Fault Monitoring of Batch Process Based on Moving Window SVDD

XIE Yanhong; SUN Chengao; LI Yuan

doi:10.13976/j.cnki.xk.2015.0531

Volume 44 Issue 5

Oct. 2015

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INFORMATION AND CONTROL > 2015 > 44(5): 531-537. > DOI: 10.13976/j.cnki.xk.2015.0531 CSTR: 32166.14.xk.2015.0531

XIE Yanhong, SUN Chengao, LI Yuan. Fault Monitoring of Batch Process Based on Moving Window SVDD[J]. INFORMATION AND CONTROL, 2015, 44(5): 531-537. DOI: 10.13976/j.cnki.xk.2015.0531

Citation:

XIE Yanhong, SUN Chengao, LI Yuan. Fault Monitoring of Batch Process Based on Moving Window SVDD[J]. INFORMATION AND CONTROL, 2015, 44(5): 531-537. DOI: 10.13976/j.cnki.xk.2015.0531

Citation:

XIE Yanhong, SUN Chengao, LI Yuan. Fault Monitoring of Batch Process Based on Moving Window SVDD[J]. INFORMATION AND CONTROL, 2015, 44(5): 531-537. DOI: 10.13976/j.cnki.xk.2015.0531

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Fault Monitoring of Batch Process Based on Moving Window SVDD

1.
Department of Science, Shenyang University of Chemical Technology, Shenyang 110142, China
2.
College of Information Engineering, Shenyang University of Chemical Technology, Shenyang 110142, China

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Received Date: September 22, 2014
Revised Date: January 21, 2015
Published Date: October 19, 2015

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Abstract

Abstract

Traditional support vector data description (SVDD) methods fail to guarantee real-time monitoring online in relation to dynamical characteristics of batch process data. This study proposes a moving-window-based SVDD method to monitor faults online in real-time. By selecting a moving window with an appropriate size, and gradually updating the current sub-data space, sub-models of SVDD are constructed, thereby executing fault monitoring online. The proposed method not only solves the adverse effects of non-Gaussian and nonlinearity, but also considers dynamic characteristics of batch process data and improves the timeliness and accuracy of batch processes monitoring. Finally, a numerical example and industrial cases are presented to verify effectiveness of the proposed method.
- batch process,
- SVDD (support vector data description),
- moving window,
- process monitoring

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