Broken Steel Wire Rope Inspection Based on RBF Neural Network

Abstract:

In view of the problem of low detection precision exists in traditional quantitative detection system of broken wire for steel rope, the paper proposed a design scheme of quantitative detection system of broken wire for steel rope based on RBF neural network. The RBF Neural Network was introduced to establish the model of discerning quantitative broken steel wires. Experimental results showed that the method performed well in the identification of damage.

• Periodical: Advanced Materials Research (Volumes 614-615)
• Pages: 1734-1737
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.614-615.1734
• Online since: December 2012
• Authors: Zhen Chen, Yan Mei Liu
• Keywords: Broken Wire, Neural Network (NN), Quantitative Inspection, Steel Rope

References

[1] Huang Yue, Yang Shu, Chinese mechanical engineering, 1(1994)1-4.

[2] Kalwa E, Piekarski K.: NDT&E Internalional. 21 (1998) 2177-2182.

[3] J. Kennedy, R.C. Eberhart, Y. H. Shi, Swarm intelligence, San Francisco, Morgan Kaufman Publishers,2001.

[4] R.Y. Cui, B.R. Hong, X.F. Piao, China University of Mining & Technology, 33(2004)668-672.

[5] J. D. Powell, Proceedings of the Numerical analysis, Dundee, (1987)223-241.

[6] D. T. Pham, X. Liu, Systems Engineering, 2(1992)90-97.

[7] J. Kennedy, R. C. Eberhart, Proceedings of IEEE International Conference on Neural Network. Piscataway, IEEE Press,(1995)1942-1948.

[8] Y. H. Shi, R.C. Eberhart, Proceedings of SCI Conference. Piscataway, IEEE Press, (1999) 1945-1950.

[9] D. Y. Zhu, H. Shi, Principle and application of artificial neural network, Beijing: Science Press, 2006.