Fault diagnosis method of hydro-generating unit based on voiceprint image

Abstract This paper focuses on the fault diagnosis of hydro generator sets and proposes a fault diagnosis method based on acoustic patterns. Through the acquisition, analysis, and feature extraction of the acoustic signals generated during the operation of the hydro-generator set, a fault diagnosis model is constructed by combining machine learning algorithms. The experimental results show that the method can effectively identify different types of faults and provide a reliable guarantee for the stable operation of the hydro-generator set.