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Toward a Real-Time Measurement-Based System for Estimation of Helicopter Engine Degradation Due to Compressor Erosion

机译:朝着基于实时测量的基于测量系统,用于估计直升机发动机劣化引起的压缩机侵蚀

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This paper presents a preliminary demonstration of an automated health assessment tool, capable of real-time on-board operation using existing engine control hardware. The tool allows operators to discern how rapidly individual turboshaft engines are degrading. As the compressor erodes, performance is lost, and with it the ability to generate power. Thus, such a tool would provide an instant assessment of the engine's fitness to perform a mission, and would help to pinpoint any abnormal wear or performance anomalies before they became serious, thereby decreasing uncertainty and enabling improved maintenance scheduling. The research described in the paper utilized test stand data from a T700-GE-401 turboshaft engine that underwent sand-ingestion testing to scale a model-based compressor efficiency degradation estimation algorithm. This algorithm was then applied to real-time Health Usage and Monitoring System (HUMS) data from a T700-GE-701C to track compressor efficiency on-line. The approach uses an optimal estimator called a Kalman filter. The filter is designed to estimate the compressor efficiency using only data from the engine's sensors as input.
机译:本文介绍了一种自动健康评估工具的初步演示,可以使用现有的发动机控制硬件实时车载操作。该工具允许操作员辨别快速单独的涡轮轴引擎如何降级。随着压缩机的侵蚀,性能丢失,并且有能力产生电源。因此,这种工具将提供对发动机的适应性的即时评估以执行任务,并且在它们变得严重之前有助于确定任何异常磨损或性能异常,从而降低不确定性并实现改进的维护调度。本文中描述的研究利用来自T700-GE-401涡轮轴发动机的测试支架数据,该发动机接受了砂吸收测试,以规模基于模型的压缩机效率降级估计算法。然后将该算法应用于来自T700-GE-701C的实时健康使用和监控系统(HUMS)数据,以跟踪压缩机效率在线。该方法使用称为卡尔曼滤波器的最佳估计器。滤波器旨在仅使用来自发动机的传感器的数据作为输入来估计压缩机效率。

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