CN105738061B - A kind of image analysis method of vibration signal - Google Patents
A kind of image analysis method of vibration signal Download PDFInfo
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Abstract
The invention discloses a kind of image analysis method of vibration signal, including establish filter stage and detection-phase；Establishing filter stage includes the vibration signal of horizontal direction carrying out experience wavelet transformation, obtains empirical modal, empirical modal is carried out into Hilbert transform, obtains spectral magnitude, carries out border detection to spectral magnitude, establishes bandpass filter；Detection-phase is filtered including vibration signal is first passed through into row bandpass filter, and exports row image along row, then is filtered by row bandpass filter, and exports row image along row, and experience wavelet transformation figures are tieed up in obtain vibration signal 2.Present invention has the advantages that：By obtain vibration signal 2 dimension experience wavelet transformation figures, image by Bo Liye frequency or difference 2 dimension AM-AM mode form.Therefore, feature recognition and fault diagnosis can be easy to based on the different vibration signal characteristics of 2 dimension graphical analyses.
Description
Technical field
The present invention and analysis of vibration signal field, more particularly to a kind of image analysis method of vibration signal.
Background technology
Experience wavelet transformation (EWT) is a kind of new adaptive signal decomposition method, and this method inherits EMD and small wavelength-division
The respective advantage of analysis method, adaptively split Fourier spectrum by extracting frequency domain maximum point to separate different mode,
Then bandpass filter group is constructed so as to construct orthogonal wavelet function in frequency domain adaptive, there is compact schemes Fourier with extraction
AM/FM amplitude modulation/frequency modulation (AM-FM) composition of frequency spectrum.
Research direction in recent years refers to this method in mechanical fault diagnosis, it is proposed that one kind is become based on experience small echo
The mechanical failure diagnostic method changed, and carried out comparative analysis with EMD methods.But above-mentioned mechanical failure diagnostic method is all one
The dimension of kind 1, accident analysis individually can only be carried out to the vibration signal in a direction, can not be by 2 dimensions, the vibration of both direction
Signal carries out detection and the analysis directly on image, causes the situation that is not accurate, taking time and effort of fault diagnosis to occur.
The content of the invention
The present invention be solve above-mentioned technical problem be provide it is a kind of it is more accurate, more comprehensively, the figure of more effective vibration signal
As analysis method.
In order to solve the above technical problems, the technical solution adopted by the present invention is：
A kind of image analysis method of vibration signal, including establish filter stage and detection-phase；
The filter stage of establishing includes establishing line filter and establishes column filter,
Establish line filter：The vibration signal of horizontal direction is subjected to experience wavelet transformation, empirical modal is obtained, by experience
Mode carries out Fourier transformation, obtains the spectral magnitude of every row, carries out border detection to the spectral magnitude of every row, establishes corresponding
Row bandpass filter；
Establish column filter：The vibration signal of vertical direction is subjected to experience wavelet transformation, empirical modal is obtained, by experience
Mode carries out Fourier transformation, obtains the spectral magnitude of each column, carries out border detection to the spectral magnitude of each column, establishes corresponding
Row bandpass filter；
Detection-phase includes：Vibration signal is first passed through into row bandpass filter to be filtered, and row image is exported along row,
It is filtered again by row bandpass filter, and row image is exported along row, row image and row image is shown over the display,
Obtain 2 dimension experience wavelet transformation figures of vibration signal.
Present invention has the advantages that：By obtaining 2 dimension experience wavelet transformation figures of vibration signal, image in Bo Liye by becoming
The difference 2 changed ties up AM-AM mode composition.Therefore, it can be easy to based on the different vibration signal characteristics of 2 dimension graphical analyses
Feature recognition and fault diagnosis.Make fault diagnosis more accurate, more comprehensive, more have reference value, establish a kind of new experience
Application of the small echo in fault diagnosis, a kind of image of 2 dimension vibration signal characteristics is presented, it is time saving and energy saving, intuitively view and shake
The change procedure of dynamic signal.
