基于多时段MPCA模型的间歇过程监测方法研究

Research on Multistage-based MPCA Modeling and Monitoring Method for Batch Processes

针对间歇过程的多时段特性,提出一种新的生产操作时段划分方法.该方法利用反映过程特性变化的主成分个数、负载矩阵以及主成分矩阵的变化实现间歇过程子时段的三步划分.根据各时间片主成分个数不同,对生产操作时段进行粗划分.为了更客观地反映负载矩阵以及主成分矩阵的相似性,提出了基于加权负载向量夹角余弦的负载矩阵相似度度量以及基于加权主成分欧氏距离的主成分矩阵相似度度量方法.以相似度最小原则,对时间片矩阵进行奖惩竞争聚类,进而实现了生产操作子时段的细划分.将基于改进时段划分方法的MPCA建模应用于注塑成型过程在线监测,实验结果验证了该方法的有效性.

A new operation stage separation method is proposed for the substage separation of multistage batch processes.Based on the changes in principle component number,loading matrixes,and principle component matrixes,which reveal evolvement of the underlying process behavior,a three-step substage separation method is realized.First,rough separation of operation substage is executed by the difference of principle component number.To reflect objectively the similarity of the loading matrixes and the similarity of the principle component matrixes,two improved similarity distances,based on weighted cosine of the angle between loading vectors and weighted Euclidean distances,are introduced respectively.According to the criterion of minimum similarity distances,time-slice matrixes are sorted using the rival penalized competitive learning algorithm to realize separation of operation substage more particularly for batch processes.The effectiveness of the proposed method is illustrated by applying it to the MPCA modeling and on-line monitoring of the injection mold process.