计算机应用与软件Issue(12)：84-86,3.DOI:10.3969/j.issn.1000-386x.2013.12.022
多线性主元分析的应用与研究
RESEARCH AND APPLICATION OF MULTILINEAR PRINCIPAL COMPONENT ANALYSIS
摘要
Abstract
In order to decrease the computation complexity and information loss ,in this paper we propose a new method to diagnose the in-termittent process fault with multilinear principal component analysis (multilinear PCA).First,we apply the multilinear PCA directly to the di-mension reduction of three-dimensional data of intermittent process and get the projection vectors with low dimensions .Then all the batches are projected onto the projection vectors to get the scoring vectors ,and we calculate the control limits of SPE statistics indexes and build the multi-linear PCA model.Thirdly,we calculate the scoring vectors and SPE statistics indexes of the new batch ,and monitor the production operation according to whether the statistical index exceeding the control limit .Finally,we adopt SPE contribution chart to diagnose the fault cause when the faults are detected.Simulation examples show that compared with multiway principal component analysis (MPCA),the multilinear PCA improves the accuracy of process performance monitoring and fault diagnosis ,and finds the abnormal process earlier .关键词
间歇过程故障诊断/多向主元分析/多线性主元分析Key words
Intermittent process fault diagnosis/Multiway principal component analysis/Multilinear principal component analysis分类
信息技术与安全科学引用本文复制引用
孔晓光,郭金玉,林爱军..多线性主元分析的应用与研究[J].计算机应用与软件,2013,(12):84-86,3.基金项目
国家自然科学基金项目（61174119）。孔晓光，讲师，主研领域自动化生产过程性能监视和故障诊断。 （）
