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Towards proper sampling and statistical modelling of defects
Author(s) -
Cetin A.,
Roiko A.,
Lind M.
Publication year - 2015
Publication title -
fatigue and fracture of engineering materials and structures
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.887
H-Index - 84
eISSN - 1460-2695
pISSN - 8756-758X
DOI - 10.1111/ffe.12317
Subject(s) - sampling (signal processing) , statistics , reliability engineering , computer science , data mining , forensic engineering , engineering , mathematics , filter (signal processing) , computer vision
Predicting the size of the largest defect expected to occur in components based on samples obtained from polished inspection areas is a common exercise, which is even addressed in standards. However, the standard practice may occasionally yield poor results. This paper presents a comprehensive method that aims to improve some of the shortcomings of the standard practice. The method is utilized on actual defect data, which showed that the proposed method is able to predict significant experimental observations that the standard practice missed.