Title :
Denoising method for cracks of hydraulic turbine blades based on independent component analysis
Author :
Wang, Xiang-hong ; Shao, Yi-min ; Hu, Hong-wei ; Fu, Jun-qin
Author_Institution :
Sch. of Automobile & Mech. Eng., Changsha Univ. of Sci. & Technol., Changsha, China
Abstract :
Cracks of hydraulic turbine unit are very dangerous to the safety of power station. The crack signals are usually contaminated by strong background noise. Thus extraction of the crack signals is studied in the paper. Independent component analysis (ICA) technique is used to extract the crack signal mixed with white Gaussian noise and operating background noise of the hydraulic turbine unit. It concludes that the method can separate the wanted signal. The denoising result is hardly affected by input signal-to-noise ratios (SNRs) and frequency ranges of signals. Furthermore, the extracted signal has small nuances with the real signal in wave shape. As a result, ICA technique is a better method to extract weak signals.
Keywords :
Gaussian noise; blades; hydraulic turbines; independent component analysis; signal denoising; white noise; background noise; crack signals; denoising method; hydraulic turbine blades; independent component analysis; power station safety; white Gaussian noise; Hydraulic turbines; Independent component analysis; Noise measurement; Noise reduction; Signal to noise ratio; Time frequency analysis; Denoising; Hydraulic turbine; ICA; crack;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5582575