Nonlinear process monitoring using kernel nonnegative matrix factorization-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Nonlinear process monitoring using kernel nonnegative matrix factorization

Published:2017-09-10 Issue:2 Volume:96 Page:554-563
ISSN:0008-4034
Container-title:The Canadian Journal of Chemical Engineering
language:en
Short-container-title:Can. J. Chem. Eng.

Author:

Zhai Lirong¹²^ORCID,Zhang Yingwei¹³,Guan Shouping¹,Fu Yuanjian¹,Feng Lin¹

Affiliation:

1. College of Information Science and Engineering; Northeastern University; Shenyang Liaoning 110819 P. R. China

2. College of Light Industry; Liaoning University; Shenyang Liaoning 110036 P. R. China

3. State Key Laboratory of Synthetical Automation of Process Industry; Northeastern University; Shenyang Liaoning 110819 P. R. China

Funder

China's National 973 program

NSF of China

Publisher

Wiley

Subject

General Chemical Engineering

Reference39 articles.

1. Subspace approach to multidimensional fault identification and reconstruction

2. Joint diagnosis of process and sensor faults using principal component analysis

3. Statistical process monitoring using improved PCA with optimized sensor locations

4. Monitoring batch processes using multiway principal component analysis

5. Use of principal component analysis for sensor fault identification

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A novel fault detection scheme for a nonlinear dynamic process based on generalized non‐negative matrix projection‐maximum mean discrepancy: Application on the DAMADICS benchmark process;The Canadian Journal of Chemical Engineering;2023-11-07

2. Anomaly detection of train wheels utilizing short-time Fourier transform and unsupervised learning algorithms;Engineering Applications of Artificial Intelligence;2023-06

3. Structured Joint Sparse Orthogonal Nonnegative Matrix Factorization for Fault Detection;IEEE Transactions on Instrumentation and Measurement;2023

4. Fault Detection and Isolation of Industrial Fermentation Process Based on Semi-supervised Convex Nonnegative Matrix Factorizations;JOURNAL OF CHEMICAL ENGINEERING OF JAPAN;2022-12-20

5. A time‐varying process monitoring approach based on iterative‐updated semi‐supervised nonnegative matrix factorizations;The Canadian Journal of Chemical Engineering;2022-11-09

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3