Safety Boundary Extraction Using FCM and Prediction Using ELM for Aero-engine Performance Parameters*

Abstract

The safety boundary of Aero-engine performance parameters is one of the essential criteria for measuring aero-engine performance. However, due to the differences among individuals and discrepancies among the working environments, the fixed theoretical boundary is no longer sufficient for engineering needs. In this paper, a method based on fuzzy C-means (FCM) and Extreme Learning Machine (ELM) is proposed to extract and predict the safety boundary for aero-engine performance parameters. Firstly, the residuals between the predicted values and the actual values are used as the quantitative basis to extract the safe boundary. And then the ELM algorithm is used to forecast the safety boundary for next period of time. The method mentioned in this paper enhances the accuracy and generalization of safety boundary due to improvement for specific situations. The effectiveness of this method has been verified by simulation case.