Vibration analysis of a submarine model based on an improved ICA approach

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Abstract

Vibration and noise reduction and control have obvious significance for submarines. A novel vibration analysis method based on an improved ICA algorithm is proposed in this paper. By using the clustering evaluation method, the stability and separating performance of the algorithm are significantly enhanced. The improved ICA algorithm is applied to feature extraction of the vibration signals and quantitative calculation of the source contributions of a scaled submarine model. The result shows that the proposed method is effective, and this research provides a primary basis for the vibration and noise control of submarines.

Original languageEnglish
Title of host publicationAdvances in Neural Network Research and Applications
Pages721-728
Number of pages8
DOIs
StatePublished - 2010
Event7th International Symposium on Neural Networks, ISNN 2010 - Shanghai, China
Duration: 6 Jun 20109 Jun 2010

Publication series

NameLecture Notes in Electrical Engineering
Volume67 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference7th International Symposium on Neural Networks, ISNN 2010
Country/TerritoryChina
CityShanghai
Period6/06/109/06/10

Keywords

  • Clustering evaluation
  • Feature extraction
  • Independent component analysis
  • Quantitative calculation
  • Source contributions

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