DocumentCode
2810958
Title
Research on Magnetic Flux Leakage Signals Quantity Technology of Tank Floor Corrosion Defects Based on Artificial Neural Network
Author
Yang, Zhijun ; Dai, Guang ; Li, Wei ; Jiang, Yanbiao
Author_Institution
Daqing Pet. Inst., Daqing, China
Volume
2
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
245
Lastpage
249
Abstract
Magnetic flux leakage testing method is a major direction of tank floor testing. In this paper, the spatial distribution of magnetic flux leakage field of tank floor corrosion defects is analyzed based on the features of magnetic flux leakage signals. BP neural network model is applied to the quantity analysis of tank floor corrosion defects. The results in network training and test reach the quantitative accuracy requirements of tank floor corrosion defects, the established BP neural network is effective to the quantitative recognition of depth and width of the defects.
Keywords
backpropagation; corrosion testing; magnetic flux; magnetic leakage; mechanical engineering computing; neural nets; tanks (containers); BP neural network model; artificial neural network; magnetic flux leakage signals quantity technology; magnetic flux leakage testing method; network training; quantity analysis; tank floor corrosion defects; tank floor testing; Artificial neural networks; Biological neural networks; Corrosion; Leak detection; Magnetic analysis; Magnetic fields; Magnetic flux leakage; Magnetic materials; Neural networks; Testing; corrosion defects; neural network; quantity; tank floor;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3736-8
Type
conf
DOI
10.1109/ICNC.2009.460
Filename
5362993
Link To Document