Damage Detection Technique for Cold-Formed Steel Beam Structure Based on NSGA-II

Abstract

Cold-formed steel is uniform in quality, suitable for mass production, and light in weight. It is widely used for both structural and nonstructural members in buildings. When it is used in a bending structural member, damage such as local buckling is considered to be more important than general steel members in terms of failure mode. However, preceding studies on damage detection did not consider the failure characteristics of cold-formed beam members. Hence, this paper proposes a damage detection technique that considers the failure mode of local buckling for a cold-formed beam member. The differences between the dynamic characteristics from vibration-based measurements and those from finite element model are set to error functions. The error functions are minimized by the optimization technique NSGA-II. In the damage detection, the location of local damage and the severity of damage are considered variables. The proposed technique was validated through a simulation of damage detection for a cold-formed steel beam structure example.

Fatigue crack detection method using analysis of vibration signal

“…The problem of identifying structural damage on the basis of vibrations was raised by numerous authors (BRODA et al 2014a, OH et al 2015, JASSIM et al 2013, TAO et al 2014, TROCHIDIS et al 2014, TROJNIAR et al 2014, XU 2014, ZHOU 2006. Object vibration parameters are defined in this approach, and structural damage identification is the function of change in object structural properties, such as rigidity and mass.…”