Multi-parameter Fusion Similarity-based Method for Remaining Useful Life Predicition of Civil Aviation Engines

被引：1
|
作者：
Cao H. [1 ]
Cui K. [1 ]
Liang J. [2 ]
机构：
[1] School of Aeronautical Engineering, Civil Aviation University of China, Tianjin
[2] Shanghai Aircraft Customer Service Co., Ltd., Shanghai
来源：
Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2020年 / 31卷 / 07期
关键词：
Civil aviation engine; Parameter fusion; ReliefF-PCA algorithm; Remaining life prediction; Similarity;
D O I：
10.3969/j.issn.1004-132X.2020.07.003
中图分类号：
学科分类号：
摘要：
Aiming at the problems that single parameter monitoring was not comprehensive and multi-monitoring parameter utilization rate was low in the research of civil aviation engine life prediction, a life prediction method was proposed based on multi-parameter fusion. In order to correct the parameter sensitivity, the ReliefF-PCA algorithm was used to screen the attributes of various monitoring parameters of the engine and to fuse them into the parameter-health index representing the engine health states. According to the different recession stages of the engine, the trend sensitivity of the similarity measurement algorithm was modified to increase the influence of the change trend on the prediction results. The effects of time domain on the algorithm were reduced by the translation of sample trajectory. Finally, the validity of the proposed method was verified by comparing the actual data. The results show that the improved method has better prediction accuracy. © 2020, China Mechanical Engineering Magazine Office. All right reserved.
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页码：781 / 787
页数：6
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