Identification of Cavitation by Noise

Abstract

The identification of cavitation is very important in technical practice for operational and especially economic reasons. The article deals with the use of another way to measure noise during cavitation. The current approach of measuring noise with an intensity probe is used in practice for identification, but it does not immediately address the position of the cavitation source for a given frequency range. Measurement by an acoustic camera is not entirely common in practice, but it allows to determine the location of the noise source for a given frequency range. To test the acoustic camera, the authors focused on the cavitating flow in a hydraulic circuit with three previously tested nozzles. Noise was measured for these nozzles using an acoustic intensity probe with two microphones. The results were evaluated by statistical methods and compared with measurements using an acoustic camera. The aim of the article is to point out the advantages of using this approach for accurate area identification of the problem. Research background: The work is focused on the issue of cavitation and its identification in the hydraulic circuit. For cavitation research, a variant of cavitation identification by noise was chosen. However, this measurement brings problems that are only revealed through more sophisticated and accurate measurements. Purpose of the article: The purpose of the article is to point out other possibilities of measuring cavitation noise using modern technologies and subsequently verify the results. Methods: Metody: A common way of measuring noise is to measure it with a suitably located acoustic intensity probe. A more modern approach is area noise measurement. Measurement methodology and benefits are described. Findings & Value added: The commonly used way of measuring noise using an acoustic intensity probe has proved to be insufficient, as it is not possible to distinguish the location of sources in the case of complex measurements. When using an acoustic camera, there are more sources of noise in a given circuit and they are detected according to the required frequencies in different places than expected. The article points out the specific identification of noise sources using the frequency spectrum of noise for selected elements.