As a kind of preferred structure of the present invention, vibration level signal direction and vertical direction can not be confirmed in order to improve
Problem, described establish in filter stage use the tensor product empirically dimension experience wavelet transformation figures of small echo structure 2.It is in this way, logical
The method for crossing the tensor product using two vector spaces, analysis determine which direction of vibration signal is horizontal direction, which direction
For vertical direction, detect vibration signal for subsequent analysis and effective accurate foundation is provided.
As a kind of preferred structure of the present invention, the problem of effectively can not comprehensively detecting vibration signal to improve, institute
State vibration signal of the detection-phase using current vortex sensor detection level and vertical direction, and make respectively detection level with it is vertical
The vibration signal in direction first passes through row bandpass filter, then passes through row bandpass filter output image.In this way, pass through an electric whirlpool
The vibration signal in flow sensor detection level direction, a current vortex sensor detect vertical vibration signal, make detection more
Add comprehensively, static and dynamic relative displacement change between current vortex sensor energy accurate measurement measured body and probe tip face, from
And it is converted into vibration signal.
In order to solve the above technical problems, another technical scheme provided by the invention is：
A kind of image analysis method of vibration signal, including establish filter stage and detection-phase；
The filter stage of establishing includes establishing line filter and establishes column filter,
Establish line filter：The vibration signal of horizontal direction is subjected to experience wavelet transformation, empirical modal is obtained, by experience
Mode carries out Hilbert transform, obtains the spectral magnitude of every row, carries out border detection to the spectral magnitude of every row, establishes corresponding
Row bandpass filter；
Establish column filter：The vibration signal of vertical direction is subjected to experience wavelet transformation, empirical modal is obtained, by experience
Mode carries out Hilbert transform, obtains the spectral magnitude of each column, carries out border detection to the spectral magnitude of each column, establishes corresponding
Row bandpass filter；
Detection-phase includes：Vibration signal is first passed through into row bandpass filter to be filtered, and row image is exported along row,
It is filtered again by row bandpass filter, and row image is exported along row, row image and row image is shown over the display,
Obtain 2 dimension experience wavelet transformation figures of vibration signal.
Present invention has the advantages that：By obtaining 2 dimension experience wavelet transformation figures of vibration signal, image in Bo Liye by becoming
The difference 2 changed ties up AM-AM mode composition.Therefore, it can be easy to based on the different vibration signal characteristics of 2 dimension graphical analyses
Feature recognition and fault diagnosis.Make fault diagnosis more accurate, more comprehensive, more have reference value, establish a kind of new experience
Application of the small echo in fault diagnosis, a kind of image of 2 dimension vibration signal characteristics is presented, it is time saving and energy saving, intuitively view and shake
The change procedure of dynamic signal.
As a kind of preferred structure of the present invention, vibration level signal direction and vertical direction can not be confirmed in order to improve
Problem, described establish in filter stage use the tensor product empirically dimension experience wavelet transformation figures of small echo structure 2.It is in this way, logical
The method for crossing the tensor product using two vector spaces, analysis determine which direction of vibration signal is horizontal direction, which direction
For vertical direction, detect vibration signal for subsequent analysis and effective accurate foundation is provided.
As a kind of preferred structure of the present invention, the problem of can not effectively obtaining spectral magnitude to improve, the foundation
The process of spectral magnitude is obtained in filter stage to be included：
After instantaneous vibration signal is carried out into experience wavelet transformation, instantaneous empirical modal is obtained, to instantaneous Empirical Mode
State carries out Hilbert transform, obtains instantaneous frequency and instantaneous amplitude, each empirical modal of a vibration period is wished
You convert Bert, obtain the spectral magnitude of a vibration period.In this way, by entering to each empirical modal of a vibration period
Row Hilbert transform, the time of vibration period can be obtained, so as to obtain the spectral magnitude of vibration period, be obtained for fault diagnosis
To effective accurate spectral magnitude.
