一种基于DIOCVA的过程监控方法

曹玉苹; 黄琳哲; 田学民

doi:10.16383/j.aas.2015.c150058

一种基于DIOCVA的过程监控方法

doi: 10.16383/j.aas.2015.c150058

1.
中国石油大学(华东) 信息与控制工程学院青岛 266580;
2.
中国石油工程建设公司华东设计分公司青岛 266071

基金项目:

国家自然科学基金(61273160,61403418),山东省自然科学基金(ZR2014FL016),中央高校基本科研业务费专项资金(14CX02174A)资助

详细信息

作者简介:
黄琳哲中国石油工程建设公司华东设计分公司助理工程师. 主要研究方向为过程故障诊断.E-mail: joeyseraph@gmail.com

通讯作者:
曹玉苹中国石油大学(华东) 信息与控制工程学院讲师.主要研究方向为过程故障诊断与预测.本文通信作者.

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出版历程
- 收稿日期: 2015-01-30
- 修回日期: 2015-10-19
- 刊出日期: 2015-12-20

A Process Monitoring Method Using Dynamic Input-output Canonical Variate Analysis

1.
College of Information and Control Engineering, China University of Petroleum (East China), Qingdao 266580;
2.
East-China Design Branch, China Petroleum Engineering and Construction Corporation, Qingdao 266071

Funds:

Supported by National Natural Science Foundation of China (61273160, 61403418), Natural Science Foundation of Shandong Province (ZR2014FL016) and the Fundamental Research Funds for the Central Universities (14CX02174A)

摘要

摘要: 传统基于典型变量分析的过程监控方法无法判断故障是否影响产品质量.为此,本文提出一种基于动态输入输出典型变量分析(Dynamic input-output canonical variate analysis, DIOCVA)的过程监控方法.该方法利用典型变量分析提取数据之间的相关性,并进一步考虑方差信息和时序相关性, 将过程数据和质量数据映射到5个子空间:输入输出相关子空间,不相关输入主元子空间, 不相关输入残差子空间,不相关输出主元子空间和不相关输出残差子空间.所提方法能够精细区分影响质量的过程故障和不影响质量的过程故障.以Tennessee Eastman过程为例对所提方法的有效性进行了验证.
- 过程监控 /
- 质量监控 /
- 故障检测 /
- 典型变量分析 /
- 方差
Abstract: Traditional process monitoring methods based on canonical variate analysis cannot judge whether faults affect product quality or not. Therefore, a process monitoring method using dynamic input-output canonical variate analysis is proposed. Canonical variate analysis is used to analyze correlations between data. Furthermore, variance information and serial correlations in data are taken into account. Process data and quality data are projected to five subspaces: input-output correlated subspace, uncorrelated input principal subspace, uncorrelated input residual subspace, uncorrelated output principal subspace and uncorrelated output residual subspace. The proposed method can distinguish between the faults that affect product quality and those that do not. The effectiveness of the proposed method is demonstrated through a case study of the Tennessee Eastman process.
- Process monitoring /
- quality monitoring /
- fault detection /
- canonical variate analysis /
- variance

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参考文献(31)

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