DocumentCode
3024150
Title
Application of ANN in the Thickness Measuring of Conductive Materials
Author
Zhang Wei ; Qu Surong ; Li, Li ; Miao Qinglin ; Song Changyuan
Author_Institution
Sch. of Mechinery & Electron., Henan Inst. of Sci. & Technol., Xinxiang, China
Volume
4
fYear
2009
fDate
7-8 Nov. 2009
Firstpage
94
Lastpage
97
Abstract
Eddy current testing (ECT) is becoming a widely used inspection technique, particularly in the aircraft, power and nuclear industries. Many factors may affect the eddy current response. Inverse problems to determine the thickness from ECT signals of multilayer conductors have been a challenge for a certain degree. The objectives of this study are to introduce a method based on improved back propagation neural network (BPNN) to identify the multilayer thickness from their ECT signals. The simulation study and an experimental validation carried out on a number of specimens with different known thickness confirmed the suitability of the proposed approach for multilayer thickness measuring.
Keywords
backpropagation; eddy current testing; inspection; neural nets; production engineering computing; ANN; back propagation neural network; conductive materials; eddy current response; eddy current testing; inspection technique; inverse problems; multilayer conductors; multilayer thickness measuring; Aerospace materials; Aircraft; Artificial neural networks; Conducting materials; Conductivity measurement; Eddy current testing; Electrical capacitance tomography; Inspection; Multi-layer neural network; Thickness measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-3835-8
Electronic_ISBN
978-0-7695-3816-7
Type
conf
DOI
10.1109/AICI.2009.468
Filename
5376421
Link To Document