Abstract

A new structural damage estimation procedure using grey relation coefficient and curvature of displacement influence line in beams using sparse measurement is proposed in this paper. The method is based on static structural response which can be obtained using single sensor. Determination of damage location as well as determination of corre­sponding damage severity can be easily calculated with simple arithmetic operations, which is the main advantage of the proposed method. Conducted numerical simulation for different damage scenarios and various measurement sparseness and experimental validation confirm the effectiveness of proposed damage severity estimation procedure.

Highlights

  • Monitoring of structures is essential to prevent the accumulation of damage which may result in structural failure

  • A new structural damage estimation procedure using grey relation coefficient and curvature of displacement influence line in beams using sparse measurement is proposed in this paper

  • Determination of damage location as well as determination of corresponding damage severity can be calculated with simple arithmetic operations, which is the main advantage of the proposed method

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Summary

Introduction

Monitoring of structures is essential to prevent the accumulation of damage which may result in structural failure. The global techniques are, firstly, developed to detect the presence of damage and estimate damage location (Cornwell et al 1999; Li et al 2002; Choi et al 2004; Garstecki et al 2004; Štimac Grandić et al 2009; Abdo 2012). Many global NDDT are able to estimate severity of damage at damage location (Chen, Bicanic 2000; Nicholson, Alnefaie 2000; Kim et al 2006; Štimac Grandić, Grandić 2010; Wang 2013; Fayyadha, Razaka 2013). The usability of static NDDT using influence line approach in damage localization has been presented by several researchers (Choi et al 2004; Stöhr et al 2006; Štimac Grandić et al 2011; Wang et al 2011) but none of them try to evaluate severity of damage.

Theoretical formulation
Damage severity estimation algorithm
Numerical simulations
Experimental test
Findings
Discussion
Conclusions
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