CN112254910A - Motor rotor broken bar fault detection method and system based on fusion correlation spectrum - Google Patents
Motor rotor broken bar fault detection method and system based on fusion correlation spectrum Download PDFInfo
- Publication number
- CN112254910A CN112254910A CN202011077825.5A CN202011077825A CN112254910A CN 112254910 A CN112254910 A CN 112254910A CN 202011077825 A CN202011077825 A CN 202011077825A CN 112254910 A CN112254910 A CN 112254910A
- Authority
- CN
- China
- Prior art keywords
- signal
- motor
- fusion
- vibration
- stator current
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M7/00—Vibration-testing of structures; Shock-testing of structures
- G01M7/02—Vibration-testing by means of a shake table
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/34—Testing dynamo-electric machines
- G01R31/343—Testing dynamo-electric machines in operation
Abstract
The invention discloses a motor rotor broken bar fault detection method and system based on fusion correlation spectra, which are characterized in that a first stator current signal and a first vibration signal of a motor to be identified and diagnosed within a preset time interval are collected in real time, Hilbert transform is respectively carried out on the first stator current signal and the first vibration signal to obtain a stator current modulus signal and a vibration modulus signal, direct current components in the stator current modulus signal and the vibration modulus signal are filtered to obtain a second stator current signal and a second vibration signal, and fusion correlation spectrum analysis is carried out on the second stator current signal and the second vibration signal to obtain a fusion correlation spectrogram; judging whether the motor has a broken bar fault by using the obtained fusion-related spectrogram, and if the fusion-related spectrogram has 2sf0And judging that the motor rotor has the fault of broken bars at present by the fault component spectrum peak of frequency multiplication, wherein s is the motor slip ratio, f0Is the fundamental frequency.
Description
Technical Field
The invention belongs to the technical field of motor fault identification, and particularly relates to a motor rotor broken bar fault detection method and system based on fusion correlation spectrum.
Background
An asynchronous motor is an alternating current motor, also called an induction motor, and is mainly used as a motor. When the stator winding of the asynchronous motor is connected with a three-phase symmetrical alternating current power supply, three-phase symmetrical current flows through the stator winding, fundamental wave rotating magnetomotive force is established in an air gap, and a fundamental wave rotating magnetic field is generated. The rotor winding conductors cut the rotating magnetic field to produce induced electrical potentials and corresponding currents in the rotor windings. The rotor current interacts with the rotating magnetic field in the air gap to produce an electromagnetic torque, thereby driving the rotor to rotate. According to the electromagnetic torque generation principle, when the asynchronous motor runs electrically, the rotating speed of the asynchronous motor is lower than the synchronous rotating speed of a magnetic field.
The asynchronous motor has the obvious advantages of simple structure, reliable operation, easy manufacture, low price, firmness, durability, high working efficiency, good working characteristics and the like, and is widely applied to various industrial production fields of metallurgy, coal, mines, machinery, oil fields and the like, wherein the number of cage type asynchronous motors accounts for about 85 percent of the total number of the whole asynchronous motor. When the motor is overloaded or frequently started and braked, the rotor guide bars are subjected to overlarge alternating stress such as mechanical stress, electromagnetic stress, centrifugal force, thermal stress and the like, and the rotor has certain inherent defects, so that the motor is likely to have faults such as broken bars, end ring cracking and the like. Research shows that the rotor broken bar fault accounts for about 10% of the motor fault, so that the air gap magnetic field is distorted slightly, various performance indexes of the motor are deteriorated, and the motor is subjected to stator and rotor phase friction and is burnt out seriously, thereby causing huge economic loss. Therefore, the method is particularly important for diagnosing the initial fault of the motor.
In the existing motor broken bar fault detection method, current signal spectrum analysis is widely applied due to the fact that the current signal spectrum analysis is convenient to obtain and contains abundant fault information. However, in the conventional current spectrum analysis, the fault identification signal is single and is based on detecting the fault frequency component (1-2s) f in the current spectrum0Whether two working conditions that fault of the broken bar and motor load fluctuation are difficult to distinguish exist or not easily causes misjudgment. And in the broken strip of the motorAt the initial stage of the fault, the amplitude of the frequency component reflecting the fault of the broken bar in the current spectrogram is very small compared with the amplitude of the fundamental frequency, and the identification difficulty of the motor fault is increased due to the influence of fundamental frequency leakage. The invention patent 201510148103.7 provides a method for detecting a broken bar fault of a cage type induction motor rotor based on a vibration signal, which is characterized in that a frequency spectrogram of the vibration signal is detected to be (1-3s) f under the stable operation of the motor0And (1+ s) f0And whether a larger vibration peak value exists at the frequency position or not is realized, so that the detection of the broken bar fault of the cage type induction motor rotor is realized. The frequency component of the radial electromagnetic force wave generated by the interaction of the air gap additional magnetic field and the stator magnetic field caused by the broken bar fault is complex, so that f is (1-3s)0、(1+s)f0The accurate identification of the frequency of faults is more difficult.
