Combining whitening filter and wavelet transform to de-noise cavitation noise for cavitation state monitoring

Cavitation has become the main cause of damage to hydraulic machinery. Monitoring and detection of cavitation is necessary to avoid severe consequences. The sound, especially the audible sound-based method, is becoming attractive due to its simplicity and logicality. However, cavitation noise is easily contaminated by surrounding environmental noise, ie background noise, which is always coloured and cannot be eliminated easily by a wavelet transform (WT)-based method, although this has its merits and is very popular and effective. In this paper, in order to de-noise cavitation noise and eliminate coloured background noise efficiently, a de-noising strategy is proposed, which combines the whitening filter technique and the WT-based de-noising method. The main idea of the proposed de-noising strategy is that the whitening filter is constructed first with respect to the background noise, and then the constructed whitening filter is used to pre-process the cavitation noise so that the included background noise can be whitened before the WT-based method is used finally for the de-noising process. A simulation is designed to validate the effect of the proposed de-noising strategy. The experimental study is also presented to demonstrate its effect in de-noising cavitation noise for cavitation detection and state monitoring.