For a physical system whose operating state is monitored by various sensors, one of the crucial steps involved in fault monitoring and diagnosis process is to validate the sensor values. A sensor value can be validated by observing redundant measurement values. When numerous sensors are installed at different locations in a system and if there exist certain relationships among the measured parameters, the redundancies of the sensors can be viewed as embedded throughout the system. In this paper, a technique is proposed that can systematically explore such embedded redundancies of the sensors in a system and utilize them in quickly validating sensor values. The technique is based on causal relations and their interrelations within sensor redundancy graphs (SRG's) as defined in this paper. Any sensor in an SRG can potentially benefit from any other sensor involved in the same SRG in validation. A validity level is defined and used to express the strength of the validity of a sensor value as supported by varying degrees of evidence. The validation results also yield valuable clues to the systems' fault diagnosis knowledge-based systems on the occurrences of system faults and their locations.>
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S.C. Lee (1994) studied this question.
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