Bridge diagnosis system by using nonlinear independent component analysis

Juanqing Zheng, Qingwen Wang, Harutoshi Ogai, Chen Shao, Jingqiu Huang

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

The aim of this paper is to structure a daily diagnosis system for bridge monitoring and maintenance. Technology of wireless sensor, signal processing and structure analysis are used in this diagnosis system. The vibration data are collected through wireless sensor network by exerting some external forces such as running vehicles. Then use nonlinear independent component analysis (nonlinear ICA) and spectral analysis to analyze the data for extracting character frequency. In the past, linear ICA such as FastICA is used to do the signal processing step. But simple linear ICA algorithms work efficiently only in linear mixing environments. Whereas a nonlinear ICA model, which is more complicated, would be more practical for bridge diagnosis system. In this paper, we firstly use post nonlinear (PNL) method to change the data from nonlinear to linear, after that do linear separation by FastICA. Through the processed data this diagnosis technology can be used to understand the phenomena like corrosion and crack and evaluate the health condition of a bridge. We apply this system to do experiments at Nakajima Bridge in Yahata, Kitakyushu, Japan and successfully extract the character frequency of a bridge.

本文言語English
ホスト出版物のタイトルProceedings of SICE Annual Conference 2010, SICE 2010 - Final Program and Papers
出版社Society of Instrument and Control Engineers (SICE)
ページ2118-2121
ページ数4
ISBN(印刷版)9784907764364
出版ステータスPublished - 2010 1 1

出版物シリーズ

名前Proceedings of the SICE Annual Conference

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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