Modeling the x-ray process and x-ray flaw size parameter for POD studies
Author(s) -
Ajay M. Koshti
Publication year - 2014
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.2044677
Subject(s) - calibration , detector , nondestructive testing , sensitivity (control systems) , statistical power , monotonic function , range (aeronautics) , point of delivery , reliability (semiconductor) , process (computing) , contrast (vision) , algorithm , estimation theory , computer science , power (physics) , mathematics , statistics , materials science , engineering , electronic engineering , artificial intelligence , mathematical analysis , physics , telecommunications , agronomy , quantum mechanics , composite material , biology , operating system
Nondestructive evaluation (NDE) method reliability can be determined by a statistical flaw detection study called probability of detection (POD) study. In many instances, the NDE flaw detectability is given as a flaw size such as crack length. The flaw is either a crack or behaving like a crack in terms of affecting the structural integrity of the material. An alternate approach is to use a more complex flaw size parameter. The X-ray flaw size parameter, given here, takes into account many setup and geometric factors. The flaw size parameter relates to X-ray image contrast and is intended to have a monotonic correlation with the POD. Some factors such as set-up parameters, including X-ray energy, exposure, detector sensitivity, and material type that are not accounted for in the flaw size parameter may be accounted for in the technique calibration and controlled to meet certain quality requirements. The proposed flaw size parameter and the computer application described here give an alternate approach to conduct the POD studies. Results of the POD study can be applied to reliably detect small flaws through better assessment of effect of interaction between various geometric parameters on the flaw detectability. Moreover, a contrast simulation algorithm for a simple part-source-detector geometry using calibration data is also provided for the POD estimation.
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