Application of the Wavelet Transform for Defect Detection in Prestressing Strands by Guided Wave Technique

Prestressing strands are widely used in civil structures. The health monitoring of the strands is an important factor in evaluating the structural safety. This paper aims to improve the detection sensitivity of the guided wave technique in strands by wavelet processing. Groove defects with different depths are cut in the wire and detected by magnetostrictive sensors. The wavelet threshold method is employed to denoise the signals. In this study, the suitable thresholds are related to the median value of the coefficients. Results show that defects above 3.6% cross section loss can be found after this processing. Moreover, the amplitudes of the defect signals are related to the defect depths, which can be used to size the defects.