Disclosure of Invention
In view of at least one defect or improvement requirement of the prior art, the invention provides a motor rotor fault detection method and system based on fusion correlation spectrum, and aims to solve the problem that the fault frequency component at the initial stage of fault is very small compared with the fundamental component of the signal and is difficult to identify and detect.
In order to achieve the above object, according to an aspect of the present invention, there is provided a method for detecting a motor rotor bar breakage fault based on a fusion correlation spectrum, including the following steps:
acquiring a first stator current signal and a first vibration signal of a diagnostic motor to be identified in real time within a preset time interval, respectively carrying out Hilbert transform on the first stator current signal and the first vibration signal to obtain a stator current modulus signal and a vibration modulus signal, and filtering direct current components in the stator current modulus signal and the vibration modulus signal to obtain a second stator current signal and a second vibration signal;
performing fusion correlation spectrum analysis on the second stator current signal and the second vibration signal to obtain a fusion correlation spectrogram;
whether the motor has a broken bar fault or not is judged by using the obtained fusion-related spectrogram, which specifically comprises the following steps: if fusion-related spectrogram exists 2sf0And the frequency multiplication fault component spectrum peak thereof, judging that the motor rotor has the fault of broken bars at presentWhere s is the motor slip, f0Is the fundamental frequency.
As a further improvement of the present invention, a signal filtering method is adopted to filter out direct current components in the stator current modulus signal and the vibration modulus signal, and specifically the method comprises the following steps:
the notch filter at the specified frequency of 0Hz is set so that the input signal is rapidly attenuated at the frequency point of 0Hz to filter out the direct current component of the signal.
As a further improvement of the present invention, if there is a broken bar fault in the present motor, the first stator current signal is approximately expressed as:
i＝Im cos(wt-α)+Idl cos[(1-2s)w0t-β1]+Idr cos[(1+2s)w0t-β2]
the stator current is transformed by Hilbert into:
the stator current modulus signal at this time can be expressed as:
wherein, Im、Idl、Idr、α、β1、β2Stator phase current fundamental component and broken bar fault (1-2s) f0Side frequency component, broken bar fault (1+2s) f0Amplitude and phase of the side-frequency component, w0Is an alternating current angular frequency.
As a further improvement of the invention, the specific calculation formula of the fusion correlation spectrum analysis is as follows:
0≤Cxy(f)≤1
wherein, Cxy(f) Is a current signal sumThe amplitude of the fusion correlation spectrum of the vibration signals represents the correlation degree of the frequency spectrums of the two signals under a certain frequency, Pxy(f) For cross-power spectral density estimation of two signals, Pxx(f) For self-power spectral density estimation of current signals, Pyy(f) Is a self-power spectral density estimate of the vibration signal.
In order to achieve the above object, according to another aspect of the present invention, there is provided a motor rotor bar breakage fault detection system based on a fusion correlation spectrum, the system including:
the signal acquisition module is used for acquiring a first stator current signal and a first vibration signal of the motor to be identified and diagnosed within a preset time interval in real time;
the filtering module is used for respectively carrying out Hilbert transform on the first stator current signal and the first vibration signal to obtain a stator current modulus signal and a vibration modulus signal, and filtering direct current components in the stator current modulus signal and the vibration modulus signal to obtain a second stator current signal and a second vibration signal;
the fusion correlation spectrum analysis module is used for performing fusion correlation spectrum analysis on the second stator current signal and the second vibration signal to obtain a fusion correlation spectrogram;
the fault analysis module is used for judging whether the motor has a broken bar fault by using the obtained fusion-related spectrogram, and specifically comprises the following steps: if fusion-related spectrogram exists 2sf0And judging that the motor rotor has the fault of broken bars at present by the fault component spectrum peak of frequency multiplication, wherein s is the motor slip ratio, f0Is the fundamental frequency.
As a further improvement of the present invention, the filtering module filters out the dc component in the stator current modulus signal and the vibration modulus signal by using a signal filtering method, specifically:
the notch filter at the specified frequency of 0Hz is set so that the input signal is rapidly attenuated at the frequency point of 0Hz to filter out the direct current component of the signal.
As a further improvement of the present invention, if there is a broken bar fault in the present motor, the first stator current signal is approximately expressed as:
i＝Im cos(wt-α)+Idl cos[(1-2s)w0t-β1]+Idr cos[(1+2s)w0t-β2]
the stator current is transformed by Hilbert into:
the stator current modulus signal at this time can be expressed as:
wherein, Im、Idl、Idr、α、β1、β2Stator phase current fundamental component and broken bar fault (1-2s) f0Side frequency component, broken bar fault (1+2s) f0Amplitude and phase of the side-frequency component, w0Is an alternating current angular frequency.
As a further improvement of the invention, the specific calculation formula of the fusion correlation spectrum analysis is as follows:
0≤Cxy(f)≤1
wherein, Cxy(f) Is a fusion correlation spectrum of the current signal and the vibration signal, the amplitude of the fusion correlation spectrum represents the correlation degree of the frequency spectrums of the two signals under a certain frequency, Pxy(f) For cross-power spectral density estimation of two signals, Pxx(f) For self-power spectral density estimation of current signals, Pyy(f) Is a self-power spectral density estimate of the vibration signal.
