Unit operational pattern analysis and forecasting using EMD and SSA for industrial systems

Yang, Zhijing, Bingham, Chris, Ling, Wing-Kuen , Zhang, Yu, Gallimore, Michael and Stewart, Jill (2012) Unit operational pattern analysis and forecasting using EMD and SSA for industrial systems. In: 11th International Symposium, IDA 2012, October 25-27, 2012, Helsinki, Finland.

Full content URL: http://link.springer.com/chapter/10.1007%2F978-3-6...

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Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive


This paper studies operational pattern analysis and forecasting for industrial
systems. To analyze the global change pattern, a novel methodology for
extracting the underlying trends of signals is proposed, which is based on the
sum of chosen intrinsic mode functions (IMFs) obtained via empirical mode decomposition
(EMD). An adaptive strategy for the selection of the appropriate
IMFs to form the trend, is proposed. Then, to forecast the change of the trend,
Singular Spectrum Analysis (SSA) is applied. Results from experiment trials on
an industrial turbine system show that the proposed methodology provides a
convenient and effective mechanism for forecasting the trend of the operational
pattern. In so doing, it therefore has application to support flexible maintenance
scheduling, rather than the traditional use of calendar based maintenance.

Additional Information:11th International Symposium, IDA 2012, Helsinki, Finland, October 25-27, 2012, Proceedings
Keywords:Operational pattern analysis, trend extraction, empirical mode decomposition, signal forecasting, singular-spectrum analysis
Subjects:G Mathematical and Computer Sciences > G290 Operational Research not elsewhere classified
Divisions:College of Science > School of Engineering
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ID Code:12555
Deposited On:20 Nov 2013 12:08

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