@inproceedings{f1f7ce856281484cada63558670e5b38,
title = "Magnetic flux leakage detection in non destructive tests performed on ferromagnetic pieces, using signal processing techniques and data mining",
abstract = "In this paper we propose the use of Support Vector Machine classifiers (SVM) and linear discriminant analysis (LDA) to determine the existence of magnetic flux leakage (MFL) in non-destructive testing (NDT for its acronym in English) performed on ferromagnetic sheets. These signals were provided by the Corporation for Research in Corrosion (CIC) and were acquired on a dyno. The signals are preprocessed to; filter data (ie Wavelet Transform), remove the existing noise (ie thresholding), baseline correction (ie Least Squares Theorem (LST)) and normalize the data (ie First Normal Form). Within the aims of the project are design suitable classifier for each technical proposed for this phenomenon, and a comparison between them to determine which had the best performance.",
keywords = "LDA, MFL, NDT, SVM",
author = "Aldana, {Aldair Barajas} and Jaime Parra-Raad and Arizmendi, {Carlos Julio}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 3rd International Congress of Engineering Mechatronics and Automation, CIIMA 2014 ; Conference date: 22-10-2014 Through 24-10-2014",
year = "2014",
month = dec,
day = "11",
doi = "10.1109/CIIMA.2014.6983455",
language = "Ingl{\'e}s",
series = "2014 3rd International Congress of Engineering Mechatronics and Automation, CIIMA 2014 - Conference Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Marrugo, {Andres G.}",
booktitle = "2014 3rd International Congress of Engineering Mechatronics and Automation, CIIMA 2014 - Conference Proceedings",
}