Forecasting and Detection of Fatigue Cracks in Polycrystalline Alloys With Ultrasonic Testing Via Discrete Wavelet Transform

Abstract

Forecasting and detection of fatigue cracks play a key role in damage mitigation of mechanical structures (e.g., those made of polycrystalline alloys) to enhance their service life, and ultrasonic testing (UT) has emerged as a powerful tool for detection of fatigue cracks at early stages of damage evolution. Along this line, the work reported in this paper aims to improve the performance of fatigue crack forecasting and detection based on a synergistic combination of discrete wavelet transform (DWT) and Hilbert transform (HT) of UT data, collected from a computer-instrumented and computer-controlled fatigue-testing apparatus. Performance of the proposed method is evaluated by comparison with the images generated from a digital microscope, which are treated as the ground truth in this paper. The results of comparison reveal that forthcoming fatigue cracks can be detected ahead of their appearance on the surface of test specimens. The proposed method apparently outperforms both HT and conventional DWT, when they are applied individually, because the synergistic combination of DWT and HT provides a better characterization of UT signal attenuation for detection of fatigue crack damage.