Title :
Engine Noise of Identification using an Improved Blind Sources Separation Algorithm
Author :
Yongman, Lin ; Tusheng, Lin
Author_Institution :
South China Univ. of Technol., Guangzhou
Abstract :
Engine noise of identification is a key technique on controlling engine noise. Traditionally, each of noises is separated to test. That is complicated, and experiment is needed many tested instruments. The paper proposes a novel approach to identify engine noise. The approach utilizes blind sources separation (BSS) to separated engine noise according to mixing noise of engine. Two experiment results indicate the effectiveness of this new algorithm that has low requirements for experiment environments and the amount of measure instruments. We approach an improved AC algorithm that is lesser time for separated mixing noise than the AC algorithm.
Keywords :
acoustic signal processing; blind source separation; engines; noise abatement; BSS; blind sources separation algorithm; engine mixing noise; engine noise control; engine noise identification; Acoustic noise; Acoustic testing; Combustion; Diesel engines; Instruments; Noise generators; Signal processing; Signal processing algorithms; Vehicles; Working environment noise;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.357