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