Cavitation Detection Using Wavelet Denoising

Abstract

Cavitation in turbomachinery provides a source of damage to the hydrodynamic surfaces. Detection of cavitation at the earliest possible time after inception is desirable from a damage prevention standpoint. In order to detect cavitation in real time, acoustic sensing of the cavitation events has long been an accepted practice. A problem with this measurement technique is the potential contamination from electrical and acoustic background noise sources. This work employs an algorithm based on wavelet denoising. The wavelet denoising algorithm depends on a measurement of the acoustic background noise in the absence of cavitation. Cavitation measurements of a stationary object are evaluated with and without the application of the denoising process. The results of this comparison indicate that the wavelet denoising procedure allows an increased number of cavitation events to be detected at a given static pressure, and cavitation is detected at higher pressures than previous techniques.