To achieve the above object, according to another aspect of the present invention, there is provided a computer readable medium storing a computer program executable by an electronic device, the computer program causing the electronic device to perform the steps of the above method when the computer program runs on the electronic device.
To achieve the above object, according to another aspect of the present invention, there is provided a terminal device comprising at least one processing unit, and at least one memory unit, wherein the memory unit stores a computer program which, when executed by the processing unit, causes the processing unit to perform the steps of the above method.
In general, compared with the prior art, the above technical solution contemplated by the present invention can achieve the following beneficial effects:
(1) the invention provides a motor rotor broken bar fault detection method and system based on fusion correlation spectrum, which completely convert the fault characteristic frequency of a stator current signal and a motor vibration signal of a motor after a broken bar fault occurs into a corresponding low-frequency range of 0-ksf through Hilbert conversion0And (k 1, 2, 3.) to eliminate the influence of fundamental frequency leakage, so that the fault characteristic frequency is easier to identify, and the problem that the fault frequency component at the initial stage of the fault is very small compared with the fundamental component of the signal and is difficult to identify and detect is solved.
(2) According to the motor rotor broken bar fault detection method and system based on the fusion correlation spectrum, provided by the invention, the direct-current component of the Hilbert modulus signal is filtered by a notch filtering method, so that the interference in the subsequent fusion correlation spectrum analysis of the current signal and the vibration signal is avoided. The traditional method for filtering the signal direct current component comprises the following steps: the signal is subjected to Hilbert transformation twice and then a negative value is obtained, and the method increases the calculation amount and complexity of signal processing; the dc component is filtered out by subtracting the average value of the signal, and this method is only suitable for removing the dc component of the stationary signal. The method for filtering out the direct current component by the notch filtering can be simply realized by software or hardware, and is less influenced by signal fluctuation.
(3) According to the motor rotor broken bar fault detection method and system based on the fusion correlation spectrum, provided by the invention, the difficulty in identifying broken bar faults is simplified through a method of fusion correlation spectrum analysis. The correlation spectrum function essentially expresses the similarity of two signals and is a measure of the linear correlation of the two signals. This causes the amplitude of the current signal self-power spectrum and the vibration signal self-power spectrum at the same frequency to be enhanced and vice versa to be weakened. By utilizing the characteristic, after the motor has the broken bar fault, the characteristic frequency spectrum component for representing the broken bar fault can be accurately extracted from the fusion related spectrum, which is beneficial to the reliable diagnosis of the broken bar fault.
Drawings
FIG. 1 is a schematic diagram of a motor rotor broken bar fault detection method based on fusion correlation spectra according to an embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating comparison of current signal self-power spectral density estimates of a normal motor, a first abnormal motor and a second abnormal motor provided by an embodiment of the present invention;
FIG. 3 is a schematic diagram comparing the vibration signal self-power spectral density estimates of a normal motor, a first abnormal motor and a second abnormal motor provided by the embodiment of the invention;
FIG. 4 is a schematic comparison of cross-power spectral density estimates of current signals and vibration signals for a normal motor, a first abnormal motor, and a second abnormal motor provided by embodiments of the present invention;
fig. 5 is a schematic comparison diagram of fusion-related spectrograms of current signals and vibration signals of a normal motor, a first abnormal motor and a second abnormal motor according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The structure and the operating principle of the motor rotor broken bar fault detection method and the system based on the fusion correlation spectrum provided by the invention are explained in detail below with reference to the embodiment and the accompanying drawings.
Fig. 1 is a schematic diagram of a method for detecting a motor rotor bar breakage fault based on a fusion correlation spectrum according to a preferred embodiment of the present invention. As shown in fig. 1, the method includes:
s1, acquiring a first stator current signal and a first vibration signal of a diagnostic motor to be identified in real time within a preset time interval, respectively carrying out Hilbert transform on the first stator current signal and the first vibration signal to obtain a stator current modulus signal and a vibration modulus signal, and filtering direct current components in the stator current modulus signal and the vibration modulus signal to obtain a second stator current signal and a second vibration signal;
specifically, the stator current modulus signal and the vibration modulus signal are obtained by respectively carrying out Hilbert conversion on the collected stator current signal and the collected motor vibration signal. If there is a broken bar fault in the present motor, the stator current will be modulated, and as an example, the first stator current signal may be expressed approximately as:
i＝Im cos(wt-α)+Idl cos[(1-2s)w0t-β1]+Idr cos[(1+2s)w0t-β2]
the stator current is transformed by Hilbert into:
the stator current modulus signal at this time can be expressed as:
wherein, Im、Idl、Idr、α、β1、β2Stator phase current fundamental component and broken bar fault (1-2s) f0Side frequency component, broken bar fault (1+2s) f0Amplitude and phase of the side frequency component, s being motor slip, w0Is an alternating current angular frequency.
