化工学报2019，Vol.70Issue(2)：581-589,9.DOI:10.11949/j.issn.0438⁃1157.20180855
一种新型的基于Levenshtein距离层次聚类的时序操作优化方法
New operation optimization method with time series based on Levenshtein distance hierarchical clustering
朱坚 1杨博 1王永健 1唐晓婕 1李宏光1
作者信息
- 1. 北京化工大学信息科学与技术学院,北京100029
- 折叠
摘要
Abstract
In the modern process industry process, DCS collects and stores a large amount of operational temporal data. If valuable operational experience and operational information can be extracted, the performance of the operating system can be greatly improved. However, operational experience is vague and cannot be quantified by value. Therefore, the operational data with time series is symbolized so that the operational experience is represented in a block form. And we propose a hierarchical clustering algorithm based on Levenshtein distance for time series. By clustering of historical operational data in the time series of variables, a variety of similar operating modes are obtained, and the process variables corresponding to the type of operation mode perform performance analysis to obtain and preserve the operational experience required in the actual work process, thereby guiding the process operation of production. In order to verify the proposed method, it is applied to the continuous multi component distillation operation process. The results show the effectiveness of the proposed method.关键词
时间序列/Levenshtein距离/层次聚类/操作优化/精馏Key words
time series/ Levenshtein distance/ hierarchical clustering/ operational optimization/ distillation分类
化学化工引用本文复制引用
朱坚,杨博,王永健,唐晓婕,李宏光..一种新型的基于Levenshtein距离层次聚类的时序操作优化方法[J].化工学报,2019,70(2):581-589,9.
