RPLS based adaptive statistical quality monitoring of rubber mixing process

宋凯 王海清 李平

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RPLS based adaptive statistical quality monitoring of rubber mixing process

更新时间：2025-12-10

- RPLS based adaptive statistical quality monitoring of rubber mixing process
- CIESC Journal Issue 2, (2007)
- 作者机构：
  
  天津大学化工学院过程装备与控制工程系
- 作者简介：
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- Online First：05 February 2007，
  
  Published：05 February 2007
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宋凯王海清李平. RPLS based adaptive statistical quality monitoring of rubber mixing process[J]. CIESC Journal, 2007, (2).
DOI：

宋凯王海清李平. RPLS based adaptive statistical quality monitoring of rubber mixing process[J]. CIESC Journal, 2007, (2). DOI：

摘要

提出一种新的基于递推部分最小二乘（RPLS）算法的自适应在线质量监控策略。利用隐变量选择算法，根据实时采集的现场数据，在不增加计算和存储容量的基础上递推更新RPLS过程监测模型，进而更新Qα控制限，从而使RPLS自适应质量监控系统具有强时变跟踪特性，能够有效克服传统监测算法Qα无法反映系统时变性的缺点，大大降低了监控系统的误报率和漏报率，提高监控系统性能。并根据橡胶混炼过程特点，将此方法运用于该时变间歇过程质量监控中，取得了满意效果。

Abstract

An adaptive recursive partial least squares(RPLS ) monitoring scheme is proposed to improve the time-variant tracking power of the statistical quality monitoring (SQM) systemsWhen new samples are obtained

this new method updates the monitoring model and the Q statistic control limit (Qα) on the basis of the improved RPLS algorithmsThus it could overcome the shortage of the traditional fixed SQM successfullyThe theoretical findings were fully supported by the application performed on the rubber mixing process in a large-scale tire plant in east ChinaIt was shown that the compounds quality is improved remarkably and the false alarm frequency was reduced significantly.

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