Fault Diagnosis for Launch Vehicle Based on Multi-sensor Information Fusion and Rough Neural Network

摘要：

In allusion to the possible faults of the launch vehicle, multi-sensor information fusion and rough neural network (RNN) technologies have been adopted to fault diagnosis. The equipment information is collected by different kinds of wireless sensors and conveyed to fusion center. After data preprocessing, feature correlation and normalization, feature information fusion by rough neural network technology has been achieved for fault automatic monitoring and recognition. Finally, fault diagnostic experiments show that the diagnostic precision of the system improved in evidence than single-sensor system.

关键词： Information Fusion Rough Neural Network Fault Diagnosis

作者: ZHAO Junyang ZHANG Zhili JIANG Xiaocun

作者单位: Xian Research Inst. Of Hi-tech Hongqing Town, Xian, China 710025 Sec. 102, The Second Artillery Petty Officer School, Qingzhou Shandong China 262500

会议类型: 国际会议

会议名称: 第七届国际测试技术研讨会

会议地点: 北京

会议语种:英文

在线出版日期: 2007-08-05（万方平台首次上网日期，不代表论文的发表时间）