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World Academy of Science, Engineering and Technology 29 2009 Faults Forecasting System

By Hanaa E. Sayed, Hossam A. Gabbar and Shigeji Miyazaki

Abstract

that utilizes statistical forecasting techniques in analyzing process variables data in order to forecast faults occurrences. FFS is proposing new idea in detecting faults. Current techniques used in faults detection are based on analyzing the current status of the system variables in order to check if the current status is fault or not. FFS is using forecasting techniques to predict future timing for faults before it happens. Proposed model is applying subset modeling strategy and Bayesian approach in order to decrease dimensionality of the process variables and improve faults forecasting accuracy. A practical experiment, designed and implemented in Okayama University, Japan, is implemented, and the comparison shows that our proposed model is showing high forecasting accuracy an

Topics: Faults Detection, Forecasting techniques, Multivariate Analysis
Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.308.3924
Provided by: CiteSeerX
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