MATEC Web of Conferences
Volume 22, 2015International Conference on Engineering Technology and Application (ICETA 2015)
|Number of page(s)||5|
|Section||Electric and Electronic Engineering|
|Published online||09 July 2015|
- Bridgman M S. 2002. Relating failure prognostics to system benefits. Aerospace Conference Proceedings, (7): 3521–3526. [Google Scholar]
- Chang Shuping, Wu Ruitao. 2011. The application of failure prognostic system in state monitoring of power plant generation equipments. GEESD, 2011 International Conference, Jilin: [s.n.]. [Google Scholar]
- Chang Shuping, Guo Jianglong, Lv Yukun. 2011. The application of nonlinear state estimation method in fault warning system. Software, 32(7): 57–60. [Google Scholar]
- Mo Juan, Wang Xue, Doong Ming, Yan Zhang. 2004. Power transformer fault diagnosis based on rough set theory, Chinese Society for Electrical Engineering, 24(7): 162–167. [Google Scholar]
- Xiong Hao, Sun Caixing, Du Peng. 2006. Integrated condition assessment of power transformer based on matter element theory. Journal of Chongqing University (Natural Science Edition), 29(10): 24–28. [Google Scholar]
- Jianyuan, Ji Yancliao. 2003. Application of fuzzy Petri knowledge representation in electric power transtormer fault diagnosis. Proceedings of the CSEE 2003, 23(1): 121–125 [Google Scholar]
- Sun Hui, Li Weidong, Sun Qizliong. Electric power transformer fault diagnosis using decision tree. Proceedings of the CSEE 2001, 21(2): 50–55 [Google Scholar]
- Qian Zheng, Yan Zhang, Luo Chengmu. 2001. Fault diagnosis method of power transformer by integrating case-based reasoning with fuzzy theory and neural network. High Voltage Engineering, 27(6): 1–5. [Google Scholar]
- Shu Hongchun, Sun Yiangtei, Si Dajun. ARS approach to founding and maintaining ES knowledge base for fault diagnosis of power transformer. Proceedings of the CSEE 2002, 22(2): 31–35. [Google Scholar]
- Yang Li, Qian Zheng, Zhou Yueteng, et al. 1999. Parsimonious covering theory applied for identifying power transformer malfunction. Journal of Yi’an Jiaotong University, 33(4): 13–16 [Google Scholar]
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