1 March 1994 Application of a multidomain diagnostic expert system in a controlled ecological life support system
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Abstract
A controlled ecological life support system (CELSS) is a critical technology for the Space Exploration Initiative. To reduce required manpower and increase CELSS reliability, an automated control system is being developed for CELSS. One part of the control system being investigated is the use of an expert system to troubleshoot mechanical failures in the biomass production chamber (BPC) within a CELSS at Kennedy Space Center, Florida. An expert system such as this would provide mission crew members with instructions and advice on how to minimize the impact of mechanical failures on the crop(s) being raised in the BPC. The nutrient delivery system (NDS) is one of the most critical subsystems of the BPC and is representative of the other BPC subsystems. The NDS is the primary focus of the expert system that was developed. The biomass production chamber operations assistant fact base was developed using several experts from the fields of mechanical engineering and biology. This combination of expertise provides the BPC Operations Assistant with a knowledge base that can assess the criticality of a mechanical failure, identify the short and long term effects on the resident crop(s), and provide instructions for bringing failed mechanical sub-systems back on-line. The BPC Operations Assistant can also help in the decision process of a failure scenario as to when it might be more cost effective to replant a crop versus continuing growing, or immediate harvesting of the crop(s). The experience gained from the research and development of the BPC Operations Assistant provides key insights into knowledge-based monitoring and diagnostic systems that will be required for the manned exploration of space in the future.
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Barry R. Clinger, Barry R. Clinger, Alfred L. Damiano, Alfred L. Damiano, "Application of a multidomain diagnostic expert system in a controlled ecological life support system", Proc. SPIE 2244, Knowledge-Based Artificial Intelligence Systems in Aerospace and Industry, (1 March 1994); doi: 10.1117/12.169397; https://doi.org/10.1117/12.169397
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