Open Access
| Issue |
E3S Web Conf.
Volume 95, 2019
The 3rd International Conference on Power, Energy and Mechanical Engineering (ICPEME 2019)
|
|
|---|---|---|
| Article Number | 04008 | |
| Number of page(s) | 5 | |
| Section | Materials Science and Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/20199504008 | |
| Published online | 13 May 2019 | |
- Lei Jiyao et al. Engineering signal processing technology. Chongqing: Chongqing University Press, 1990(in Chinese) [Google Scholar]
- Liu Ling. Zhangxi. Wang Linna. Current Situation and Development of Fault Diagnosis Technology [Journal Papers] Electronic Testing 2016 (2) (in Chinese) [Google Scholar]
- Zhang Xinhai.Lei Yong. Application of BP Neural Network in Mechanical Fault Diagnosis. Northwest Polytechnic University: School of Power and Energy, 2008(in Chinese) [Google Scholar]
- Dai Min. Xie Chun. Fault Diagnosis of Aircraft Engine Based on Fuzzy Weighted Nonferrous Network and BP Neural Network [Journal Papers] Science, Technology and Engineering. 2012(in Chinese) [Google Scholar]
- Li Ning, Lei Hongli, Han Jianding, Zhu Xihua. Research on Fault Reasoning Model of Aircraft Switched Reluctance Generation System [Journal Paper] Power Supply Technology. 2011 (5) (in Chinese) [Google Scholar]
- M. Demtgul, I.N. Tansel and S. Taskin.Fault diagnosis of pneumatic systems with artificial neural network Algorithms, Expert Systems with Applications, 2009, 36(7),10514–10519. [Google Scholar]
- S.C. Liu,S.Y. Liu,in:An Efficient Expert System for Machine Fault Diagnosis Source. International Journal of Advanced Manufacturing Technology. 2003, 21(9):69l–698. [Google Scholar]
- Autar R.K. An Automated Diagnostic Expert System for Diesel Engines. Journal of Engineering for Gas Turbines and Power,1996,118:673—679. [CrossRef] [Google Scholar]
- Davia J, Krivine J, Tiarri J et al. DIVA Recognition of Typical Situations for Turbine Generator Diagnosis. Journal of Intelligent and Robotic Systems,1988, 1:287–298. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.