Detection and Diagnosis of Air Contaminants in Spacecraft

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 converting the 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.