Independent component analysis of excavator noise

Authors:
Guohao Zhang;Qiangen Chen
Affiliations:
National Key Laboratory of High performance and Complex Manufacturing, China,Department of Mechanical and Electrical Engineering, Central South University, Changsha, China;National Key Laboratory of High performance and Complex Manufacturing, China,Department of Mechanical and Electrical Engineering, Central South University, Changsha, China
Venue:
ICIC'12 Proceedings of the 8th international conference on Intelligent Computing Theories and Applications
Year:
2012

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Abstract

To identify excavator noise sources, an acoustic camera was used to acquire sound signals, and FastICA was applied to separate the signals. For strong background noise and echoic interference, the noise separation model was built based on FastICA algorithm in frequency-domain, then principle frequencies were obtained. To find the corresponding parts of these frequencies, modal analysis of major surface parts of the diesel was run in Ansys, and the modal analysis results were compared with principle frequencies. Research shows that ICA can effectively separate excavator sound signals contaminated by strong background noise and echoic interference; and the surface noise radiation sources such as cylinder block, cylinder head and valve cover were found by comparing component principle frequencies and modal analysis results.