摘要
针对工业过程的动态和多模态特性,提出一种基于局部近邻标准化(LNS)和动态主元分析(DPCA)相结合的故障检测方法(LNS-DPCA)。首先,在训练数据集中寻找样本的K近邻集;然后,应用K近邻集的均值与标准差对当前样本进行标准化处理;最后,在新的数据集中应用DPCA方法确定T^2和SPE控制限进行故障检测。LNS方法能够消除过程的多模态特征,使得标准化后数据近似服从多元高斯分布,且保持过程离群点偏离正常样本轨迹;而结合DPCA方法则能够提高对具有动态特性过程的监视性能。利用数值例子和青霉素发酵过程进行仿真,并将测试结果与主元分析法(PCA)、DPCA、K近邻故障检测(FD-KNN)等方法进行对比分析,验证了LNS-DPCA方法的有效性。
Aiming at the processes with dynamic and multimode characteristics,a fault detection strategy based on Local Neighbor Standardization(LNS)and Dynamic Principal Component Analysis(DPCA)was proposed.First,the K nearest neighbors set of each sample in training data set was found,then the mean and standard deviation of each variable were calculated.Next,the above mean and standard deviation were applied to standardize the current samples.At last,the traditional DPCA was applied in the new data set to determine the control limits of T 2 and SPE statistics respectively for fault detection.LNS can eliminate the multimode characteristic of a process and make the new data set follow a multivariate Gaussian distribution;meanwhile,the feature of a outlier deviating from normal trajectory can also be maintained.LNS-DPCA can reduce the impact of multimode structure and improve the detectability of fault in processes with dynamic property.The efficiency of the proposed strategy was implemented in a simulated case and the penicillin fermentation process.The experimental results indicate that the proposed method outperforms the Principal Component Analysis(PCA),DPCA and Fault Detection based on K Nearest Neighbors(FD-K NN).英文关键词
作者
张成
郭青秀
冯立伟
李元
ZHANG Cheng;GUO Qingxiu;FENG Liwei;LI Yuan(Department of Science,Shenyang University of Chemical Technology,Shenyang Liaoning 110142,China;Research Center for Technical Process Fault Diagnosis and Safety,Shenyang University of Chemical Technology,Shenyang Liaoning 110142,China)
出处
《计算机应用》
CSCD
北大核心
2018年第9期2730-2734,共5页
journal of Computer Applications
基金
国家自然科学基金资助项目(61490701
61673279)
辽宁省自然科学基金资助项目(2015020164)
辽宁省教育厅基金资助一般项目(L2015432)~~
关键词
局部近邻标准化
动态主元分析
多模态
青霉素发酵过程
故障检测
Local Neighbor Standardization(LNS)
Dynamic Principal Component Analysis(DPCA)
multimode
penicillin fermentation process
fault detection
