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Theresa Cenate, C. F.
- Segmentation of Anomaly in Time of Flight Diffraction Images of Austentic Stainless Steel Weld
Abstract Views :165 |
PDF Views:2
Authors
Affiliations
1 Sathyabama University, Chennai-600 119, IN
2 Indira Gandhi Centre for Atomic Research, Kalpakkam–603 102, IN
1 Sathyabama University, Chennai-600 119, IN
2 Indira Gandhi Centre for Atomic Research, Kalpakkam–603 102, IN
Source
Digital Image Processing, Vol 7, No 7 (2015), Pagination: 222-224Abstract
Time of Flight Diffraction (TOFD) is an advanced Ultrasonic Technique for examination of weld specimen in process industries. Ultrasonic experts are required for defect detection which means increase in resource is needed increased resource. Hence an algorithm has to be developed to automate the defect segmentation. This research work develops an algorithm involving the stages of preprocessing, global thresholding and segmentation procedure of image processing. The proposed algorithm was tested on the TOFD image acquired in the laboratory condition. According to the result obtained the algorithm developed and applied to TOFD images for segmentation of defects are highly reliable.Keywords
Time of Flight Diffraction (TOFD), Segmentation, Morphology, Image Processing, Defect Detection, Global Thresholding.
- Comparative Study of Diverse Techniques for Flaw Segmentation in TOFD Images of Austenitic Stainless Steel Weld
Abstract Views :221 |
PDF Views:0
Authors
Affiliations
1 Sathyabama University, Chennai - 600 119, Tamil Nadu, IN
2 Indira Gandhi Centre for Atomic Research, Kalpakkam - 603 102, Tamil Nadu, IN
1 Sathyabama University, Chennai - 600 119, Tamil Nadu, IN
2 Indira Gandhi Centre for Atomic Research, Kalpakkam - 603 102, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 8, No 30 (2015), Pagination: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 Region- Based 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 DefectFull Text