ABSTRACT
This chapter introduces the basic elements of aero engine diagnosis and prognosis in terms of the working principle, sensor types, and the popular prognostics and health management platform. It discusses several well-implemented diagnostic approaches for single/multiple signal under single/multiple working conditions and failure modes. The chapter examines status prediction approaches, including degradation trends and remaining useful life predictions. It presents an example of actual failure-mode detection and prognosis from the engines of a modern commercial civil aircraft. The chapter focuses on state-of-the-art methods for the diagnosis and prognosis of aero engines through sensor data analytics. The traditional condition monitoring and diagnosis of aero engines in the aviation maintenance industry generally consists of four parts, namely, flight data analysis, nondestructive testing, lubricating oil parameter analysis, and vulnerable-parts tracking. The prediction of an aero engine performance degradation state is based on collected historical engine-monitoring data to predict engine performance trends.
