Process Equipment Diagnosis & Prognosis


High degree of reliability is required in variety of automated systems, which requires a health monitoring system capable of detecting any equipment faults as they occur and identifying the faulty components. Component fault detection has been the subject of numerous studies in the past few decades. Fault diagnosis of system components, in particular, can lead to greater plant availability, extended plant life, higher quality products, and smoother system operations. Under MDA funding, we have developed a new system for data-based, online, real-time monitoring of equipment health state and predicting imminent failures. It is developed based on a new, general, state-space based approach for slower parameter tracking in dynamical systems. Our technology is applicable to systems where the parameters drift at a slower time rate than the observable dynamics measured by sensors. 



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