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Detection and diagnosis of air contaminants in spacecraft

机译:航天器空气污染物的检测与诊断

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In this paper we report on the development of the air quality monitoring and early detection system for an enclosed environment with specific emphasis on manned spacecraft. The proposed monitoring approach is based on the distributed parameter model of contaminant dispersion and real-time contaminant concentration measurements. The Implicit Kalman Filtering (IKF) algorithm is used to generate on-line estimations of the spatial contamination profile, which are used for the air quality monitoring and early detection of an air contamination event. We also solve the problem of the pointwise source identification of the convection-diffusion transport processes. This is done by convert identification problem into an optimization problem of finding a spatial location and the capacity of a point source which results in the best match of the model-predicted measurements to the observed measurements.
机译:在本文中,我们报告了在载人宇宙飞船上具有特定重点的封闭环境的空气质量监测和早期检测系统的发展。所提出的监测方法基于污染物分散和实时污染物浓度测量的分布参数模型。隐式卡尔曼滤波(IKF)算法用于生成空间污染轮廓的在线估计,其用于空气质量监测和早期检测空气污染事件。我们还解决了对流扩散传输过程的点源识别问题。这是通过将识别问题转换为找到空间位置的优化问题和点源的能力来完成的,这导致模型预测测量到所观察到的测量的最佳匹配。

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