[논문]Detection of Subsurface Defects in Metal Materials Using Infrared Thermography; Image Processing and Finite Element Modeling

Ranjit, Shrestha; Kim, Won Tae

doi:10.7779/jksnt.2014.34.2.128

Detection of Subsurface Defects in Metal Materials Using Infrared Thermography; Image Processing and Finite Element Modeling 원문보기

비파괴검사학회지 = Journal of the Korean Society for Nondestructive Testing, v.34 no.2, 2014년, pp.128 - 134

Ranjit, Shrestha (Department of Mechanical Engineering, Kongju National University) , Kim, Won Tae (Department of Mechanical Engineering, Kongju National University)

Abstract ▼ AI-Helper

Infrared thermography is an emerging approach to non-contact, non-intrusive, and non-destructive inspection of various solid materials such as metals, composites, and semiconductors for industrial and research interests. In this study, data processing was applied to infrared thermography measurements to detect defects in metals that were widely used in industrial fields. When analyzing experimental data from infrared thermographic testing, raw images were often not appropriate. Thus, various data analysis methods were used at the pre-processing and processing levels in data processing programs for quantitative analysis of defect detection and characterization; these increased the infrared non-destructive testing capabilities since subtle defects signature became apparent. A 3D finite element simulation was performed to verify and analyze the data obtained from both the experiment and the image processing techniques.

주제어

AI 본문요약
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제안 방법

The use of these methods has increased the infrared non-destructive testing (NDT) capabilities since subtle defects became more apparent. 3D finite element simulation (ANSYS program) was performed to verify and analyzed the data obtained from both the experiment and the image processing techniques.

대상 데이터

A square shaped (180 mm × 18 mm) specimen of the stainless materials (STS 304) was used in the experiment.

참고문헌 (14)

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원문보기 상세보기
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상세보기
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상세보기
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