Intelligent System for the Detection and Diagnosis of Spacecraft Air Contaminants 981679
In this paper, we report on the development of an intelligent system for air quality monitoring and early detection and diagnosis of air contaminants. Optimal identification of contaminants is based upon the use of an Implicit Kalman Filter that uses both experimental data and a theoretical model to obtain optimal estimates. We have developed a three-dimensional unsteady-state model of contaminant transport, which uses a flow field generated numerically for the cabin using a finite element mesh. The optimal contaminant estimates are used as the basis for the detection of a contamination event. The algorithm is shown to distinguish between sensor faults and process faults.
Citation: Narayan, A. and Ramirez, W., "Intelligent System for the Detection and Diagnosis of Spacecraft Air Contaminants," SAE Technical Paper 981679, 1998, https://doi.org/10.4271/981679. Download Citation
Author(s):
Anand P. Narayan, W. Fred Ramirez
Affiliated:
University of Colorado at Boulder
Pages: 12
Event:
International Conference On Environmental Systems
ISSN:
0148-7191
e-ISSN:
2688-3627
Also in:
SAE 1998 Transactions - Journal of Aerospace-V107-1
Related Topics:
Scale models
Air pollution
Mathematical models
Spacecraft
Identification
Sensors and actuators
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