化工学报Issue(11)：4546-4554,9.DOI:10.11949/j.issn.0438-1157.20150546
基于分布式ICA-PCA模型的工业过程故障监测
Fault monitoring of industrial process based on distributed ICA-PCA model
摘要
Abstract
A fault monitoring method based on distributed independent component analysis-principal component analysis (ICA-PCA) model is proposed, which is suitable for complex industrial process that cannot be divided into several sub-blocks through an automatic way and has non-Gaussian information. Firstly, an initial PCA decomposition is carried out upon the variables of the whole process. By constructing sub-blocks through different directions of PCA principal components, the original feature space can be automatically divided into several sub-feature spaces. In addition, a two step extractions of the ICA-PCA information are carried on upon all sub-blocks in order to extract both Gaussian and non-Gaussian information, establishing the new statistics and their statistic limits. Finally, the simulation of TE process shows that the proposed fault detection model is efficient and feasible.关键词
复杂工业过程/自动划分子块/非高斯/ICA-PCA/故障监测Key words
complex industrial process/automatic partitioning sub-blocks/non-Gaussian/ICA-PCA/fault monitoring分类
信息技术与安全科学引用本文复制引用
衷路生,何东,龚锦红,张永贤..基于分布式ICA-PCA模型的工业过程故障监测[J].化工学报,2015,(11):4546-4554,9.基金项目
国家自然科学基金项目（61263010，60904049）；江西省自然科学基金项目（20114BAB211014）；江西省教育厅项目（GJJ14399）。@@@@supported by the National Natural Science Foundation of China (61263010,60904049), the Natural Science Foundation of Jiangxi Province (20114BAB211014) and the Project of Education Department of Jiangxi Province (GJJ14399) （61263010,60904049）