Besides causing modulation of three-phase current, the rotor broken bar fault also can generate unbalanced radial electromagnetic force which acts on a stator core and generates electromagnetic vibration with characteristic frequency different from that of a normal motor. When the motor breaks, an additional magnetic field is generated in the air gap:
wherein r ═ 1, ± 2, ± 3rFor the additional field amplitude, s is the slip.
Based on Maxwell's equations, the radial electromagnetic stress is proportional to the square of the air gap radial flux density. Under the condition of rotor broken bars, the additional electromagnetic stress is mainly generated by interaction of a stator magnetic field and an additional magnetic field, the interaction of a stator fundamental wave magnetic field and the additional magnetic field is considered, and the expression of the additional radial electromagnetic stress is as follows:
according to the expression of the additional radial electromagnetic stress, after the motor has a broken bar fault, the order of the additional radial electromagnetic wave generated in the air gap is r +/-1, and the frequency is
The electromagnetic stress of the motor acts on the stator core to cause electromagnetic vibration with characteristic frequency.
Taking the force wave order r of + -2, + -4, + -6, + -8, + -10 as an example, the part of the characteristic frequency of the additional radial electromagnetic stress calculated is 2sf0、(1-s)f0、(3-s)f0、(2-2s)f0、(4-2s)f0、(1-3s)f0、(3-3s)f0、(5-3s)f0、(2-4s)f0、(4-4s)f0、(6-4s)f0、(3-5s)f0、(5-5s)f0、(4-6s)f0、 (6-6s)f0。
Similar to the derivation of the stator current modulus signal, the frequency spectrum from which the vibration signal can be derived will also contain ksf0(k ═ 1, 2, 3, 4, 5, 6.) fault signature components. The expression of the stator current modulus signal shows that the stator current modulus signal contains a certain direct current signal component,it is therefore necessary to filter out the interference of the dc component.
As an example, a method of signal filtering may be used to filter out dc components in the stator current modulus signal and the vibration modulus signal, where the method of signal notch filtering is:
the notch filter at the specified frequency of 0Hz is set, so that the input signal is rapidly attenuated at the frequency point of 0Hz to achieve the effect of filtering out the direct-current component of the signal, and therefore, the frequency response formula of the 0Hz dip filter can be expressed as:
of course, the above filtering of the dc component by using the notch filter is only an example, and other dc filtering methods may be selected according to the requirement.
S2, performing fusion correlation spectrum analysis on the second stator current signal and the second vibration signal to obtain a fusion correlation spectrogram;
specifically, the method for fusion correlation spectrum analysis of the current signal and the vibration signal comprises the following steps:
when the motor has a broken bar fault, the modulus signal obtained by Hilbert conversion of the stator phase current signal and the motor vibration signal simultaneously contains 2sf0And the fault frequency component of the frequency multiplication can make the fault characteristic frequency more prominent by adopting a method of fusing related spectrum analysis, and the diagnosis of the current running state of the motor is convenient.
The calculation formula for fusion-related spectral analysis can be expressed as:
0≤Cxy(f)≤1
wherein, Cxy(f) Is a fusion correlation spectrum of the current signal and the vibration signal, the amplitude of the fusion correlation spectrum represents the correlation degree of the frequency spectrums of the two signals under a certain frequency, Pxy(f) For cross-power spectral density estimation of two signals, Pxx(f) Is composed ofSelf-powered spectral density estimation of current signals, Pyy(f) Is a self-power spectral density estimate of the vibration signal.
S3, judging whether the motor has a broken bar fault by using the obtained fusion-related spectrogram, specifically comprising the following steps: if present, the frequency is 2sf0And judging that the motor rotor has a broken bar fault at present if the frequency multiplication fault component spectrum peak is reached, otherwise, the motor is normally operated at present.
As an example, the motor broken bar fault characteristic signal can be easily identified and detected by a method of fusion correlation spectrum analysis of the current signal and the vibration signal, and the method can be applied to broken bar fault detection of the motor under power frequency or variable frequency power supply.
A motor rotor broken bar fault detection system based on fusion correlation spectrum comprises:
the signal acquisition module is used for acquiring a first stator current signal and a first vibration signal of the motor to be identified and diagnosed within a preset time interval in real time;
the filtering module is used for respectively carrying out Hilbert transform on the first stator current signal and the first vibration signal to obtain a stator current modulus signal and a vibration modulus signal, and filtering direct current components in the stator current modulus signal and the vibration modulus signal to obtain a second stator current signal and a second vibration signal;
the fusion correlation spectrum analysis module is used for performing fusion correlation spectrum analysis on the second stator current signal and the second vibration signal to obtain a fusion correlation spectrogram;
the fault analysis module is used for judging whether the motor has a broken bar fault by using the obtained fusion-related spectrogram, and specifically comprises the following steps: if fusion-related spectrogram exists 2sf0And judging that the motor rotor has the fault of broken bars at present by the fault component spectrum peak of frequency multiplication, wherein s is the motor slip ratio, f0Is the fundamental frequency.