As a kind of preferred structure of the present invention, the problem of effectively can not comprehensively detecting vibration signal to improve, institute
State vibration signal of the detection-phase using current vortex sensor detection level and vertical direction, and make respectively detection level with it is vertical
The vibration signal in direction first passes through row bandpass filter, then passes through row bandpass filter output image.In this way, pass through an electric whirlpool
The vibration signal in flow sensor detection level direction, a current vortex sensor detect vertical vibration signal, make detection more
Add comprehensively, static and dynamic relative displacement change between current vortex sensor energy accurate measurement measured body and probe tip face, from
And it is converted into vibration signal.
Embodiment
To describe the technology contents of the present invention, construction feature, the objects and the effects in detail, below in conjunction with embodiment
It is explained in detail.
Embodiment one
The image analysis method of vibration signal of the present invention, including establish filter stage and detection-phase；
The filter stage of establishing includes establishing line filter and establishes column filter,
Establish line filter：The vibration signal of horizontal direction is subjected to experience wavelet transformation, empirical modal is obtained, by experience
Mode carries out Fourier transformation, obtains the spectral magnitude of every row, carries out border detection to the spectral magnitude of every row, establishes corresponding
Row bandpass filter；
Wavelet transformation is a kind of new transform analysis method, using the teaching of the invention it is possible to provide " T/F " window with frequency shift
Mouthful, it is the ideal tools for carrying out signal time frequency analysis and processing.Being mainly characterized by for it being capable of abundant outstanding problem by conversion
The feature of some aspects, the localization of time (space) frequency can be analyzed, by flexible shift operations to signal (function) by
Step carries out multi-scale refinement, is finally reached high frequency treatment time subdivision, and frequency is segmented at low frequency, can adapt to time frequency signal analysis automatically
Requirement, so as to focus on any details of signal.Vibration signal is subjected to experience wavelet transformation, by vibration signal
Frequency spectrum is adaptively divided, and constructs suitable orthogonal wavelet filter group to extract the AM- with compact schemes Fourier spectrum
FM compositions, so as to carry out Fourier transformation to the AM-FM mode extracted, obtain spectral magnitude.
Fourier transformation represents that some function representation of certain condition can will be met into trigonometric function (sinusoidal and/or cosine
Function) or their integration linear combination.Fourier transformation is a kind of method of signal Analysis, it can signal Analysis into
Point, it is also possible to these composition composite signals.
Establish column filter：The vibration signal of vertical direction is subjected to experience wavelet transformation, empirical modal is obtained, by experience
Mode carries out Fourier transformation, obtains the spectral magnitude of each column, carries out border detection to the spectral magnitude of each column, establishes corresponding
Row bandpass filter；
Described establish in filter stage uses the tensor product empirically dimension experience wavelet transformation figures of small echo structure 2.In this way,
By using the method for the tensor product of two vector spaces, analysis determines which direction of vibration signal is horizontal direction, which side
To for vertical direction, detect vibration signal for subsequent analysis and effectively accurate foundation is provided.
Detection-phase includes：Vibration signal is first passed through into row bandpass filter to be filtered, and row image is exported along row,
It is filtered again by row bandpass filter, and row image is exported along row, row image and row image is shown over the display,
Obtain 2 dimension experience wavelet transformation figures of vibration signal.
The detection-phase makes detection respectively using current vortex sensor detection level and the vibration signal of vertical direction
The horizontal vibration signal with vertical direction first passes through row bandpass filter, then passes through row bandpass filter output image.Current vortex
Sensor can statically and dynamically non-contact, high linearity, measure high resolution metal conductor measured away from detecting head surface away from
From, by current vortex sensor and vibroseismic signal fixed setting, the distance of detection current vortex sensor and vibroseismic signal.Such as
This, by the vibration signal in a current vortex sensor detection level direction, a current vortex sensor detection vertical direction is shaken
Dynamic signal, makes detection more comprehensive, static and dynamic between current vortex sensor energy accurate measurement measured body and probe tip face
Relative displacement changes, so as to be converted into vibration signal.Current vortex sensor, the state of energy directly non-cpntact measurement rotating shaft, to all
The imbalance of such as rotor, misalign, bearing wear, axle crackle and occur friction mechanical problem Early judgement, it is possible to provide close
The information of key.
