Rub-impact fault diagnosis method based on wavelet and harmonic component greedy sparse recognition
A technology for harmonic components and fault diagnosis, applied in the testing of mechanical components, testing of machine/structural components, instruments, etc., it can solve the problems that noise cannot be filtered out, affect the correct extraction of instantaneous amplitude and instantaneous frequency, etc., to achieve accurate Effects of translation invariance, avoiding mode breakage, good practicability and engineering application promotion value
Active Publication Date: 2019-08-20
XIAMEN UNIV +1
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[0004] Although the current time-frequency analysis method can adaptively select the filter passband according to the characteristics of the rubbing signal, thereby suppressing the noise outside the passband, it still cannot filter out the noise within the passband, thus affecting the instantaneous amplitude and instantaneous frequency. The correct extraction of parameters such as
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[0052] The following embodiments will further illustrate the present invention in conjunction with the accompanying drawings.
[0053] Embodiments of the present invention include the following steps:
[0054] 1. Use eddy current sensors to measure the shaft of the mechanical equipment power transmission system in a non-contact manner, and obtain the vibration displacement signal x of the shaft. The signal {x(n)} is obtained after introducing anti-aliasing filtering and anti-mean processing conditioning links in the acquisition, its length is L, and the sampling frequency is f s ,Such as figure 1 and figure 2 shown, and has
[0055] x={x(n)|n=1,2,...,N}.
[0056] 2. Use the redundant second-generation wavelet packet transform to decompose the vibration displacement signal in multiple scales and perform single-branch reconstruction, search the time-domain signals of subspaces on each scale, and select the harmonic component shw with significant amplitude modulation charact...
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The invention discloses a rub-impact fault diagnosis method based on wavelet and harmonic component greedy sparse recognition, and relates to a mechanical fault diagnosis method. Firstly, redundant second-generation wavelet packet transformation is adopted to carry out multi-scale decomposition on a signal; an amplitude signal is enhanced from the subspace signals of each scale; Hanning window Fourier transform is performed on the selected subspace, and the signal is divided into a plurality of harmonic components according to an energy concentration principle; a greedy sparse recognition algorithm of harmonic parameters is adopted to carry out iterative accurate recognition on amplitude, frequency and phase parameters; a noise reduction signal of the subspace is constructed through the harmonic parameters; through Hilbert envelope demodulation, the instantaneous amplitude and instantaneous frequency information of the subspace can be accurately obtained so as to diagnose the rub-impact fault of the rotor system. And the method has accurate translation invariance and linear phase characteristics. The mode rupture phenomenon in the decomposition process can be avoided, the parameteridentification precision is continuously improved through the iteration method, and the rub-impact fault of the rotor system is diagnosed through periodic abrupt change of the instantaneous amplitudeand the instantaneous frequency.
Description
technical field [0001] The invention relates to a mechanical fault diagnosis method, in particular to a rubbing fault diagnosis method based on greedy and sparse recognition of wavelet and harmonic components, which reduces the noise of vibration displacement signals to improve the recognition accuracy of instantaneous parameters. Background technique [0002] Rubbing is a common type of failure in the rotor system, which often occurs between the rotor-stator of aero-engines and power machinery. The eddy current sensor can measure the vibration displacement signal of the rotating shaft in a non-contact manner, and is a reliable carrier of the rubbing signal. The fault features produced by early rubbing faults are weak and difficult to be directly identified from the original signal, and advanced signal processing methods are needed to extract them. [0003] The time-frequency analysis method is a common tool for vibration displacement signal analysis. Gong Xiaoyun et al. (...
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IPC IPC(8): G06F17/50G01M13/00
CPCG01M13/00G06F30/17G06F30/20
Inventor 陈彬强李阳姚斌蔡志钦曹新城卢杰
Owner XIAMEN UNIV
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