Importance

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Abstract

Determined results of which measured data of a plant is normal/abnormal are mapped to a plant model in an abstract function level hierarchically represented with flow structures of mass/energy and goals to be accomplished by the respective flow structures so as to detect a failure propagation network. In the failure propagation network, a flow structure at the lowest hierarchical level of a network with a top goal of the highest priority is selected as an object to be diagnosed first. In other words, flow structures that are functionally important and close to the origin of anomaly are preferentially diagnosed. The diagnosis for flow structures detects abnormal elements through hypothesis and test. The abnormal element are evaluated with respective mass/energy balances or the like. With respect to the evaluated result, the origin of failure is inferred based on the rule of experience. When the abnormal element has a detailed flow structure, it is diagnosed. Thus, an abnormal position can be detected in more detail.

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First Claim