The implementation principle and technical effect of the system are similar to those of the method, and are not described herein again.
Table 1 shows the basic parameters of the motor according to the embodiment of the present invention. As shown in Table 1, a 4-pole 3-phase motor is taken as an example, corresponding simulation verification is carried out in Ansoft Maxwell, MATLAB/SIMULINK software, and the basic relevant parameters of the motor are shown in Table 1.
Table 1 fundamental relevant parameters of the motor of the embodiment of the present invention
Finite element modeling and simulation are carried out on the motor in Ansoft Maxwell software, and the simulation of the motor broken bar fault can be realized by changing the material of the conducting bar. The bar material in the normal motor model is selected from cast aluminum material cast _ aluminum _75C carried by the RMxprt material library, and the conductivity of the bar material is 23000000 siemens/m. The broken bar fault is simulated by presetting the conductivity of certain conducting bar materials to be 2 siemens/m. The finite element simulation time is set to 3s, and the simulation step length is set to 0.001 s. The current signals and radial electromagnetic force signals corresponding to a normal motor, a first abnormal motor (a broken bar motor) and a second abnormal motor (a broken two bar motor) are respectively extracted through simulation post-processing operation, and then the signals are further fused and correlated through MATLAB (matrix laboratory), so that the health state of the current motor is judged through whether fault characteristic frequency spectrum peaks exist in a fused and correlated spectrogram.
Fig. 2, fig. 3, fig. 4 and fig. 5 are respectively a normal motor, a first abnormal motor and a second abnormal motor, corresponding to the current signal self-power spectral density estimation, the vibration signal self-power spectral density estimation, the cross-power spectral density estimation of the current signal and the vibration signal, and the fusion correlation spectrogram of the current signal and the vibration signal according to the preferred embodiment of the present invention.
As shown in FIG. 2, the self-power spectral density estimation graphs of the current signals of the first abnormal motor and the second abnormal motor are at 2sf0、4sf0The spectral peak of the frequency component reflecting the broken bar fault information is greatly increased compared with the normal motor, the amplitude is up to more than 20dB,the current modulus signal at the moment is indicated to have characteristic frequency information capable of reflecting the motor broken bar fault.
As shown in FIG. 3, the self-power spectral density estimation graphs of the vibration signals of the first abnormal motor and the second abnormal motor are at 2sf0、4sf0Compared with a normal motor, the spectral peak at the frequency component reflecting the broken bar fault information is increased to a certain extent, but the amplitude change is not obvious, so that the difficulty of accurately identifying the fault is increased if the broken bar fault of the motor is diagnosed only by a single vibration modulus signal.
As shown in FIG. 4, the cross power spectral density estimation graphs of the current signal and the vibration signal of the first abnormal motor and the second abnormal motor are at 2sf0、4sf0Compared with a normal motor, the spectrum peak at the frequency component reflecting the fault information of the broken bar is obviously increased, the amplitude of the current signal self-power spectrum and the amplitude of the vibration signal self-power spectrum at the same frequency are enhanced, and the amplitude of the current signal self-power spectrum and the amplitude of the vibration signal self-power spectrum at the same frequency are weakened. The method for diagnosing the broken bar fault of the motor by using the current signal and the vibration signal to fuse the related spectrums is feasible.
As shown in fig. 5, the fused correlation spectrogram of the current signal and the vibration signal of the first abnormal motor and the second abnormal motor appears 2sf compared with the normal motor0、4sf0And the characteristic frequency component of the fault information of the broken bar is reflected, and the amplitude of the fault component is increased along with the aggravation of the fault degree of the broken bar. Whether the motor has a broken bar fault or not can be conveniently and accurately identified through the fusion correlation spectrogram of the current signal and the vibration signal, and the effectiveness of the method is verified.
The embodiment also provides an electronic device, which includes at least one processor and at least one memory, where the memory stores a computer program, and when the computer program is executed by the processor, the processor is enabled to execute the steps of the method for detecting a motor rotor broken bar fault based on a fusion correlation spectrum in the embodiment, and specific steps refer to the embodiment and are not described herein again; in this embodiment, the types of the processor and the memory are not particularly limited, for example: the processor may be a microprocessor, digital information processor, on-chip programmable logic system, or the like; the memory may be volatile memory, non-volatile memory, a combination thereof, or the like.
The electronic device may also communicate with one or more external devices (e.g., keyboard, pointing terminal, display, etc.), with one or more terminals that enable a user to interact with the electronic device, and/or with any terminals (e.g., network card, modem, etc.) that enable the electronic device to communicate with one or more other computing terminals. Such communication may be through an input/output (I/O) interface. Also, the electronic device may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public Network, such as the internet) via the Network adapter.
