基于Copula相似性的航空发动机RUL预测
RUL prediction for aero-engines based on Copula similarity
许先鑫 1李娟 1孙秀慧 1戴洪德2
作者信息
- 1. 鲁东大学数学与统计科学学院统计系,山东烟台 264025
- 2. 海军航空大学航空基础学院,山东烟台 264001
- 折叠
摘要
针对航空发动机性能退化特征众多,以及特征相互影响等问题,考虑退化特征间的非线性相关关系,提出了基于Copula相似性的航空发动机RUL(remaining useful life)预测方法.通过K-means聚类将航空发动机的工作状态分类,建立退化模型,选取退化性能趋势最明显的3组传感器.基于Copula函数对选取的3组传感器进行相关性建模分析,构建发动机传感器之间的Copula结构.基于Copula相似性实现对航空发动机的剩余寿命预测.结果表明:基于Copula相似性的航空发动机RUL预测方法相较传统方法,在发动机运行周期的50％、70％、90％预测误差分别减少13.053％、31.328％、74.602％,预测精度得到提高.
Abstract
In view of many degradation features of aero-engine performance and their mutual influence,the RUL(remaining useful life)prediction method of aero-engine based on Copula similarity was proposed considering the nonlinear correlations of the degradation features.The working state of the aero-engine was classified through K-means clustering,and a degradation model was established to select three sets of sensors with the most obvious degradation performance trend.Based on the Copula function,the correlation modeling and analysis of the selected three sets of sensors were carried out to build the Copula structure between engine sensors.The prediction of the remaining life of aero-engine was realized based on Copula similarity.The results showed that compared with traditional methods,the prediction errors of the aero-engine RUL based on Copula similarity were reduced by 13.053％,31.328％and 74.602％during the aero-engine operation cycle of 50％,70％,90％,respectively,and the prediction accuracy was improved.
关键词
预测与健康管理/特征退化/剩余使用寿命/Copula相似性/非线性Key words
prediction and health management/performance degradation/remaining useful life/Copula similarity/nonlinearity引用本文复制引用
出版年
2024
NETL
NSTL
万方数据