文献类型：期刊文献

中文题名：Isolation of Whole-plant Multiple Oscillations via Non-negative Spectral Decompositio

英文题名：Isolation of Whole-plant Multiple Oscillations via Non-negative Spectral Decompositio

作者：夏春明[1];郑建荣[1];John Howell[2]

机构：[1]Centre for Mcchatronics Engineering, East China University of Science ＆ Technology, Shanghai 200237, China;[2]Department of Mechanical Engineering, University of Glasgow, Glasgow G12 8QQ, UK

年份：2007

卷号：15

期号：3

起止页码：353

中文期刊名：Chinese Journal of Chemical Engineering

外文期刊名：中国化学工程学报（英文版）

收录：CSTPCD;;Scopus;CSCD:【CSCD2011_2012】；

基金：Supported by the Scientific Research Foundation for the Returned Overseas Chinese Scholars,State Education Ministry.

语种：中文

中文关键词：process monitoring; multiple oscillations; non-negative matrix factorization; sparse; spectral analysis;fault isolation

外文关键词：非负频谱分解;厂级多重振荡源;分离;光谱分析

摘要：Constrained spectral non-negative matrix factorization(NMF)analysis of perturbed oscillatory process control loop variable data is performed for the isolation of multiple plant-wide oscillatory sources.The technique is described and demonstrated by analyzing data from both simulated and real plant data of a chemical process plant. Results show that the proposed approach can map multiple oscillatory sources onto the most appropriate control loops,and has superior performance in terms of reconstruction accuracy and intuitive understanding compared with spectral independent component analysis(ICA).
Constrained spectral non-negative matrix factorization（NMF）analysis of perturbed oscillatory process control loop variable data is performed for the isolation of multiple plant-wide oscillatory sources.The technique is described and demonstrated by analyzing data from both simulated and real plant data of a chemical process plant. Results show that the proposed approach can map multiple oscillatory sources onto the most appropriate control loops,and has superior performance in terms of reconstruction accuracy and intuitive understanding compared with spectral independent component analysis（ICA）.