The present embodiment also provides a computer readable medium storing a computer program executable by an electronic device, and when the computer program runs on the electronic device, the electronic device is caused to execute the steps of the motor rotor broken bar fault detection method based on the fusion correlation spectrum in the embodiment. Types of computer readable media include, but are not limited to, storage media such as SD cards, usb disks, fixed hard disks, removable hard disks, and the like.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A motor rotor broken bar fault detection method based on fusion correlation spectrum is characterized by comprising the following steps:
acquiring a first stator current signal and a first vibration signal of a diagnostic motor to be identified in real time within a preset time interval, respectively carrying out Hilbert transform on the first stator current signal and the first vibration signal to obtain a stator current modulus signal and a vibration modulus signal, and filtering direct current components in the stator current modulus signal and the vibration modulus signal to obtain a second stator current signal and a second vibration signal;
performing fusion correlation spectrum analysis on the second stator current signal and the second vibration signal to obtain a fusion correlation spectrogram;
whether the motor has a broken bar fault or not is judged by using the obtained fusion-related spectrogram, which specifically comprises the following steps: if fusion-related spectrogram exists 2sf0And judging that the motor rotor has the fault of broken bars at present by the fault component spectrum peak of frequency multiplication, wherein s is the motor slip ratio, f0Is the fundamental frequency.
2. The method for detecting the motor rotor broken bar fault based on the fusion correlation spectrum as claimed in claim 1, wherein a signal filtering method is adopted to filter out direct current components in the stator current modulus signal and the vibration modulus signal, and specifically comprises the following steps:
the notch filter at the specified frequency of 0Hz is set so that the input signal is rapidly attenuated at the frequency point of 0Hz to filter out the direct current component of the signal.
3. The motor rotor broken bar fault detection method based on the fusion correlation spectrum as claimed in claim 1 or 2, wherein if the current motor has a broken bar fault, the first stator current signal is approximately expressed as:
i＝Imcos(wt-α)+Idlcos[(1-2s)w0t-β1]+Idrcos[(1+2s)w0t-β2]
the stator current is transformed by Hilbert into:
the stator current modulus signal at this time can be expressed as:
wherein, Im、Idl、Idr、α、β1、β2Stator phase current fundamental component and broken bar fault (1-2s) f0Side frequency component, broken bar fault (1+2s) f0Amplitude and phase of the side-frequency component, w0Is an alternating current angular frequency.
4. The method for detecting the motor rotor broken bar fault based on the fusion correlation spectrum as claimed in claim 3, wherein the specific calculation formula of the fusion correlation spectrum analysis is as follows:
0≤Cxy(f)≤1
wherein, Cxy(f) Is a fusion correlation spectrum of the current signal and the vibration signal, the amplitude of the fusion correlation spectrum represents the correlation degree of the frequency spectrums of the two signals under a certain frequency, Pxy(f) For cross-power spectral density estimation of two signals, Pxx(f) For self-power spectral density estimation of current signals, Pyy(f) Is a self-power spectral density estimate of the vibration signal.
5. A motor rotor broken bar fault detection system based on fusion correlation spectrum is characterized by comprising:
the signal acquisition module is used for acquiring a first stator current signal and a first vibration signal of the motor to be identified and diagnosed within a preset time interval in real time;
the filtering module is used for respectively carrying out Hilbert transform on the first stator current signal and the first vibration signal to obtain a stator current modulus signal and a vibration modulus signal, and filtering direct current components in the stator current modulus signal and the vibration modulus signal to obtain a second stator current signal and a second vibration signal;
the fusion correlation spectrum analysis module is used for performing fusion correlation spectrum analysis on the second stator current signal and the second vibration signal to obtain a fusion correlation spectrogram;
the fault analysis module is used for judging whether the motor has a broken bar fault by using the obtained fusion-related spectrogram, and specifically comprises the following steps: if fusion-related spectrogram exists 2sf0And judging that the motor rotor has the fault of broken bars at present by the fault component spectrum peak of frequency multiplication, wherein s is the motor slip ratio, f0Is the fundamental frequency.
6. The system for detecting the motor rotor broken bar fault based on the fusion correlation spectrum according to claim 5, wherein the filtering module filters the direct current component in the stator current modulus signal and the vibration modulus signal by a signal filtering method, and specifically comprises:
the notch filter at the specified frequency of 0Hz is set so that the input signal is rapidly attenuated at the frequency point of 0Hz to filter out the direct current component of the signal.
7. The system for detecting the broken bar fault of the motor rotor based on the fusion correlation spectrum as claimed in claim 5 or 6, wherein if the broken bar fault of the current motor exists, the first stator current signal is approximately expressed as:
i＝Imcos(wt-α)+Idlcos[(1-2s)w0t-β1]+Idrcos[(1+2s)w0t-β2]
the stator current is transformed by Hilbert into:
the stator current modulus signal at this time can be expressed as:
wherein, Im、Idl、Idr、α、β1、β2Stator phase current fundamental component and broken bar fault (1-2s) f0A side frequency component,Broken bar fault (1+2s) f0Amplitude and phase of the side-frequency component, w0Is an alternating current angular frequency.
