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基于变量分组DTW-MCVA的不等长间歇过程故障检测方法
引用本文:于蕾,邓晓刚,曹玉苹,路凯琪.基于变量分组DTW-MCVA的不等长间歇过程故障检测方法[J].化工学报,2019,70(9):3441-3448.
作者姓名:于蕾  邓晓刚  曹玉苹  路凯琪
作者单位:中国石油大学(华东)信息与控制工程学院,山东 青岛 266580
基金项目:山东省重点研发计划项目(2018GGX101025);中央高校基本科研业务费专项资金(17CX02054);国家自然科学基金项目(61403418);山东省自然科学基金项目(ZR2014FL016);山东省高等学校科技计划项目(J18KA359)
摘    要:针对不等长间歇过程监控中批次数据同步化未能充分挖掘局部信息的问题,提出一种基于变量分组DTW-MCVA(VGDTW-CVA)的不等长间歇过程故障检测方法。首先,利用互信息矩阵描述不等长间歇过程测量变量之间的相关性,并基于互信息矩阵进行变量分组。然后利用DTW算法对各个变量组分别进行同步化,并将同步化后的变量组整合为完整的三维数据集。最后,利用MCVA方法建立动态监控模型实现对间歇生产过程的在线监控。盘尼西林发酵过程的仿真结果表明,VGDTW-MCVA能够比基本的DTW-MCVA方法更好地监控间歇过程故障。

关 键 词:不等长间歇过程  局部信息挖掘  变量分组  互信息  动态时间规整  多向典型变量分析  故障检测  
收稿时间:2019-04-03
修稿时间:2019-06-10

Fault detection method of unequal-length batch process based on VGDTW-MCVA
Lei YU,Xiaogang DENG,Yuping CAO,Kaiqi LU.Fault detection method of unequal-length batch process based on VGDTW-MCVA[J].Journal of Chemical Industry and Engineering(China),2019,70(9):3441-3448.
Authors:Lei YU  Xiaogang DENG  Yuping CAO  Kaiqi LU
Affiliation:Information and Control Engineering College, China University of Petroleum, Qingdao 266580, Shandong, China
Abstract:Aiming at the problem that batch data synchronization in unequal-length batch process monitoring fails to fully exploit local information, this paper proposes a variable grouping dynamic time warping-multiway canonical variate analysis (VGDTW-CVA) algorithm for unequal-length batch process fault detection. First, the mutual information matrix is used to describe the correlation between variables of unequal-length batch process, and all the variables are divided into serval groups based on mutual information matrix. Then use the DTW algorithm to synchronize each variable group separately, and integrate the synchronized variable groups into a complete 3D data set. Finally, MCVA method is utilized to establish dynamic monitoring model for online monitoring of batch production process. The simulation results on the penicillin simulation system show that the VGDTW-MCVA has better monitoring effect for the unequal-length batch production process.
Keywords:unequal-length batch process  local information exploiting  variable grouping  mutual information  dynamic time warping  canonical variate analysis  fault detection  
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