Prognostics and health management (PHM) is a widely-used effective discipline consisting of advanced technologies and methods to assess the reliability of a system under its actual application conditions. It can be used to improve the safety and reliability of aircraft engines (AEs). In a PHM system for AEs, a large number of sensors are installed to provide health condition information. A selection of a minimal subset of the most informative and cost-effective sensors is required to monitor the optimum performance. In this paper, a PHM-oriented sensor optimization selection model is developed, which considers both sensor cost and monitoring performance as objective functions, and takes the PHM requirements as the constraints. A numerical example is given to demonstrate the sensor selection approach for an aircraft gas turbine engine. The results demonstrated that the proposed model and algorithm were effective and feasible, and were able to effectively guide the sensor selection for AEs.Index Terms-Prognostics and health management, multiobjective, sensor optimization selection, aircraft engines.1530-437X (c) He is also an IEEE member. His area of research interest mainly focuses on complex systems integrated health management, systems engineering, and risk management.