Statistical Process Monitoring Based on Ensemble Structure Analysis  

作　　者：Likang Shi Chudong Tong Ting Lan Xuhua Shi 

机构地区：[1]Faculty of Electrical Engineering and Computer Science,Ningbo University,Ningbo 315211,China

出　　处：《IEEE/CAA Journal of Automatica Sinica》2024年第8期1889-1891,共3页自动化学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(61503204);the Natural Science Foundation of Zhejiang Province(Y16F030001);the Nature Science Foundation of Ningbo City(2016A610092).

摘　　要：Dear Editor,This letter presents a novel process monitoring model based on ensemble structure analysis(ESA).The ESA model takes advantage of principal component analysis(PCA),locality preserving projections(LPP),and multi-manifold projections(MMP)models,and then combines the multiple solutions within an ensemble result through Bayesian inference.In the developed ESA model,different structure features of the given dataset are taken into account simultaneously,the suitability and reliability of the ESA-based monitoring model are then illustrated through comparison.Introduction:The requirement for ensuring safe operation and improving process efficiency has led to increased research activity in the field of process monitoring.

关 键 词：ENSEMBLE PRESERVING LETTER 

分 类 号：O213[理学—概率论与数理统计]