A novel bridge structure damage diagnosis algorithm based on statistical pattern recognition

Author

Haitao Xiao ; Cheng Lu ; Ogai, Harutoshi ; Roy, Kaushik

Author_Institution

Grad. Sch. of Inf., Production & Syst., Univ. of Waseda, Kitakyushu, Japan

fYear

2014

fDate

9-12 Sept. 2014

Firstpage

775

Lastpage

780

Abstract

This paper presents a structure damage detection algorithm based on statistical pattern recognition to analyze the acquired data to evaluate the health level of bridge. In this algorithm a novel statistical pattern recognition damage detection algorithm including a new damage sensitive index D_SPR is proposed to determine the severity and location of damages. This paper also presents simulation and experiment, including a detection experiment of making artificial damage to a real bridge, to show that our design choices are indeed quite effective.

Keywords

bridges (structures); condition monitoring; pattern recognition; statistical analysis; structural engineering computing; DSPR; bridge structure; damage diagnosis algorithm; damage sensitive index; health level; statistical pattern recognition; Algorithm design and analysis; Bridges; Data models; Equations; Feature extraction; Mathematical model; Sensors; Statistical pattern recognition; WSN (wireless sensor network); bridge diagnosis; system design;

fLanguage

English

Publisher

ieee

Conference_Titel

SICE Annual Conference (SICE), 2014 Proceedings of the

Conference_Location

Sapporo

Type

conf

DOI

10.1109/SICE.2014.6935224

Filename

6935224