Application of the Systematic Sensor Selection Strategy for Turbofan Engine DiagnosticsThe data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall 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 sensor selection 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 a sensor suite 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 applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.
Document ID
20080013422
Acquisition Source
Glenn Research Center
Document Type
Conference Paper
Authors
Sowers, T. Shane (Analex Corp. Cleveland, OH, United States)
Kopasakis, George (NASA Glenn Research Center Cleveland, OH, United States)
Simon, Donald L. (NASA Glenn Research Center Cleveland, OH, United States)