Abstract
Fuzzy neural networks fault diagnosis technology and diagnosis mode are used to diagnose cracks. It is trained with promoted BP arithmetic. The faults of cracked cantilever plate are diagnosed. Firstly the mode and frequency of numerical simulation intact plate and different cracked plates are calculated. Then five crack diagnosis indexes are calculated. Divide five indexes into three groups and create three fuzzy neural networks. The fuzzy neural networks are trained using these indexes, and diagnosis is taken to the crack in the end.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Liu, Z., Dong, G., Wang, W.: Engineering Structure Breaking Resistance Design Basis, pp. 3–5. Huazhong University of Technology Press, Wuhan (1990)
Zhang, L.: Artificial Neural Networks Model and Application, pp. 25–28. Xidian University Press, Xi’an (1995)
Zhang, J.: Research on Intelligent Diagnosis to Equipment Fault and Structural Crack Based on Vibration, pp. 54–76. Dalian University of Technology, Dalian (2003)
Grimes, P.J.: Advancements in Structural Dynamic Technology Resulting from Saturn Programs. NASA CR-1539 and CR-1540. 1 (1970) 6
Fox, C.H.J.: The Location of Defects in Structures: A Comparison of Natural Frequency and Mode Shape Data. In: Proceedings of the 10th International Modal Analysis Conference, USA, pp. 522–528 (1992)
Zhang, J.: Fault Diagnosis to Engineering Structure and Mechanical Equipment Based on Fuzzy Neural Network, pp. 20–35. Dalian University of Technology, Dalian (2003)
Zgonc, K., Achenbach, J.D.: A Neural Network for Crack Sizing Trained by Finite Element Calculations. NDT&E International 29, 147–155 (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhang, J., Meng, G., Zhao, D. (2004). The Study on Crack Diagnosis Based on Fuzzy Neural Networks Using Different Indexes. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_98
Download citation
DOI: https://doi.org/10.1007/978-3-540-28648-6_98
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22843-1
Online ISBN: 978-3-540-28648-6
eBook Packages: Springer Book Archive