Jet engine gas path fault diagnosis using dynamic fusion of multiple classifiers

Jet engine gas path fault diagnosis is not only important in modern condition-based maintenance of aircraft engines, but also a challenging classification problem. Exploring more advanced classification techniques for achieving improved classification performance for gas path fault diagnosis, therefore, has been increasingly active in recent years in PHM community. To that end, in this paper, we apply a recently developed dynamic fusion scheme to gas path fault diagnosis. Through designing a real-world gas path fault diagnostic system, we demonstrate that dynamic fusion of multiple classifiers can be effective in improving classification performance of gas path diagnosis.