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- W1997956008 abstract "Data fusion and sensor management approaches have largely been implemented with centralized and hierarchical architectures. Numerical and statistical methods are the most common data fusion methods found in these systems. Given the proliferation and low cost of processing power, there is now an emphasis on designing distributed and decentralized systems. These systems use analytical/quantitative techniques or qualitative reasoning methods for date fusion.Based on other work by the author, a sensor may be treated as a highly autonomous (decentralized) unit. Each highly autonomous sensor (HAS) is capable of extracting qualitative behaviours from its data. For example, it detects spikes, disturbances, noise levels, off-limit excursions, step changes, drift, and other typical measured trends. In this context, this paper describes a distributed sensor fusion paradigm and theory where each sensor in the system is a HAS. Hence, given the reach qualitative information from each HAS, a paradigm and formal definitions are given so that sensors and processes can reason and make decisions at the qualitative level. This approach to sensor fusion makes it possible the implementation of intuitive (effective) methods to monitor, diagnose, and compensate processes/systems and their sensors. This paradigm facilitates a balanced distribution of intelligence (code and/or hardware) to the sensor level, the process/system level, and a higher controller level. The primary application of interest is in intelligent health management of rocket engine test stands." @default.
- W1997956008 created "2016-06-24" @default.
- W1997956008 creator A5052141105 @default.
- W1997956008 date "2001-07-08" @default.
- W1997956008 modified "2023-10-01" @default.
- W1997956008 title "Facility monitoring - A qualitative theory for sensor fusion" @default.
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- W1997956008 doi "https://doi.org/10.2514/6.2001-3765" @default.
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