Importance

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Abstract

Machinery diagnostics and prognostics is an emerging engineering field that seeks to accurately determine the operational health of a machine without waiting for the machine to fail, performing maintenance that may not yet be required or, in the worst case, performing unnecessary maintenance that inadvertently causes other problems and hastens machine health deterioration. Accurate prediction of machine health (operability) enables operators to base machine maintenance on the machine's actual condition, in contrast to the common practice of time-based maintenance (e.g., perform maintenance every 100 hours). The 'just-in-time' methodology of the machine health monitoring system (MHMS) of the present invention translates into significant cost savings by providing early warning of impending failures and thus reducing unanticipated catastrophic machine failures through preventative maintenance techniques (but no more or no less than is required) while simultaneously keeping false alarm rates low. The MHMS couples proprietary analysis, modeling and pattern recognition techniques to provide accurate machine health predictions. The MHMS's combination of technologies provides accurate, easy-to-understand, early indication of potential problems, enabling efficient and timely repair. In addition, MHMS technology can continuously 'learn' from its own machine health monitoring experience, so that system accuracy and false alarm rate improve over time.

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First Claim