Pearson Correlation and Discrete Wavelet Transform for Crack Identification in Steel Beams

Discrete wavelet transform is a useful means for crack identification of beam structures. However, its accuracy severely dependent on the selecting mother and vanishing moments, which raises significant challenge in practical structural identification. In this paper, novel approach introduced health monitoring beams to fix challenge. The based combination statistical characteristics vibrational mode shapes structures their discrete transforms. First, paper suggests using regression statistics between intact damaged modes monitor Then, it extracting quasi-Pearson-based shape index use them as an original signal Findings show that proposed has several advantages compared with conventional processing by transforms significantly improves damage detection’s accuracy.