JOURNAL ARTICLE

DWT Based Automated Weld Pool Detection and Defect Characterisation from Weld Radiographs

Abstract

Industrial Radiography is the most widely accepted NDT technique for weld quality in industries. As it is an indirect method, defect type and nature must be obtained by analyzing the radiographs. Manual interpretation of radiographs is subjective in nature. So the paradigm shifted to automated weld defect detection system. Though considerable research is done in automated weld defect detection, an accurate domain specific technique has not yet been evolved due to noise, artifacts in radiographs, low contrast between the defect region and the background and difficulty in isolating the defect. The proposed work aims at developing an automated weld defect detection system that enhances the contrast between the object and the background and isolates the weld defect. In this work, real time weld radiographs are acquired and contrast enhancement is performed with DWT. Slag and Porosity are isolated and dimensionally characterized.

Keywords:
Radiography Radiographic testing Welding Nondestructive testing Contrast (vision) Noise (video) Materials science Artificial intelligence Biomedical engineering Computer vision Computer science Radiology Engineering Medicine Metallurgy Image (mathematics)

Metrics

3
Cited By
0.35
FWCI (Field Weighted Citation Impact)
6
Refs
0.65
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Welding Techniques and Residual Stresses
Physical Sciences →  Engineering →  Mechanical Engineering
Non-Destructive Testing Techniques
Physical Sciences →  Engineering →  Mechanical Engineering
Advanced X-ray and CT Imaging
Physical Sciences →  Engineering →  Biomedical Engineering
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