Air-quality monitoring and detection of air contamination in an enclosed environment

Abstract

We report on the development of an air-quality monitoring and early detection system for an enclosed environment with specific emphasis on manned spacecraft. The proposed monitoring approach is based on a distributed parameter model of contaminant dispersion and real-time contaminant concentration measurements. Kalman filtering is identified as a suitable method for generating on-line estimation of the spatial contamination profile, and an implicit Kalman filtering algorithm is shown to be preferable for rear-time implementation. The identification of the contaminant concentration profile allows for a straightforward solution of the early detection of an air contamination event and provides information that enables potential automatic diagnosis of an unknown contamination source.