| 基于集成主成分分析的故障检测方法 |
| |
| 引用本文： | 邹凌伟,田学民.基于集成主成分分析的故障检测方法[J].青岛科技大学学报,2012(5):474-478. |
| |
| 作者姓名： | 邹凌伟 田学民 |
| |
| 作者单位： | 中国石油大学(华东)信息与控制工程学院 |
| |
| 基金项目： | 国家自然科学基金项目(51104175);山东省自然科学基金项目(ZR2011FM014) |
| |
| 摘 要： | 针对核主成分分析(KPCA)和主成分分析(PCA)的一些不足,提出一种基于集成主成分分析的故障检测方法。该方法将PCA与KPCA结合,利用KPCA描述过程的非线性信息并提取核主成分,再利用PCA对原始信息和核主成分一同提取线性主成分,通过构造统计量T2和SPE(或Q)进行故障检测。在TE(Tennessee-Eastman)过程上的仿真研究表明,本文提出的方法较PCA和KPCA有更高的故障检测精度。
|
| 关 键 词： | 故障检测 主成分分析 核主成分分析 特征提取 |
A Fault Detection Method Based on Integrated PCA |
| |
| ZOU Ling-wei,TIAN Xue-min.A Fault Detection Method Based on Integrated PCA[J].Journal of Qingdao University of Science and Technology:Natutral Science Edition,2012(5):474-478. |
| |
| Authors: | ZOU Ling-wei TIAN Xue-min |
| |
| Affiliation: | (College of Information and Control Engineering,China University of Petroleum,Qingdao 266580,China) |
| |
| Abstract: | A kind of fault detection method based on Integrated Principal Component Analysis is proposed for some weakness of KPCA and PCA.This method combines PCA and KPCA,firstly the nonlinear information of process is described and the kernel principal component is extracted by KPCA,and then combining the original information and kernel principal component as a whole extracted linear principal component by PCA,The T2 and Q statistics are constructed for fault detection.The simulation results on TE process show that the proposed method can detect process faults more accurate than traditional PCA and KPCA. |
| |
| Keywords: | fault detection principal component analysis kernel principal component analysis feature extraction |
| 本文献已被 CNKI 等数据库收录！ |
