摘要
本文针对多模态复杂过程的多变量、多工序、变量时变性以及模态转换时间不确定等多种特性,提出基于高斯混合模型的多模态过程监测算法;针对离线数据没有模态标签的问题,提出离线数据分类算法;针对在线数据无法对应模态类型的问题,提出在线数据模态识别算法.并在以上方法的基础上建立多模态过程监测模型,以连续退火机组为背景,利用实际生产过程数据验证了算法的有效性.
Considering the process high dimensionality, multi -operation, time -variant characteristics, and unknown mode duration, the article proposes the multiple mode monitoring algorithm based on the gaussian mixture model. It also proposes the offline data classification algorithm aiming at the problem that offline data has no modal tag. For online data to corresponding modal type of problem, online data mo- dal identification algorithm is put forward. And on the basis of the above methods establishing the model of multimodal process monitoring in continuous annealing line as the background, the effectiveness of the algorithm was validated by actual production data.
作者
张艳芬
谭帅
李彬彬
ZHANG Yah- fen, TAN Shuai, LI Bin -bin （1. Yingkou Vocational ＆ Technical College, Yingkou Liaoning 115000, China; 2. School of Information Science ＆ Engineering, Northeast University, Shenyang Liaoning 110004, China）
基金
中央高校基本科研专项资金（N120304004）
中国博士后科学基金（2013M530937）.
关键词
多模态过程
过程监测
模态识别
连续退火机组
multiple mode processes
process monitoring
mode identification
continuous annealing line
