYQS_44
Indicate->
Figure QLYQS_47
Layer wavelet packet decomposition +.>
Figure QLYQS_49
The%>
Figure QLYQS_39
And coefficients.
7. A traction motor rotor breakage fault diagnosis device, characterized by comprising:
the acquisition module is used for acquiring current signals of the net side of the traction system of the motor train unit;
the signal processing module is used for decomposing the current signals into a preset number of frequency bands, carrying out signal reconstruction on the signals corresponding to each frequency band to obtain reconstructed signals corresponding to each frequency band, and respectively carrying out fast Fourier transformation on the reconstructed signals corresponding to each frequency band to obtain a fast Fourier transformation spectrogram corresponding to each frequency band;
the acquisition module is used for acquiring a theoretical value of a fault characteristic frequency of the traction motor rotor broken bar in the network side current;
the query module is used for querying the fault characteristic frequency matched with the theoretical value of the fault characteristic frequency in the reconstruction signal corresponding to each frequency band to obtain a query result;
the determining module is used for determining the faults of the broken bars of the traction motor rotor according to the query result;
wherein, the inquiry module is further used for:
Determining a maximum frequency value in a frequency band taking a theoretical value of the fault characteristic frequency as a center frequency;
determining a fundamental wave frequency value in a current fast Fourier transform spectrogram;
calculating the ratio of the maximum frequency value to the fundamental frequency value, and detecting whether the ratio is larger than a first preset critical value or not;
when the ratio is greater than the first preset critical value, determining that the maximum frequency value is a fault characteristic frequency matched with the theoretical value of the fault characteristic frequency, and determining the type of the maximum frequency value;
when the ratio is not greater than the first preset critical value, adding 1 to the decomposition level corresponding to the current search, and detecting whether the new decomposition level reaches a second preset critical value;
if the new decomposition level reaches a second preset critical value, determining the maximum frequency value as a fault characteristic frequency matched with the theoretical value of the fault characteristic frequency;
and if the new decomposition level does not reach the second preset critical value, re-determining the maximum frequency value in the frequency band taking the theoretical value of the fault characteristic frequency as the center frequency and the subsequent steps.
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