Abstract
This paper presents a fuzzy knowledge-based system for turbomachinery diagnosis. Given symptoms associated with a vibration problem, the system can identify and rank possible causes by performing incremental forward chaining. The diagnostic system incorporates an attribute weighting component to reflect the relative significance of conditional attributes, thereby allowing the system to produce more accurate diagnoses. The ability of this system to identify causes of typical vibration problems in rotating machinery is supported with tests on real cases.
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