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Reaction Wheel Performance Characterization Using the Kepler Spacecraft as a Case Study

机译:开普勒飞船的反作用轮性能表征作为案例研究

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The Kepler spacecraft had lost two of its four reaction wheels by 2012, and the Kepler attitude engineers were forced to create a novel concept of operations to continue the mission. Monitoring the health and performance of the surviving wheels became a critical task, as loss of another wheel would be mission-ending. To support these efforts, a group of students at the Laboratory for Atmospheric and Space Physics developed, verified, and refined an analysis tool to identify changes in reaction wheel behavior. The tool compares the data we are interested in analyzing to a verified set of baseline data, then filters the comparison to further highlight trending. The baseline data is created for each wheel independently, and it associates commanded torque to reaction wheel speed. The tool compares the measured data from the spacecraft with the baseline, producing a set of residuals that we call delta torque. These values are passed through a Kalman filter and the resulting trend line is studied to find changes in behavior. We have identified torque changes that occurred in the two failed wheels before they were lost completely. Since the start of K2, our tool has also identified friction events in the remaining two reaction wheels. This tool was developed specifically for the Kepler mission, but the method could be easily applied to any mission that uses reaction wheels.
机译:开普勒航天器到2012年失去了四个反作用轮中的两个,开普勒姿态工程师被迫创造一种新颖的作战概念来继续执行任务。监视幸存的车轮的健康状况和性能已成为一项关键任务,因为丢失另一个车轮将导致任务结束。为了支持这些努力,大气和空间物理实验室的一组学生开发,验证并完善了一种分析工具,以识别反作用轮行为的变化。该工具将我们感兴趣的数据与经过验证的基准数据集进行比较,然后过滤比较以进一步突出趋势。为每个车轮独立创建基准数据,并将基准扭矩与反作用轮速度相关联。该工具将航天器的测量数据与基线进行比较,从而产生一组残差,我们称其为增量扭矩。这些值通过卡尔曼滤波器传递,并研究所得趋势线以发现行为的变化。我们已经确定了在两个故障车轮完全丢失之前发生的扭矩变化。自K2开始以来,我们的工具还确定了其余两个反作用轮中的摩擦事件。该工具是专为开普勒任务而开发的,但是该方法可以轻松地应用于任何使用反作用轮的任务。

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