信息与控制2017，Vol.46Issue(6)：671-676,6.DOI:10.13976/j.cnki.xk.2017.0671
基于动态全主成分回归质量相关的故障检测
Quality-related Fault Detection Approach Based on Dynamic Total Principal Component Regression Component Regression
摘要
Abstract
On the basis of the structure of auto-regressive moving average exogenous (ARMAX),we propose a dynamic total principal component regression (DT-PCR) method for dynamic performance of quality-related fault detection.We form the input augmented matrix in the method based on the delay value of the input.The augmented matrix is divided into two orthogonal parts,namely,quality-related and quality-unrelated.We design a simple fault detection strategy based on statistics in two subspaces that correspond to the two parts.The output prediction accuracy of DT-PCR is better than that of former methods.The prediction and fault detection performance of the proposed approach are proved by a numerical example and the Tennessee Eastman process through a comparison by using total partial least squares (TPLS).关键词
故障检测/输出预测/质量相关/动态系统Key words
fault detection/output prediction/quality-related/dynamic system分类
信息技术与安全科学引用本文复制引用
王光,孙程远,尹珅..基于动态全主成分回归质量相关的故障检测[J].信息与控制,2017,46(6):671-676,6.基金项目
国家自然科学青年基金资助项目(61503039,61503040) （61503039,61503040）
