The Application of Intelligent Fault Diagnosis Technology on the Loader System of One Self-Propelled Gun
In this paper, first, the principle of the configuration and function of a certain self-propelled guns loader system is introduced, as well as the character of the failure model of it, and the significance of the fault diagnosis technology research on the loader system is pointed out. Next, expert system, neural network, case-based reasoning and fuzzy logic, which are four of the methods of the intelligent fault diagnosis technology, are analyzed in detail, especially their technique trait and scope of application. Each advantages and disadvantages, along with their applicability in the area of fault diagnosis on self-propelled guns loader system are obtained after the analysis. Then a way to build a fault diagnosis expert system with a hybrid reasoning method is confirmed. Finally, a diagnosis example is presented, in order to validate the diagnosis system is feasible.
self-propelled gun loader system artificial intelligence fault diagnosis ezpert system
Zhao Jiguang Sun Zhongsheng Chen Jingpeng Cao Zhen Li Xiaoli
Department of Space Equipment, the Academy of Equipment Command & Technology, Beijing 101416, China Company of Postgraduate Management, the Academy of Equipment Command & Technology, Beijing 101416, C The NO.127 Military Delegation Office, Qiqihaer 161000, China
国际会议
第八届国际测试技术研讨会(8th International Symposium on Test and Measurement)
重庆
英文
1520-1523
2009-08-01（万方平台首次上网日期，不代表论文的发表时间）