Research of Fuzzy Neural Network in the Fault Diagnosis of Numerically-Controlled Machine Tool

Abstract:

At present, our rapid development of a processing industry requires the increasing number of numerically-controlled machine tool. At the same time, people grow the attention of diagnosing the fault in order to repair the machine one time. This article starts the research of fault diagnosis based on fuzzy neural network. At first, it evaluates the structure and learning method of fuzzy neural network. In the second place, this paper analyzes the numerically-controlled machine tool in details, and summarizes the fault and reason. At last, this article makes the comprehensive research of neural network and fault diagnosis and provides part of the code. It has positive guiding significance to the worker of numerically-controlled machine tool.

• Periodical: Applied Mechanics and Materials (Volumes 490-491)
• Pages: 1754-1758
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.490-491.1754
• Online since: January 2014
• Authors: Xing Yun Chen, Jing Zi Wei
• Keywords: Fault Diagnosis, Neural Network (NN), Numerically-Controlled Machine Tool

References

[1] Gao haibin, Zheng chengbo, Liu bin, Frequency controllor for wireless power based on fuzzy neural network, Chinese journal of scientific instrument, 27(6)pp.1861-1862, (2006).

[2] Deng Sanpeng, Structure and maintenance of numerical-controlled machine tool, Beijing: National Defense Industry Press, (2008).

[3] Chen Liyun, evaluation and design of Fuzzy controller based on T-S model , Tianjin: Tianjin University, (2005).

[4] Sun Tao, Fault diagnosis case analysis of numerically-controlled machine tool, Manufacture Information Engineering of China, 2, pp.75-77, (2010).

[5] Jinag xiuhua, Research on NC equipment fault-handling, Manufacturing Automation , Vol. 32, No. 8, pp.30-32, (2011).