Defect identification by sensor network under uncertainties

Tomonari Furukawa, Jinquan Cheng, Shen Hin Lim, Fei Xu, Ryuji Shioya

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

This paper presents a theoretical framework for identification of defects by a sensor network under uncertainties. While location of sensors are not known due to their inspection due to limited knowledge on the structure to be inspected, existing inspection methods do not take uncertainties of sensor locations into account for the localization of defects. The proposed theoretical framework formulates the uncertainties of sensor states stemming from both motion and measurement and allows stochastic identification of defects using recursive Beyesian estimation. Multi-sensor belief fusion further allows a network of sensors to jointly identify defects and improve the accuracy of identification. Parametric studies and application to practical defect identification have shown the validity of the proposed framework.

Original languageEnglish
Title of host publicationProceedings - 2010 International Conference on Broadband, Wireless Computing Communication and Applications, BWCCA 2010
Pages155-158
Number of pages4
DOIs
StatePublished - 2010
Event5th International Conference on Broadband Wireless Computing, Communication and Applications, BWCCA 2010 - Fukuoka, Japan
Duration: 4 Nov 20106 Nov 2010

Publication series

NameProceedings - 2010 International Conference on Broadband, Wireless Computing Communication and Applications, BWCCA 2010

Conference

Conference5th International Conference on Broadband Wireless Computing, Communication and Applications, BWCCA 2010
Country/TerritoryJapan
CityFukuoka
Period4/11/106/11/10

Keywords

  • Defect identification
  • Recursive Bayesian estimation
  • Sensor network
  • Sensor uncertainties

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