DTW based quantitative fault diagnosis of gas path component in turbofan

A quantitative fault diagnosis method was presented, based on pattern recognition principles for gas path component in turbofan. The method consists of a preprocessing step for multivariate dynamic data, where the magnitude dependent information is standardized, and a similarity assessment step via DTW (dynamic time warping). DTW is a flexible pattern matching method used in the area of speech recognition. The method was designed to classify faults independently of inconsistencies in the operating processes of turbofan ground test-runs. Quantitative diagnosis was fulfilled by the subdivision of fault pattern database according to the fault degree of gas path component. The results show that the method has a low false alarm rate and a high capability in isolating faults and is robust with measuring noise and other uncertainties.