Detecting small flaws in two-phase Ti-6Al-4V with rough surfaces
Xiongbing Li1, Yingdong Fu2, Feng Zhang3
1School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China; Joint International Research Laboratory of Key Technology for Rail Traffic Safety, Changsha 410075, China; National & Local Joint Engineering Research Center of Safety Technology for Rail Vehicle, Changsha 410075, China.
Abstract:
Surface roughness degrades the performance of ultrasonic methods when detecting sub-wavelength flaws. In this work, a roughness-modified doubly-scattered response (DSR) model is developed to enhance the flaw detection method for two-phase Ti-6Al-4V with rough surfaces. Extreme value statistics are used to calculate the confidence bounds of grain noise, then the bounds are treated as a time-dependent threshold for segmenting flaws in C-scan images of two-phase Ti-6Al-4V with rough surfaces. Three Ti-6Al-4V samples with different surface roughness are designed and manufactured for validating the present method; ultrasonic C-scan results show that it can distinguish sub-wavelength flaws (about 1/3 wavelength) in two-phase Ti-6Al-4V with rough surfaces, which can be extended to industry applications.
