华东理工大学学报（自然科学版）2017，Vol.43Issue(2)：260-265,6.DOI:10.14135/j.cnki.1006-3080.2017.02.017
基于局部特征的多模态过程监控方法
Multimode Process Monitoring Based on Local Feature
摘要
Abstract
Every mode has different features in a multimode process,so the local features of modal data can be more effectively than global features for the reasonable characterization of chemical process.In order to use the local characteristics of multimodal data,this paper proposes a local feature based multiple model method,called,Local Feature-based Multiple Model (LFMM),for process monitoring.Firstly,the sequential information between data and the modal data features is utilized in the offline phase and the coefficient of variance of data in different time windows is applied for the clustering of the training data of multimode process.In the latter model phase,LOF algorithm is utilized to compute the local data density in their mode data set.In the online phase,by taking the local data density as statistic character,a new global probability index is established as a monitoring statistic for multimode process monitoring.Finally,TE process is adopted to verify the effectiveness of the proposed method.关键词
多模态/局部特征/多模型/过程监控/时序信息Key words
multimode/local feature/multiple model/process monitoring/sequential information分类
信息技术与安全科学引用本文复制引用
许圆圆,杨健,谭帅,侍洪波..基于局部特征的多模态过程监控方法[J].华东理工大学学报（自然科学版）,2017,43(2):260-265,6.基金项目
国家自然科学基金(61374140) （61374140）
国家自然科学基金青年基金(61403072) （61403072）
