化工学报 ›› 2017, Vol. 68 ›› Issue (5): 1961-1968.DOI: 10.11949/j.issn.0438-1157.20161501

• 过程系统工程 • 上一篇    下一篇

基于多阶段多向核熵成分分析的间歇过程故障检测方法

邓晓刚, 张琛琛, 王磊   

  1. 中国石油大学(华东)信息与控制工程学院, 山东 青岛 266580
  • 收稿日期:2016-10-26 修回日期:2017-01-17 出版日期:2017-05-05 发布日期:2017-05-05
  • 通讯作者: 邓晓刚
  • 基金资助:

    国家自然科学基金项目(61403418,61273160);山东省自然科学基金项目(ZR2014FL016);中央高校基本科研业务费专项资金(17CX02054)。

Fault detection in batch process by multistage multiway kernel entropy component analysis

DENG Xiaogang, ZHANG Chenchen, WANG Lei   

  1. College of Information and Control Engineering, China University of Petroleum, Qingdao 266580, Shandong, China
  • Received:2016-10-26 Revised:2017-01-17 Online:2017-05-05 Published:2017-05-05
  • Supported by:

    supported by the National Natural Science Foundation of China (61403418, 61273160), the Natural Science Foundation of Shandong Province (ZR2014FL016) and the Fundamental Research Funds for the Central Universities(17CX02054).

摘要:

针对间歇过程的非线性、多阶段特性,提出一种基于多阶段多向核熵成分分析(multistage-MKECA,MsMKECA)的故障检测方法。针对间歇过程的多阶段特性,建立一种时序核熵主元关联度的矩阵相似性阶段划分方法,实现对间歇生产过程的多阶段划分;针对传统批次展开方式在线监控需要预估批次未来值的缺陷,进一步引入一种批次-变量三维数据展开方式建立每个阶段的MKECA非线性统计模型,实现对间歇过程的分阶段监控。最后对盘尼西林发酵过程开展仿真研究,结果表明所提方法能够比传统MKECA方法更为快速地进行故障检测。

关键词: 故障检测, MKECA, 间歇过程, 多阶段

Abstract:

A fault detection method, i.e., multistage multiway kernel entropy component analysis (MsMKECA) was proposed on the basis of nonlinearity and multistage characteristics of batch process. First, in order to divide a batch process into multiple stages, a matrix similarity stage division method was constructed from correlation matrixes of the time-series kernel entropy components. Then, a batch-variable 3-D unfolding technique was introduced to build MKECA model in each stage and to monitor operations in each stage of the batch process, which overcame on-line monitoring impediments of requiring estimation on future values by conventional batch-wise unfolding technique. Simulation study on penicillin fermentation process showed that the proposed method can offer much faster fault detection than traditional MKECA.

Key words: fault detection, MKECA, batch process, multistage

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