Acoustic Signal Denoising Technology Investigation of Hydroelectric Generator Based on Wavelet Threshold
- Resource Type
- Conference
- Authors
- He, Wei; Song, Gangwei; Yuan, Pu; Nie, Lei; Guo, Chenliang
- Source
- 2023 3rd Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS) ACCTCS Communications Technology and Computer Science (ACCTCS), 2023 3rd Asia-Pacific Conference on. :583-587 Feb, 2023
- Subject
- Computing and Processing
Time-frequency analysis
Wavelet domain
Noise reduction
Interference
White noise
Wavelet analysis
Acoustic measurements
hydroelectric generator
sound signal
wavelet threshold
autocorrelation analysis
- Language
Aiming at the problem that hydroelectric generator sound signal detection is prone to external interference, this paper proposes a noise denoising method of hydroelectric generator sound signal based on wavelet threshold based on the analysis of time-frequency domain characteristics of hydroelectric generator sound signal, and uses autocorrelation analysis to extract acoustic signal characteristic frequency, and verifies the effectiveness of the algorithm through simulation tests. The algorithm is applied to the noise reduction analysis of the hydroelectric generator signal measured in the field. The results show that the wavelet threshold denoising method can effectively remove the Gaussian white noise signal in the hydroelectric generator sound signal and improve the signal-to-noise ratio of the hydroelectric generator sound signal. The autocorrelation analysis can further reduce the impact of noise and extract the key characteristic frequencies of sound signals of hydroelectric generators. The research results have reference significance for improving the sound measurement accuracy of hydroelectric generators under complex environmental interference conditions.