DocumentCode :
2294091
Title :
Wavelet Neural Network Based Intelligent System for Oil Pipeline Defect Characterization
Author :
Tikaria, Mamta ; Nema, Shikha
Author_Institution :
SAKEC, Mumbai, India
fYear :
2010
fDate :
19-21 Nov. 2010
Firstpage :
42
Lastpage :
47
Abstract :
Wavelet neural network is a new kind of network which fuses advantages of wavelet transform and neural computing. It utilizes the good localize character of the wavelet transformation and combines the self learning function of the neural network. It has the ability of strong adaptive learning and function approach. Wavelet neural network has the simple implementation process and fast convergence rate, therefore it can be used to detect the defect of oil pipe. This paper presents a wavelet neural network approach for detection and characterization of defects from magnetic flux leakage signal.
Keywords :
flaw detection; inspection; learning (artificial intelligence); magnetic flux; mechanical engineering computing; neural nets; pipelines; wavelet transforms; adaptive learning; defect detection; intelligent system; magnetic flux leakage signal; neural computing; oil pipeline defect characterization; self learning function; wavelet neural network; wavelet transform; Magnetic Flux Leakage (MFL) technique; Neural Network; Wavelets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Emerging Trends in Engineering and Technology (ICETET), 2010 3rd International Conference on
Conference_Location :
Goa
ISSN :
2157-0477
Print_ISBN :
978-1-4244-8481-2
Electronic_ISBN :
2157-0477
Type :
conf
DOI :
10.1109/ICETET.2010.88
Filename :
5698288
Link To Document :
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