A New Pattern Recognition Technique in Non Destructive Testing by the Use of Linear Discriminate Analysis

Saeedreza Ehteram, Alborz Sereshkeh, Seyed Z. Moussavi and Ali Sadr

Modern Applied Science, 2009, vol. 3, issue 5, 118

Abstract: One of the most challenging scientific industrial courses in recent years is intelligent defect detection. Non Destructive Testing (NDT) techniques are the most useful methods due to their efficiency and low cost. Models were developed to determine surface-breaking defects along the applied field when using the magnetic flux leakage (MFL) non-destructive technique. The theoretical model fits the experimental MFL results from simulated defects. For MFL sensors, the normal magnetic leakage field is subsequently used for evaluation of defects. Permeability variations were neglected by employing a flux density close to sample saturation. Three different defect geometries were experimentally investigated and the validity of the analytical model was verified. Different Feature extractor functions are applied in this paper to yield fast decision and more accurate. Indeed more accuracy is because of decision on different features that yields by employing two kinds of feature extractors, PCA and DCT. By hiring a BELBIC (Brain Emotional Learning Based Intelligent Controller) controller on the extracted features, the results are more accurate in some cases. Linear Discriminate Analysis (LDA) is another helpful instrument that is employed precise decision. All feature extractions LDAs and Multilayer perceptron (MLP), are methods for identifying erosion defects are described and employed in this paper. Great accuracy rate in compare between results of related approaches suggests that this Method can be used as an algorithm of MFL data interpretation technique.

Date: 2009
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ccsenet.org/journal/index.php/mas/article/download/1946/1850 (application/pdf)
https://ccsenet.org/journal/index.php/mas/article/view/1946 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ibn:masjnl:v:3:y:2009:i:5:p:118

Access Statistics for this article

More articles in Modern Applied Science from Canadian Center of Science and Education Contact information at EDIRC.
Bibliographic data for series maintained by Canadian Center of Science and Education ().