Slow feature analysis for monitoring and diagnosis of control performance
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- 作者：Chao Shanga ; b ; shangc07@mails.tsinghua.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Biao Huangb ; biao.huang@ualberta.ca" class="auth_mail" title="E-mail the corresponding author ; Fan Yanga ; yangfan@tsinghua.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Dexian Huanga ; huangdx@tsinghua.edu.cn" class="auth_mail" title="E-mail the corresponding author
- 关键词：Data-driven modeling ; Control performance monitoring ; Contribution plot ; Fault diagnosis ; Industrial alarm system
- 刊名：Journal of Process Control
- 出版年：2016
- 出版时间：March 2016
- 年：2016
- 卷：39
- 期：Complete
- 页码：21-34
- 全文大小：5273 K
文摘
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A data-driven approach to control performance monitoring and diagnosis is proposed.
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Temporal variations of processes implicitly reveal control performance.
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Nominal temporal dynamics is statistically modeled by slow feature analysis.
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Control charts are established based on temporal variations of slow features.
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Contribution plots are adopted for diagnosis of control performance.