DocumentCode
2094029
Title
Crack Fault Diagnosis Based on MEP Based Neural Network
Author
Liu, Mingjun ; Xiu, Liming ; Jia, Guangfeng ; Chen, Yuehui
Author_Institution
Sch. of Electr. Eng. & Autom., Harbin Inst. of Technol., Harbin, China
Volume
1
fYear
2008
fDate
20-22 Dec. 2008
Firstpage
635
Lastpage
639
Abstract
The Multi Expression Programming (MEP) and Neural Network (NN) is applied to the crack fault diagnosis of structure. The inherent frequency and the position of the crack obtained by ANSYS are used as parameters of the neural network. This approach employs MEP to evolve the architecture and the parameters encoded in the NN. This framework allows input variables selection, over-layer connections for the various nodes involved. It is showed that the proposed method is feasible to diagnose the crack fault of structure.
Keywords
cracks; fault diagnosis; mathematical programming; mechanical engineering computing; neural nets; ANSYS; MEP based neural network; crack fault diagnosis; input variables selection; multi expression programming; overlayer connections; Algorithm design and analysis; Artificial neural networks; Bridges; Fault diagnosis; Feedforward neural networks; Feedforward systems; Input variables; Inspection; Neural networks; Safety;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Computational Technology, 2008. ISCSCT '08. International Symposium on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-3746-7
Type
conf
DOI
10.1109/ISCSCT.2008.274
Filename
4731508
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