Detection and transient dynamics modeling of experimental hypersonic inlet unstart
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During unstart, the rapid upstream propagation of a hypersonic engine's inlet shock system can be clearly seen through inlet pressure measurements. Specifically, the magnitude of the pressure readings suddenly and dramatically increases as soon as the leading edge of the shock system passes the measurement location. A change detection algorithm can monitor the pressure time history at a given sensing location and determine when an abrupt pressure rise occurs. If this kind of information can be obtained at various sensing locations distributed throughout the inlet then a feedback control scheme has an improved basis upon which to make actuation decisions for preventing unstart. In this thesis a variety of change detection algorithms have been implemented and tested on multiple sources of experimental high-speed pressure transducer data. The performance of these algorithms is compared and suitability of each algorithm for the general unstart problem is discussed. Attempts to model the transient dynamics governing the unstart process have also been made through the use of system identification techniques. The result of these system identification efforts is a partially nonlinear mathematical model that describes shock motion through pressure signals. The process reveals that the nonlinear behavior can be separated from the linear with relative ease. Related attempts are then made to create a model where the nonlinear portion has been specified leaving only the linear portion to be determined by system identification. The modeling and identification process specific to the unstart data used is discussed and successful models are presented for both cases.