多采样率主元分析的过程故障检测

上海交通大学学报（自然版） ›› 2015, Vol. 49 ›› Issue (06): 762-767.

• 自动化技术、计算机技术 • 上一篇下一篇

多采样率主元分析的过程故障检测

丛亚，葛志强，宋执环

(浙江大学工业控制研究所, 杭州 310027)

收稿日期:2014-12-05 出版日期:2015-06-29 发布日期:2015-06-29
基金资助:
国家自然科学基金资助项目（61273167）

Multi-Rate Principle Component Analysis for Process Monitoring

CONG Ya,GE Zhiqiang,SONG Zhihuan

(Institute of Industrial Process Control, Zhejiang University, Hangzhou 310027, China)

Received:2014-12-05 Online:2015-06-29 Published:2015-06-29

摘要/Abstract

摘要：

摘要：针对多采样率过程监测问题，提出了一种基于多采样率主元分析的故障检测方法.该方法构建了一种重新采样机制，直接利用多采样率数据计算模型中的协方差矩阵，充分利用了样本中的大量不完整数据信息，减小了多采样率数据带来的偏差，给出了离线建模和在线故障检测算法.分别在数值平台和Tennessee Eastman (TE)工业平台进行了仿真分析.仿真结果表明，所提出的方法更适合多采样率过程的故障检测，效果良好.

关键词: 多采样率过程监测, 主元分析, 故障检测

Abstract:

Abstract： To monitor multi-rate processes, a multi-rate principle components analysis algorithm was proposed in which the covariance matrix was calculated using the incomplete multi-rate data samples. To avoid the bias of the covariance matrix, the resampling method was adopted. Besides, the offline modeling strategy and online monitoring strategy were proposed. Then two case studies on both numerical and Tennessee Eastman process (TEP) simulation was given to prove the effectiveness of the proposed algorithm compared to other methods. The result shows that the proposed method has a better performance in multirate process monitoring.

Key words: multi-rate process monitoring, principle components analysis, fault detection

中图分类号:

TP 277

丛亚，葛志强，宋执环. 多采样率主元分析的过程故障检测[J]. 上海交通大学学报（自然版）, 2015, 49(06): 762-767.

CONG Ya,GE Zhiqiang,SONG Zhihuan. Multi-Rate Principle Component Analysis for Process Monitoring[J]. Journal of Shanghai Jiaotong University, 2015, 49(06): 762-767.

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多采样率主元分析的过程故障检测

Multi-Rate Principle Component Analysis for Process Monitoring

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