化工学报Issue(12)：4866-4874,9.DOI:10.3969/j.issn.0438-1157.2014.12.030
基于贝叶斯推理的PKPCAM的非线性多模态过程故障检测与诊断方法
Fault detection and diagnosis for nonlinear and multimode processes using Bayesian inference based PKPCAM approach
摘要
Abstract
the sub-principal component analysis usingk-means clustering and the kernel principal component analysis, the feasibility and effectiveness by the proposed Bayesian inference based PKPCAM method for fault detection and diagnosis in nonlinear and multimode process was validated on Tennessee Eastman process.关键词
非线性多模态过程/概率核主元混合模型/贝叶斯推理/故障检测/故障诊断Key words
nonlinear and multimode process/probabilistic kernel principal component analysis mixture model/Bayesian inference/fault detection/fault diagnosis分类
信息技术与安全科学引用本文复制引用
卢春红,熊伟丽,顾晓峰..基于贝叶斯推理的PKPCAM的非线性多模态过程故障检测与诊断方法[J].化工学报,2014,(12):4866-4874,9.基金项目
中央高校基本科研业务费专项基金项目（JUDCF12027， JUSRP51323B）；江苏高校优势学科建设工程项目（PAPD）；江苏省普通高校研究生创新计划项目（CXLX12_0734）。@@@@supported by the Fundamental Research Funds for the Central Universities of Ministry of Education of China (JUDCF12027, JUSRP51323B) （JUDCF12027, JUSRP51323B）
