Application of multi-step time series prediction for industrial equipment prognostic
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...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/201/ http://eprints.utem.edu.my/id/eprint/201/1/Prognosis-_ICOSIEEELangkawi.pdf |
| Summary: | 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. |
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