THE TEMPERATURE-VARIATION FAULT DIAGNOSIS OF HIGH-VOLTAGE ELECTRIC EQUIPMENT BASED ON INFORMATION FUSION

摘要：

As high-voltage electric equipment has complex structure and works in harsh environment, FBG (Fiber Bragg Gating) sensors were applied to realize the real-time monitoring of some characters in which temperature was taken as the main factor. Using neural network to recognize and classify fault types, making a further fusion of fault information by expert system. After simulation and experiment, it shows good results, and provides a effective way to realize the monitoring and exact diagnosis of temperature-variation fault on high-voltage electric equipment.

关键词： Information fusion neural network ezpert system FBG high-voltage electric equipment temperature-variation fault diagnosis

作者: YONG-WEI LI XING-DE HAN ZHEN-YU WANG

作者单位: College of Electrical Engineering and Information Science, Hebei University of Science and Technology, Shijiazhuang 050018, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 127-130

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）