Dynamic source identification of emitting characters in enclosed environments
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摘要: 载人航天器、飞机、潜艇等密闭微环境,随着人员停留时间的延长,舱室空气污染问题已成为危害工作人员生命安全的主要因素.为了提高上述密闭环境主动应对突发污染的能力,建立一种新的浓度离散随机模型,提出采用敏感性分析算法实现污染源定位及强度估计,利用隐式与显式卡尔曼滤波相结合的方法同时完成污染源散发特性的动态辨识及舱室空气污染物的浓度预测;分析了不同位置处的传感器可辨识区域,给出最优传感器布置策略.仿真结果证实了敏感性分析算法及隐式与显式卡尔曼滤波相结合方法能够实现污染源散发特性的快速准确辨识.Abstract: Along with the prolonging of people-s staying time in enclosed environments such as spacecraft, aircraft, submarine and so on, air pollution in the cabin has become a main factor which endangers missionaries- life safety. To improve the ability of these enclosed environments in dealing with sudden contaminant, a novel discrete concentration stochastic model was established. The sensitivity analysis algorithm which can identify source location and strength was presented. Then the dynamic identification of source emitting characters and prediction of contaminant concentration were realized using combined implicit and explicit Kalman filter. The identifiable zone of different sensor placements was analyzed, and the best scheme of sensor placement had been found. Simulation results prove that the sensitivity analysis algorithm and combined implicit and explicit Kalman filter can realize the dynamic identification of source emitting characters and prediction of contaminant concentration speedily and accurately.
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