Active sensing network system for crack detection on welded zone of steel truss member

In this paper, a sensor network system based on an active sensing scheme is introduced to identify cracks which may occur at a welded zone of a steel truss member. The active sensing network system offers special potential for real world applications, as it is light, cheap, and useful as a built-in system. Four pairs of pitch-catch Lamb wave signals are utilized from the active sensing network system. In order to extract damage sensitive features from the dispersive Lamb waves, a robust wavelet transform is applied to the original response signals. Peak values in the wavelet coefficients corresponding to the A ₀ Lamb mode are only considered for application to the damage index. The root-mean-square change of the peak values due to damage is proposed as a damage index. In addition, a least-square curve-fitting algorithm is applied to the damage indices in order to obtain a practical damage indicator with a threshold value that presents the damage tolerance. Finally, damage localization is carried out by investigating the change rates of the damage index according to each damage step. The applicability of the proposed methods has been demonstrated by an experimental study.