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AuthorQidwai, Uvais
AuthorBettayeb, Maamar
Available date2024-05-07T05:40:01Z
Publication Date2009
Publication NameIEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2009
ResourceScopus
Identifierhttp://dx.doi.org/10.1109/ISSPIT.2009.5407574
URIhttp://hdl.handle.net/10576/54714
AbstractIn this paper, a customized classifier is presented for the industry-practiced Nondestructive Evaluation (NDE) protocols using a Hybrid-Fuzzy Inference System (FIS) to classify the and characterize the defects commonly present in the steel pipes used in the gas/petroleum industry. The presented system is hybrid in the sense that it utilizes both soft computing through Fuzzy set theory, as well as conventional parametric analysis through Time-Frequency (TF) methods. Various TF transforms have been tested and the most suitable one for this application, Multiform Tiltable Exponential Distribution (MTED), is presented here. Four defining states are considered in the paper; Slag, Porosity, Crack, and Lack-of-Fusion, representing the four most critical types of defects present in welds on the pipes. The necessary features are calculated using the TF coefficients and are then supplied to the Fuzzy Inference system as input to be used in the classification. The resulting system has shown excellent defect classification with very low Misclassification and False Alarm rates.
Languageen
PublisherIEEE
SubjectDefect classification
Defect detection
Fuzzy inference system
Time frequency analysis
Ultrasonic NDT
TitleFuzzy time-frequency defect classifier for NDT applications
TypeConference Paper
Pagination303-309
dc.accessType Abstract Only


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