Integrated model-based reasoning/expert system diagnosis for rotating machinery

Abstract

A diagnostic system and method for rotating machinery having mechanical problems combine AI-based interpretive reasoning with rotordynamic-based modeling and numerical optimization. A vibration response in the machinery to be diagnosed is first measured by machine sensors, and this measured response is used in a rule-based expert system to determine a probable cause of the machinery's mechanical problem. An appropriate finite element analytical model of the machinery is generated based on the probable cause. An optimizer computes the predicted response from the analytical model and compares it with the measured response. The model is automatically refined, guided by the expert system and numerical optimization, to match the predicted response with the measured response. The modifications to the model necessary to duplicate the measured response of the defective machinery are then indicative of the defects.

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