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 :
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