A double filtering algorithm based on wavelet and application in de-noising of gearbox fault signal
Yanhui Dong, Shuhong Chen, Wenli Shang · 2008
In this paper, a double filtering algorithm is proposed for de-noising of gearbox malfunction vibration signal, which is produced by combining adaptive wavelet transform de-noising and wavelet threshold de-noising. The de-noising process of this algorithm consist of two phases, in first phase, a optimal wavelet is obtained by making its scale factor a optimized, the optimal a is obtained while the kurtosis of the wavelet transformed signal reaches maximum, and then, the malfunction signal is filtered by wavelet transform with the optimal wavelet. In this way, impactive component of the signal will be reserved farthest. In the second phase, the classical wavelet threshold de-noising algorithm is used to de-noise secondly. Because the wavelet threshold de-noising method is approximately optimal in minimum mean square error, so it can effectively lower the overall noise of the signal. Finally, a experiment is carried out. The algorithm is used to de-noise for a transmission gearbox vibration signal. The transmission have one gear broken, the vibration signal contains strong noise. Experiment results show that the algorithm is effective for de-noising of transmission gearbox failure vibration signal.