Data acquired from system sensors form the foundation upon which any health management system is based, and the available sensor suite directly impacts the absolute diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance, there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects sensor suites from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight and reliability into consideration. This procedure was originally applied to a large turbofan engine simulation at a single operating point, considering fault conditions represented by single component health parameter shifts. In the current study, sensor selection is expanded to consider multiple operating conditions such as takeoff and cruise, and more representative fault conditions.

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