8. The system for detecting the motor rotor broken bar fault based on the fusion correlation spectrum as claimed in claim 7, wherein the specific calculation formula of the fusion correlation spectrum analysis is as follows:
0≤Cxy(f)≤1
wherein, Cxy(f) Is a fusion correlation spectrum of the current signal and the vibration signal, the amplitude of the fusion correlation spectrum represents the correlation degree of the frequency spectrums of the two signals under a certain frequency, Pxy(f) For cross-power spectral density estimation of two signals, Pxx(f) For self-power spectral density estimation of current signals, Pyy(f) Is a self-power spectral density estimate of the vibration signal.
9. A computer-readable medium, in which a computer program is stored which is executable by an electronic device, and which, when run on the electronic device, causes the electronic device to perform the steps of the method of any one of claims 1 to 4.
10. A terminal device, comprising at least one processing unit and at least one memory unit, wherein the memory unit stores a computer program which, when executed by the processing unit, causes the processing unit to carry out the steps of the method according to any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011077825.5A CN112254910B (en) | 2020-10-10 | 2020-10-10 | Motor rotor broken bar fault detection method and system based on fusion correlation spectrum |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011077825.5A CN112254910B (en) | 2020-10-10 | 2020-10-10 | Motor rotor broken bar fault detection method and system based on fusion correlation spectrum |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112254910A true CN112254910A (en) | 2021-01-22 |
| CN112254910B CN112254910B (en) | 2022-05-17 |
Family
ID=74242404
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011077825.5A Active CN112254910B (en) | 2020-10-10 | 2020-10-10 | Motor rotor broken bar fault detection method and system based on fusion correlation spectrum |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112254910B (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112924090A (en) * | 2021-01-28 | 2021-06-08 | 华中科技大学 | Motor air gap eccentric fault detection method and system based on electromagnetic stress analysis |
| CN113009334A (en) * | 2021-02-18 | 2021-06-22 | 华中科技大学 | Motor fault detection method and system based on wavelet packet energy analysis |
| CN113391207A (en) * | 2021-04-01 | 2021-09-14 | 国网宁夏电力有限公司检修公司 | Motor fault detection method, medium and system |
| CN114675183A (en) * | 2022-05-30 | 2022-06-28 | 华中科技大学 | Variable frequency motor broken bar fault detection method and system based on correlation analysis |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101025430A (en) * | 2007-03-28 | 2007-08-29 | 华北电力大学 | Cage type asynchronous motor rotor strip-broken failure detecting method |
| US7539549B1 (en) * | 1999-09-28 | 2009-05-26 | Rockwell Automation Technologies, Inc. | Motorized system integrated control and diagnostics using vibration, pressure, temperature, speed, and/or current analysis |
| CN101710162A (en) * | 2009-11-27 | 2010-05-19 | 华北电力大学（保定） | Motor rotor winding interturn short-circuit failure diagnosing method based on stator iron core vibration |
| CN102944842A (en) * | 2012-11-30 | 2013-02-27 | 华北电力大学（保定） | Detecting method for rotor broken bar fault of cage-type asynchronous motor |
| CN104749519A (en) * | 2015-03-12 | 2015-07-01 | 云南电网公司西双版纳供电局 | Correlation analysis based on-load voltage regulating transformer tapping switch operating state judgment method |
| EP2919027A1 (en) * | 2014-03-11 | 2015-09-16 | Rolls-Royce plc | Fault detection in induction machines |
| CN107544025A (en) * | 2017-08-30 | 2018-01-05 | 马鞍山马钢华阳设备诊断工程有限公司 | A kind of Asynchronous Motor Rotor-Bar Fault determination methods of composite electrical signal and vibration signal |
| CN110221137A (en) * | 2019-03-07 | 2019-09-10 | 国网上海市电力公司 | A kind of distribution transformer abnormal state detection method based on vibration acoustic correlation |
| CN111504676A (en) * | 2020-04-23 | 2020-08-07 | 中国石油大学(北京) | Equipment fault diagnosis method, device and system based on multi-source monitoring data fusion |
-
2020
- 2020-10-10 CN CN202011077825.5A patent/CN112254910B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7539549B1 (en) * | 1999-09-28 | 2009-05-26 | Rockwell Automation Technologies, Inc. | Motorized system integrated control and diagnostics using vibration, pressure, temperature, speed, and/or current analysis |
| CN101025430A (en) * | 2007-03-28 | 2007-08-29 | 华北电力大学 | Cage type asynchronous motor rotor strip-broken failure detecting method |
| CN101710162A (en) * | 2009-11-27 | 2010-05-19 | 华北电力大学（保定） | Motor rotor winding interturn short-circuit failure diagnosing method based on stator iron core vibration |
| CN102944842A (en) * | 2012-11-30 | 2013-02-27 | 华北电力大学（保定） | Detecting method for rotor broken bar fault of cage-type asynchronous motor |
| EP2919027A1 (en) * | 2014-03-11 | 2015-09-16 | Rolls-Royce plc | Fault detection in induction machines |
