噪声与振动控制2017，Vol.37Issue(5)：92-96,114,6.DOI:10.3969/j.issn.1006-1355.2017.05.020
基于EEMD-Fast ICA-STFT的车用起动电机噪声源识别
Noise Source Identification of Vehicle's Starting Motors Based on EEMD-Fast ICA-STFT Approach
摘要
Abstract
A noise source identification method based on the ensemble empirical mode decomposition (EEMD), fast independent component analysis (Fast ICA) and short time Fourier transform (STFT) algorithms is proposed to study the noise source identification of vehicle's starting motors. First of all, the EEMD algorithm is used to decompose the single channel noise of the starting motors into several intrinsic mode functions. Then, the Fast ICA algorithm is used to extract the independent components. Finally, using the better time-frequency characteristics of STFT algorithm, the time-frequency characteristics of the Fast ICA results are analyzed. Combining the results with the prior knowledge of the motor noise, the relationship between the independent components and the different noise sources of the motors is determined.关键词
声学/电机噪声源/经验模态分解/独立分量分析/短时傅里叶变换Key words
acoustics/noise source of motors/ensemble empirical mode decomposition (EEMD)/fast independent component analysis (Fast ICA)/short time Fourier transform (STFT)分类
信息技术与安全科学引用本文复制引用
龚承启,华春蓉..基于EEMD-Fast ICA-STFT的车用起动电机噪声源识别[J].噪声与振动控制,2017,37(5):92-96,114,6.基金项目
国家自然科学基金资助项目(51405399) （51405399）
