计算机应用研究2018，Vol.35Issue(4)：1122-1125,1129,5.DOI:10.3969/j.issn.1001-3695.2018.04.035
基于局部Fisher判别分析的复杂化工过程故障诊断
Fault diagnosis of complex chemical process based on local Fisher discriminant analysis
摘要
Abstract
In order to improve the ability of fault detection and classification of complex chemical process,this paper proposed a fault diagnosis method of complex chemical process based on LFDA.Firstly,it calculated the local within-class and betweenclass scatter matrix of training data to find the projection direction.Secondly,it projected the training and test data into the projection vector for extracting the feature vector.Finally it calculated the Euclidean distances between feature vectors,and used KNN for classification.It applied the proposed method to the TE process.The monitoring results show that LFDA is better than FDA and KFDA,and LFDA method has the advantages of high accuracy and high sensitivity in classification and fault detection of different classes.关键词
复杂化工过程/故障诊断/Fisher判别分析/核Fisher判别分析/局部Fisher判别分析/KNN分类器Key words
complex chemical process/fault diagnosis/Fisher discriminant analysis/kernel Fisher discriminant analysis/local Fisher discriminant analysis/KNN classifier分类
信息技术与安全科学引用本文复制引用
郭金玉,韩建斌,李元,徐进学..基于局部Fisher判别分析的复杂化工过程故障诊断[J].计算机应用研究,2018,35(4):1122-1125,1129,5.基金项目
国家自然科学基金重大资助项目(61490701) （61490701）
国家自然科学基金资助项目(61673279) （61673279）
辽宁省教育厅重点实验室资助项目(LZ2015059) （LZ2015059）
辽宁省自然科学基金资助项目(201602584) （201602584）
辽宁省教育厅资助项目(L2016007,L2015432) （L2016007,L2015432）