Embodiment two
A kind of image analysis method of vibration signal, including establish filter stage and detection-phase；
The filter stage of establishing includes establishing line filter and establishes column filter,
Establish line filter：The vibration signal of horizontal direction is subjected to experience wavelet transformation, empirical modal is obtained, by experience
Mode carries out Hilbert transform, obtains the spectral magnitude of every row, carries out border detection to the spectral magnitude of every row, establishes corresponding
Row bandpass filter；
Wavelet transformation is a kind of new transform analysis method, using the teaching of the invention it is possible to provide " T/F " window with frequency shift
Mouthful, it is the ideal tools for carrying out signal time frequency analysis and processing.Being mainly characterized by for it being capable of abundant outstanding problem by conversion
The feature of some aspects, the localization of time (space) frequency can be analyzed, by flexible shift operations to signal (function) by
Step carries out multi-scale refinement, is finally reached high frequency treatment time subdivision, and frequency is segmented at low frequency, can adapt to time frequency signal analysis automatically
Requirement, so as to focus on any details of signal.Vibration signal is subjected to experience wavelet transformation, by vibration signal
Frequency spectrum is adaptively divided, and constructs suitable orthogonal wavelet filter group to extract the AM- with compact schemes Fourier spectrum
FM compositions, so as to carry out Hilbert transform to the AM-FM mode extracted, obtain significant instantaneous frequency and instantaneous width
Value, and then obtain Hilbert spectrums.
Xi Er of the Hilbert transform (hilbert transform) to a continuous time signal x (t) of vibration signal
Bert conversion be equal to the signal by with impulse response h (t)=1/ the π t later output of linear system respond xh(t).Institute
With signal after Hilbert transform, keep constant in the amplitude of each frequency component of frequency domain, but phase will appear from 90 ° of phase shifts.I.e.
Frequency hysteresis pi/2 is aligned, to negative frequency leading pi/2, therefore Hilbert transformer is also known as 90 ° of phase shifters.Use Hilbert
Envelope, instantaneous frequency and the instantaneous phase of conversion description amplitude modulation(PAM) or phase-modulation can make analysis easy.
Establish column filter：The vibration signal of vertical direction is subjected to experience wavelet transformation, empirical modal is obtained, by experience
Mode carries out Hilbert transform, obtains the spectral magnitude of each column, carries out border detection to the spectral magnitude of each column, establishes corresponding
Row bandpass filter；
Described establish in filter stage uses the tensor product empirically dimension experience wavelet transformation figures of small echo structure 2.In this way,
By using the method for the tensor product of two vector spaces, analysis determines which direction of vibration signal is horizontal direction, which side
To for vertical direction, detect vibration signal for subsequent analysis and effectively accurate foundation is provided.
Described establish in filter stage obtains the process of spectral magnitude and included：
After instantaneous vibration signal is carried out into experience wavelet transformation, instantaneous empirical modal is obtained, to instantaneous Empirical Mode
State carries out Hilbert transform, obtains instantaneous frequency and instantaneous amplitude, each empirical modal of a vibration period is wished
You convert Bert, obtain the spectral magnitude of a vibration period.In this way, by entering to each empirical modal of a vibration period
Row Hilbert transform, the time of vibration period can be obtained, so as to obtain the spectral magnitude of vibration period, be obtained for fault diagnosis
To effective accurate spectral magnitude.
Detection-phase includes：Vibration signal is first passed through into row bandpass filter to be filtered, and row image is exported along row,
It is filtered again by row bandpass filter, and row image is exported along row, row image and row image is shown over the display,
Obtain 2 dimension experience wavelet transformation figures of vibration signal.
The detection-phase makes detection respectively using current vortex sensor detection level and the vibration signal of vertical direction
The horizontal vibration signal with vertical direction first passes through row bandpass filter, then passes through row bandpass filter output image.Current vortex
Sensor can statically and dynamically non-contact, high linearity, measure high resolution metal conductor measured away from detecting head surface away from
From, by current vortex sensor and vibroseismic signal fixed setting, the distance of detection current vortex sensor and vibroseismic signal.Such as
This, by the vibration signal in a current vortex sensor detection level direction, a current vortex sensor detection vertical direction is shaken
Dynamic signal, makes detection more comprehensive, static and dynamic between current vortex sensor energy accurate measurement measured body and probe tip face
Relative displacement changes, so as to be converted into vibration signal.Current vortex sensor, the state of energy directly non-cpntact measurement rotating shaft, to all
The imbalance of such as rotor, misalign, bearing wear, axle crackle and occur friction mechanical problem Early judgement, it is possible to provide close
The information of key.
