Abstract
In order to improve the performance of the denoising method for vibration signals of rotating machinery, a new method of signal denoising based on the improved median filter and wavelet packet technology is proposed through analysing the characteristics of noise components and relevant denoising methods. Firstly, the window width of the median filter is calculated according to the sampling frequency so that the impulse noise and part of the white noise can be effectively filtered out. Secondly, an improved self-adaptive wavelet packet denoising technique is used to remove the residual white noise. Finally, useful vibration signals are obtained after the previous processing. Simulation signals and rotor experimental vibration signals were used to verify the performance of the method. Experiment results show that the method can not only effectively eliminate the mixed complex noises but also preserve the fault character details, which demonstrates that the proposed method outperforms the method based on the wavelet-domain median filter.
Highlights
It is the most direct and effective method in the fault diagnosis of rotating machinery to analyze the vibration signal and obtain the characteristic information of the running state of machinery [1, 2]
In the field measurement, due to the influence of electromagnetic interference and random noise of other equipment such as the motor and the data acquisition system, the final collected vibration signals are often polluted by different degrees of complex noise, and the useful signals carrying the characteristic information of mechanical operation state are submerged in the background noise. erefore, how to separate the real mechanical vibration signal from the mixed signal is the primary task of fault diagnosis research
Because the pulse noise has the characteristics of large amplitude, short duration, and long time interval, the application of the median filter can effectively eliminate the pulse interference; while the spectrum width of the white noise is far greater than the bandwidth of the vibration signal of the rotor system, the use of wavelet denoising technology can filter out most of the Gaussian white noise. erefore, a better denoising effect can be achieved by combining the median filter with wavelet denoising and setting it reasonably
Summary
It is the most direct and effective method in the fault diagnosis of rotating machinery to analyze the vibration signal and obtain the characteristic information of the running state of machinery [1, 2]. E method combines the median filter with window adaptive adjustment and wavelet packet denoising technology with adaptive adjustment of decomposition scale and threshold to filter out the impulse noise and white noise in the signal. Erefore, as long as the appropriate window width is set, the median filter can effectively reduce the impulse noise in the vibration signal, but because of the characteristics of the filtering method itself, it cannot filter out the white noise. E algorithm determines the threshold value and threshold processing function according to the distribution of wavelet coefficients of the signal and noise on each decomposition scale. E above theory is the core content of the wavelet packet threshold denoising method, so improving formulas (4)–(6) to remove noise and retain useful signals is an important way to improve the denoising performance of this method, and it is the research work to be carried out
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