Design of intelligent diagnosis system based on CBR for jet engine

摘要

Condition monitoring and fault diagnosis are crucial for insuring flight safety. According to characteristics of complex systems, this paper proposes an intelligent system for off-line fault detection and diagnosis for gas path components in jet engine. Based on a machine learning methodology named Case-based Reasoning (CBR), this system consists of two types of case-bases, static case-base and dynamic case-base. Dynamic time warping (DTW) is used to retrieve dynamic cases by assessing the similarity between two dynamic sequence samples.