Weld Defects Classification in Radiographic Testing by Using AI |
Author(s): |
| Suhel Khan Pathan , Sangam University Bhilwara; Rakesh Bhandari, Sangam University Bhilwara |
Keywords: |
| Radiographic Testing, Algorithms, Weld-Defects AI (CNN) |
Abstract |
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In the fabrication industry, the non-destructive testing (NDT) is more necessary part for maintain the welding quality. Various types of NDT techniques using to provide better quality inspection. Today permanent record is required to using radiographic testing that’s identify the surface and sub-surface defect of welded part. In Radiographic testing film interpretation to required more competent person and its takes lot of time. Artificial intelligence to using to prepare algorithms that automatically interpret the existing radiographic data. Automatically detecting welding defect(Slag, Cracks, porosity, Pinhole, LOF, LOP etc.) by using CNN which is a deep learning basis. |
Other Details |
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Paper ID: IJSRDV10I30339 Published in: Volume : 10, Issue : 3 Publication Date: 01/06/2022 Page(s): 141-143 |
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