期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
Modeling and monitoring of nonlinear multi-mode processes based on similarity measure-KPCA 被引量:10
1
作者 WANG Xiao-gang HUANG Li-wei ZHANG Ying-wei 《Journal of Central South University》 SCIE EI CAS CSCD 2017年第3期665-674,共10页
A new modeling and monitoring approach for multi-mode processes is proposed.The method of similarity measure(SM) and kernel principal component analysis(KPCA) are integrated to construct SM-KPCA monitoring scheme,wher... A new modeling and monitoring approach for multi-mode processes is proposed.The method of similarity measure(SM) and kernel principal component analysis(KPCA) are integrated to construct SM-KPCA monitoring scheme,where SM method serves as the separation of common subspace and specific subspace.Compared with the traditional methods,the main contributions of this work are:1) SM consisted of two measures of distance and angle to accommodate process characters.The different monitoring effect involves putting on the different weight,which would simplify the monitoring model structure and enhance its reliability and robustness.2) The proposed method can be used to find faults by the common space and judge which mode the fault belongs to by the specific subspace.Results of algorithm analysis and fault detection experiments indicate the validity and practicability of the presented method. 展开更多
关键词 process monitoring kernel principal component analysis (KPCA) similarity measure subspace separation
在线阅读 下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部