Author(s): Z L Liu; Y Zhao; Q B Guo

Linked Author(s):

Keywords: Cavitation inception; Francis turbine; Acoustic detection; Auto-test method

Abstract: The vibration and noise of large Francis-turbine units tends to increase, the efficiency decreases and the units operate unstably if the units operate under the cavitation condition. Hence it must be eradicated completely that the units run under the cavitation condition. Nowadays, the judgment of inception cavitation of model Francis-turbine runner blades remains stagnant at the stage of artificial observation so that the results lacks of objectivity and consistency. An auto-test method based on acoustics theory and the principle of cavitation is presented. When cavitation happens, the acoustic energy radiated by bubbles while collapsing is different at different stages of cavitation, for the size and number of bubbles are different. And therefore the distribution of cavitation noise energy in the frequency domain varies along with the severe degree of cavitation, according to which the inception cavitation can be determined exactly by acquiring the acoustics signals in the water with hydrophone mounted on the draft tube cone and then abstracting and analyzing the characteristics parameters of cavitation noise in the frequency domain when the model Francis-turbine operates. The rationality and accuracy have been proved by model tests, and it is significant to determine the inception cavitation of model Francis-turbine runner blades by automatic way instead of artificial way.

DOI: https://doi.org/10.1088/1755-1315/163/1/012061

Year: 2017