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Separation of Noise and Signals by Independent Component Analysis

Authors:
Sigeru Omatu
Masao Fujimura
Toshihisa Kosaka

Keywords: signal separation, independent component analysis, neural networks

Abstract:
A separation problem of acoustic signals and noise by using the independent component analysis (ICA) with band-pass filters is proposed. The frequency distribution of a recorded acoustic signal of the operating mechanical device can be divided into three fields, the low-frequency field, which corresponds to the frequency characteristics of the gear, the medium-frequency field, which is mixed with the frequency characteristics of the gear and the motor, and the high-frequency field, which corresponds to the frequency characteristics of the motor. Since only the medium-frequency components are the mixture of acoustic signals of gears and motors, the ICA with band-pass filters is expected to separate the acoustic signals of motors and gears more accurately than the conventional ICA. The simulation and experimental results show that the proposed method can separate the acoustic signals of motors and gears of mechanical devices successfully.

Pages: 105 to 110

Copyright: Copyright (c) IARIA, 2010

Publication date: October 25, 2010

Published in: conference

ISSN: 2308-4499

ISBN: 978-1-61208-101-4

Location: Florence, Italy

Dates: from October 25, 2010 to October 30, 2010