Fault vibration signal intuitively can be detected and analyze by present embodiment.
Embodiments of the invention are the foregoing is only, are not intended to limit the scope of the invention, it is every to utilize this hair
The equivalent structure or equivalent flow conversion that bright description is made, or directly or indirectly it is used in other related technology necks
Domain, it is included within the scope of the present invention.
Claims (7)
1. a kind of image analysis method of vibration signal, including establish filter stage and detection-phase；It is characterized in that：
The filter stage of establishing includes establishing line filter and establishes column filter,
Establish line filter：The vibration signal of horizontal direction is subjected to experience wavelet transformation, empirical modal is obtained, by empirical modal
Fourier transformation is carried out, obtains the spectral magnitude of every row, border detection is carried out to the spectral magnitude of every row, establishes corresponding row band
Bandpass filter；
Establish column filter：The vibration signal of vertical direction is subjected to experience wavelet transformation, empirical modal is obtained, by empirical modal
Fourier transformation is carried out, obtains the spectral magnitude of each column, border detection is carried out to the spectral magnitude of each column, establishes corresponding row band
Bandpass filter；
Detection-phase includes：Vibration signal is first passed through into row bandpass filter to be filtered, and row image is exported along row, then is led to
Cross row bandpass filter to be filtered, and row image is exported along row, row image and row image are shown over the display, obtained
2 dimension experience wavelet transformation figures of vibration signal.
2. the image analysis method of vibration signal according to claim 1, it is characterised in that：It is described to establish filter stage
It is middle that using tensor product, empirically small echo structure 2 ties up experience wavelet transformation figure.
3. the image analysis method of vibration signal according to claim 1, it is characterised in that：The detection-phase is using electricity
The vibration signal of eddy current sensor detection level and vertical direction, and make detection level and the vibration signal of vertical direction first respectively
By row bandpass filter, then pass through row bandpass filter output image.
4. a kind of image analysis method of vibration signal, including establish filter stage and detection-phase；It is characterized in that：
The filter stage of establishing includes establishing line filter and establishes column filter,
Establish line filter：The vibration signal of horizontal direction is subjected to experience wavelet transformation, empirical modal is obtained, by empirical modal
Hilbert transform is carried out, obtains the spectral magnitude of every row, border detection is carried out to the spectral magnitude of every row, establishes corresponding row
Bandpass filter；
Establish column filter：The vibration signal of vertical direction is subjected to experience wavelet transformation, empirical modal is obtained, by empirical modal
Hilbert transform is carried out, obtains the spectral magnitude of each column, border detection is carried out to the spectral magnitude of each column, establishes corresponding row
Bandpass filter；
Detection-phase includes：Vibration signal is first passed through into row bandpass filter to be filtered, and row image is exported along row, then is led to
Cross row bandpass filter to be filtered, and row image is exported along row, row image and row image are shown over the display, obtained
2 dimension experience wavelet transformation figures of vibration signal.
5. the image analysis method of vibration signal according to claim 4, it is characterised in that：It is described to establish filter stage
It is middle that using tensor product, empirically small echo structure 2 ties up experience wavelet transformation figure.
6. the image analysis method of vibration signal according to claim 4, it is characterised in that：It is described to establish filter stage
In obtain the process of spectral magnitude and include：
After instantaneous vibration signal is carried out into experience wavelet transformation, instantaneous empirical modal is obtained, instantaneous empirical modal is entered
Row Hilbert transform, obtains instantaneous frequency and instantaneous amplitude, and each empirical modal of a vibration period is carried out into Martin Hilb
Spy's conversion, obtains the spectral magnitude of a vibration period.
