The Condition Trend Analysis of Aircraft Key Components Based on D-S Evidence Theory

摘要：

In order to improve and heighten the accuracy of condition trend analysis to key components of aircraft, to grasp their running state in time and avoid accidents, In the beginning, the paper analyze a lot of characteristic dates of running state from a large number of long-term tests deeply. On this basis, two condition trend analysis models: GM(1,1) and ARMA model are established, using these two models to analyze the condition trend of key components of aircraft, and operating the decision-level fusion of the results of the above models with D-S evidence theory. The research shows that both of GM(1, 1) model and ARMA model can predict the condition trend of key components of aircraft, and we can get the better result after using D-S evidence theory fusion. So this paper gives a good trend analysis method, and it has a good value of engineering application.

关键词： Key Components of Aircraft Condition Trend Analysis GM (1 1) ARMA (n m) D-S Evidence Theory

作者: Jianguo Cui Jianqiang Shi Shiliang Dong Liying Jiang Rui Lv Haigang Liu

作者单位: School of Automation, Shenyang Aerospace University, Shenyang 110136, China Shenyang Aircraft Design & Research Institute, Shenyang 110035, China

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 2276-2281

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）