RUL prediction for aero-engines based on Copula similarity
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.
prediction and health managementperformance degradationremaining useful lifeCopula similaritynonlinearity
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