7. the image analysis method of vibration signal according to claim 4, it is characterised in that：The detection-phase is using electricity
The vibration signal of eddy current sensor detection level and vertical direction, and make detection level and the vibration signal of vertical direction first respectively
By row bandpass filter, then pass through row bandpass filter output image.
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| DE102017124135B4 (en) * | 2016-10-21 | 2023-06-07 | Computational Systems Inc. | Machine failure prediction based on an analysis of periodic information in a signal |
| CN106874833B (en) * | 2016-12-26 | 2021-05-28 | 中国船舶重工集团公司第七一0研究所 | Vibration event pattern recognition method |
| CN109981869B (en) * | 2017-12-27 | 2020-10-02 | 宁波舜宇光电信息有限公司 | Method and test equipment for measuring oscillation period of lens actuator based on image technology |
| CN108181617B (en) * | 2017-12-29 | 2020-06-12 | 北京理工大学 | Filtering method of non-linear frequency modulation system based on tensor product model transformation |
| CN109668622A (en) * | 2018-11-16 | 2019-04-23 | 国网江苏省电力有限公司盐城供电分公司 | It is a kind of that signal frequency calculation method is reflected ultrasonic wave based on vibration measurement |
| CN109614952B (en) * | 2018-12-27 | 2020-08-25 | 成都数之联科技有限公司 | Target signal detection and identification method based on waterfall plot |
| CN110595602B (en) * | 2019-04-26 | 2021-10-15 | 深圳市豪视智能科技有限公司 | Vibration detection method and related product |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6161076A (en) * | 1997-11-14 | 2000-12-12 | Baker Hughes Incorporated | Seismic data acquisition and processing using non-linear distortion in a vibratory output signal |
| JP2001099757A (en) * | 1999-09-29 | 2001-04-13 | Takasago Thermal Eng Co Ltd | Method for detecting bearing malfunction |
| CN101221066A (en) * | 2008-01-25 | 2008-07-16 | 太原理工大学 | Engineering nonlinear vibration detecting method |
| JP2012215412A (en) * | 2011-03-31 | 2012-11-08 | Jtekt Corp | Method and apparatus for performing vibration analysis and vibration source identification of in-vehicle unit |
| CN104819766A (en) * | 2015-05-13 | 2015-08-05 | 西安交通大学 | Envelope demodulation frequency band determination method based on harmonic-to-noise ratio |
| CN105115592A (en) * | 2015-09-02 | 2015-12-02 | 深圳奥博瑞脑健科技有限公司 | Cranial cavity vibration detection method and device |
-
2016
- 2016-02-19 CN CN201610093698.5A patent/CN105738061B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6161076A (en) * | 1997-11-14 | 2000-12-12 | Baker Hughes Incorporated | Seismic data acquisition and processing using non-linear distortion in a vibratory output signal |
| JP2001099757A (en) * | 1999-09-29 | 2001-04-13 | Takasago Thermal Eng Co Ltd | Method for detecting bearing malfunction |
| CN101221066A (en) * | 2008-01-25 | 2008-07-16 | 太原理工大学 | Engineering nonlinear vibration detecting method |
| JP2012215412A (en) * | 2011-03-31 | 2012-11-08 | Jtekt Corp | Method and apparatus for performing vibration analysis and vibration source identification of in-vehicle unit |
| CN104819766A (en) * | 2015-05-13 | 2015-08-05 | 西安交通大学 | Envelope demodulation frequency band determination method based on harmonic-to-noise ratio |
| CN105115592A (en) * | 2015-09-02 | 2015-12-02 | 深圳奥博瑞脑健科技有限公司 | Cranial cavity vibration detection method and device |
Non-Patent Citations (2)
| Title |
|---|
| 基于小波分析的MSMA振动传感器信号处理与故障检测;鲁军 等;《电工技术学报》;20150531;第30卷(第10期);第354-360页 * |
| 自适应谱峭度滤波方法及其振动信号检测应用;蔡改改 等;《振动、测试与诊断》;20140430;第34卷(第2期);第212-217、392页 * |
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