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Detection and Transient Dynamics Modeling of Experimental Hypersonic Inlet Unstart

机译:实验性超音速进气口起步的检测和瞬态动力学建模

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During unstart, the rapid upstream propagation of a hypersonic engine's inlet-isolator shock system can be readily detected through 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. An online 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 paper, 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 the 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 dynamic model that describes shock motion through pressure signals. The process reveals the possibility of partitioning the nonlinear behaviors from the linear dynamics with relative ease. Related attempts are then made to create a model where the nonlinear portion has been pre-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 the full system identification and the partitioned model cases.
机译:在启动过程中,高超音速发动机的进气-隔离器减震系统在上游的快速传播可以通过压力测量轻松地检测到。特别是,一旦减震系统的前端通过测量位置,压力读数的大小就会突然急剧增加。在线变化检测算法可以监视给定传感位置处的压力时间历史,并确定何时出现突然的压力上升。如果可以在分布在整个进气口的各个感应位置处获得此类信息,则反馈控制方案将具有改进的基础,在该基础上可以做出用于防止启动的致动决策。在本文中,已在多种实验高速压力传感器数据源上实现并测试了多种变化检测算法。比较了这些算法的性能,并讨论了每种算法对一般启动问题的适用性。还尝试通过使用系统识别技术来对控制启动过程的瞬态动力学进行建模。这些系统识别工作的结果是部分非线性的动力学模型,该模型通过压力信号描述了冲击运动。该过程揭示了相对容易地将非线性行为与线性动力学区分开的可能性。然后进行相关尝试以创建模型,其中已预先指定了非线性部分,仅留下了要由系统识别确定的线性部分。讨论了特定于未使用数据的建模和识别过程,并针对完整的系统识别和分区模型案例提供了成功的模型。

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