Cavitation Bubble Collapse Monitoring by Acoustic Emission in Laboratory Testing
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In order to investigate the potential of the acoustic emission technique in predicting cavitation erosion, laboratory tests were conducted in a high-speed cavitation tunnel. One face of a cylindrical stainless steel sample was subjected to an annular cavitation field created by the PREVERO cavitation tunnel. Acoustic emission was measured from the back surface of the sample in order to detect impacts caused by cavitation bubble or cloud collapses. Cavitation aggressiveness was varied by changing the operating parameters of the cavitation tunnel. Two different operating points were compared. Collapsing cavitation bubbles lead to impacts towards the sample surface and they induce elastic waves in the material. A resonance type acoustic emission sensor with a resonance frequency of 160 kHz captured these waves during the cavitation tests. The acoustic emission waveform was measured with a sampling frequency of 5 MHz. The sensor was mounted behind the sample using a wave-guide that maintained a transfer path for the elastic waves to travel from the impacted surface to the sensor. The elastic waves reaching the sensor were observed as distinguishable bursts in the acoustic emission waveform. Acoustic emission from cavitation impacts was estimated to be about 100 times stronger than acoustic emission from other sources, such as hydrodynamic events or machine vibration. This means that the signal was almost entirely induced by cavitation. The bursts contain multiple reflections that attenuate in time and that have a frequency content corresponding to the sensor frequency response. The bursts attenuate quickly enough not to overlap, as the cavitation events occur with a large enough temporal separation. The hypothesis in this study is that the maximum amplitude of the acoustic emission event voltage correlates with the strength of the cavitation bubble collapse impacting the surface. Voltage peak value counting was applied to the acoustic emission waveform data. As the bursts contain multiple amplitude peaks due to sensor resonance, an envelope function was fitted to the waveform for peak counting. Using this method, each counted voltage peak value is expected to correspond to a single cavitation impact event. The pulse distribution shows an exponential decrease with a decreasing voltage peak value rate as the peak voltage increases. This compares well with earlier studies, such as  and , where an exponential distribution of bubble collapse amplitudes was found. The results of this study prove acoustic emission as a direct and non-intrusive method that can be used to monitor cavitation impacts from outside of the cavitation field.