Oil Abrasive Signal Denoising Method Based On VMD and Wavelet Analysis
The oil metal abrasive particle detection sensor can feedback the fault characteristics of mechanical equipment in real time by monitoring the metal abrasive particles in the oil circuit of mechanical equipment.In order to improve the detection accuracy of oil wear particle detection sensor,a denoising method based on Variational Mode Decomposition(VMD)and wavelet analysis is proposed.Firstly,the optimal K value is determined by calculating the correlation coefficient between each modal component and the original oil wear particle signal.Secondly,the original signal is decomposed by VMD,and the characteristic components are screened out.Finally,the wavelet threshold denoising method is used to denoise the feature components.The experimental results show that,compared with Empirical Mode Decomposition(EMD)and traditional wavelet denoising methods,this method has the highest signal-to-noise ratio,the smallest root mean square error,and the largest energy proportion,and it is the best in the denoising effect of oil wear particle signals,which is conducive to improving the detection accuracy of wear particle detection sensors.
metal abrasive detectionVariational Mode Decomposition(VMD)wavelet analysisdenoising
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