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Application of multi-step time series prediction for industrial equipment prognostic

Asmai, S. A. and Rosmiza, W. A. and Basari, A. S. H. and Hussin, B. (2011) Application of multi-step time series prediction for industrial equipment prognostic. In: 2011 IEEE Conference on Open Systems, 25-28 Sept 2011, Langkawi, Malaysia.

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Abstract

The use of prognostics is critically to be implemented in industrial. This paper presents an application of multi-step time series prediction to support industrial equipment prognostic. An artificial neural network technique with sliding window is considered for the multi-step prediction which is able to predict the series of future equipment condition. The structure of prognostic application is presented. The feasibility of this prediction application was demonstrated by applying real condition monitoring data of industrial equipment.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > Q Science (General)
Divisions: Faculty of Information and Communication Technology > Department of Industrial Computing
Depositing User: Dr. Abd. Samad Hasan Basari
Date Deposited: 06 Dec 2011 08:44
Last Modified: 28 May 2015 02:17
URI: http://eprints.utem.edu.my/id/eprint/201

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