Indian Journal of Science and Technology

Abstract

Background/Objectives: Grain structure of Austenitic Stainless Steel (ASS) weld causes difficulty in defect detection while inspecting using Time of Flight Diffraction (TOFD) method. This study aims at comparing segmentation methods to overcome this difficulty based on defect characterization. Methods/Statistical Analysis: This study makes use of TOFD and Radiographic images of ASS weld pads fabricated with defined linear and volumetric defects. The Region-Based Level Set algorithm and Discontinuity Based Segmentation algorithm were explored for achieving flaw segmentation and quantitative characterization and validation of the result with that of standard radiographic results. Findings: The efficiency of the algorithms was analyzed by comparing and validating the size of defect with that of standard radiographic results in the form of error percentage. The consistency of error percentage in defect sizing (up to 11%) achieved by RegionBased Level Set algorithm for all the test images given in the database indicate that, this algorithm is the best as compared to Discontinuity Based Segmentation algorithm(error percentage up to 47%) for defect segmentation and characterization in TOFD images. Application/Improvements: The segmentation algorithm enables automation of measurement process and enhanced detection and characterization of defects at the initial stage. Further, it reduces human fatigue caused by operator while defect detection as the volume of data increases. The future direction is to fully automate the system in order to save time for interpretation and to modify the algorithm to segment images with multiple defects. Keywords: Defect Characterization, Discontinuity Based Segmentation, Flaw Segmentation, Region-Based Level Set Segmentation, Time of Flight Diffraction (TOFD), Weld Defect