| CN104749519A (en) * | 2015-03-12 | 2015-07-01 | 云南电网公司西双版纳供电局 | Correlation analysis based on-load voltage regulating transformer tapping switch operating state judgment method |
| CN107544025A (en) * | 2017-08-30 | 2018-01-05 | 马鞍山马钢华阳设备诊断工程有限公司 | A kind of Asynchronous Motor Rotor-Bar Fault determination methods of composite electrical signal and vibration signal |
| CN110221137A (en) * | 2019-03-07 | 2019-09-10 | 国网上海市电力公司 | A kind of distribution transformer abnormal state detection method based on vibration acoustic correlation |
| CN111504676A (en) * | 2020-04-23 | 2020-08-07 | 中国石油大学(北京) | Equipment fault diagnosis method, device and system based on multi-source monitoring data fusion |
Non-Patent Citations (5)
| Title |
|---|
| 周京波等: "基于信息融合的感应电动机定子故障检测方法研究", 《船电技术》 * |
| 王巍: "信息融合技术在电动机故障诊断中的应用", 《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》 * |
| 王新等: "《机电设备故障诊断技术及应用》", 30 April 2014, 煤炭工业出版社 * |
| 陈健等: "基于振动噪声信号的永磁电机故障诊断", 《微电机》 * |
| 黄守盟: "《电力系统继电保护信号处理》", 30 June 1993, 水利电力出版社 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112924090A (en) * | 2021-01-28 | 2021-06-08 | 华中科技大学 | Motor air gap eccentric fault detection method and system based on electromagnetic stress analysis |
| CN113009334A (en) * | 2021-02-18 | 2021-06-22 | 华中科技大学 | Motor fault detection method and system based on wavelet packet energy analysis |
| CN113009334B (en) * | 2021-02-18 | 2022-07-01 | 华中科技大学 | Motor fault detection method and system based on wavelet packet energy analysis |
| CN113391207A (en) * | 2021-04-01 | 2021-09-14 | 国网宁夏电力有限公司检修公司 | Motor fault detection method, medium and system |
| CN114675183A (en) * | 2022-05-30 | 2022-06-28 | 华中科技大学 | Variable frequency motor broken bar fault detection method and system based on correlation analysis |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112254910B (en) | 2022-05-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112254910B (en) | Motor rotor broken bar fault detection method and system based on fusion correlation spectrum | |
| Ye et al. | Current signature analysis of induction motor mechanical faults by wavelet packet decomposition | |
| Didier et al. | A new approach to detect broken rotor bars in induction machines by current spectrum analysis | |
| Garcia-Perez et al. | The application of high-resolution spectral analysis for identifying multiple combined faults in induction motors | |
| Riera-Guasp et al. | A general approach for the transient detection of slip-dependent fault components based on the discrete wavelet transform | |
| Drif et al. | Discriminating the simultaneous occurrence of three-phase induction motor rotor faults and mechanical load oscillations by the instantaneous active and reactive power media signature analyses | |
| Faiz et al. | Mixed-fault diagnosis in induction motors considering varying load and broken bars location | |
| Sahraoui et al. | The use of a modified prony method to track the broken rotor bar characteristic frequencies and amplitudes in three-phase induction motors | |
| CN113009334B (en) | Motor fault detection method and system based on wavelet packet energy analysis | |
| Wang et al. | A review of Permanent Magnet Synchronous Motor fault diagnosis | |
| Faiz et al. | Effect of magnetic saturation on static and mixed eccentricity fault diagnosis in induction motor | |
| CN101025430A (en) | Cage type asynchronous motor rotor strip-broken failure detecting method | |
| CN108680858B (en) | Method and system for monitoring loss of field fault of permanent magnet synchronous motor rotor | |
| CN109738780A (en) | One tube open circuit detection method of multiphase corner connection brushless exciter rotating diode and system | |
| Çira et al. | A new approach to detect stator fault in permanent magnet synchronous motors | |
| Silva et al. | A method for measuring torque of squirrel-cage induction motors without any mechanical sensor | |
| Khelfi et al. | Induction motor rotor fault diagnosis using three-phase current intersection signal | |
| Göktas et al. | A new method to separate broken rotor failures and low frequency load oscillations in three-phase induction motor | |
| Mehrjou et al. | Analysis of statistical features based on start-up current envelope for broken rotor bar fault detection in line start permanent magnet synchronous motor | |
| CN111537881A (en) | Fault diagnosis method, device and equipment for asynchronous motor and readable storage medium | |
| Pilloni et al. | Fault detection in induction motors | |
| Faiz et al. | A review of application of signal processing techniques for fault diagnosis of induction motors–Part I | |
| Ahamed et al. | Novel diagnosis technique of mass unbalance in rotor of induction motor by the analysis of motor starting current at no load through wavelet transform | |
| Khelfi et al. | Temporal envelope detection by the square root of the three-phase currents for IM rotor fault diagnosis | |
| Bonet-Jara et al. | A precise, general, non-invasive and automatic speed estimation method for MCSA diagnosis and efficiency estimation of induction motors |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |