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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2020.1
- 수록면
- 1,597 - 1,601 (5page)
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초록· 키워드
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Background: Non-destructive evaluation of defects in metals or composites specimens is a regular method in radiographic imaging. The maintenance examination of metallic structures is a relatively difficult effort that requires robust techniques for use in industrial environments. Methods: In this research, iron plate, lead marker and tungsten defect with a 0.1 cm radius in spherical shape were separately simulated by MCNP code and SuperMC software. By 192Ir radiation source, two exposures were considered to determine the depth of the actual defined defect in the software. Also by the code, displacement shift of the defect were computed derived from changing the source location along the x- or y-axis. Results: The computed defect depth was identified 0.71 cm in comparison to the actual one with accuracy of 13%. Meanwhile, the defect position was recognized by disorder and reduction in obtained gamma flux. The flux amount along the x-axis was approximately 0.5Eþ11 units greater than the y-axis. Conclusion: This study provides a method for detecting the depth and position of the defect in a particular sample by combining code and software simulators
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참고문헌 (31)
참고문헌 신청
I. Valavanis / 2010 / Multiclass defect detection and classification in weld radiographic images using geometric and texture features / Expert Syst. Appl 37(12):7606~7614
ASTM / 2019 / Standard Practice for Radiographic Examination of Weldments Using Industrial X-Ray Film
Nacereddine N / 2005 / Weld defect detection in industrial radiography based digital image processing / 3rd International Conference:Sciences of Electronic, Technologies of Information and Telecommunications
E. Nazemi / 2019 / A novel method for predicting pixel value distribution non-uniformity due to heel effect of Xray tube in industrial digital radiography using artificial neural network / J. Nondestruct. Eval 38:3
G. De Angelis / 2012 / A new technique to detect defect size and depth in composite structures using digital shearography and unconstrained optimization / NDT E Int 45(1):91~96
ASTM / 2019 / Standard Practice for Radiographic Examination of Weldments Using Industrial X-Ray Film
Nacereddine N / 2005 / Weld defect detection in industrial radiography based digital image processing / 3rd International Conference:Sciences of Electronic, Technologies of Information and Telecommunications
E. Nazemi / 2019 / A novel method for predicting pixel value distribution non-uniformity due to heel effect of Xray tube in industrial digital radiography using artificial neural network / J. Nondestruct. Eval 38:3
G. De Angelis / 2012 / A new technique to detect defect size and depth in composite structures using digital shearography and unconstrained optimization / NDT E Int 45(1):91~96
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