摘要
为解决化工过程故障不易诊断的问题,提出一种基于模糊粗糙集特征提取和支持向量机的故障诊断方法.首先,利用模糊粗糙集对特征信息进行提取,构筑相应的故障特征集合;然后,将故障特征集合对应的样本输入到支持向量机分类器,实现对化工过程不同故障的识别.在TEP故障诊断中的应用表明了所提出方法的有效性.
In order to solve the problem about fault diagnosis for the chemical industry process, a fault diagnosis approach is proposed based on feature extraction by using fuzzy rough sets and support vector machines.The feature information is extracted by utilizing fuzzy rough sets and the fault diagnosis sets is built firstly. Then, the samples corresponding to the fault diagnosis sets are input into the SVM multi-classifier to realize the identification of different fault diagnosis in the chemical industry process. Finally, the effectiveness of the proposed method is illustrated through fault diagnosis in TEP chemical industry process.
出处
《控制与决策》
EI
CSCD
北大核心
2015年第2期353-356,共4页
Control and Decision
基金
国家自然科学基金项目(61173071)
国家公派高级研究学者及访问学者项目([2013]3018)
河南省高校创新人才支持计划项目(2012HASTIT011)
关键词
模糊粗糙集
支持向量机
TEP过程
故障诊断
fuzzy rough sets
support vector machines
TEP process
fault diagnosis
