Incipient fault detection for nonlinear processes based on dynamic multi-block probability related kernel principal component analysis-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Incipient fault detection for nonlinear processes based on dynamic multi-block probability related kernel principal component analysis

Published:2020-10 Issue: Volume:105 Page:210-220
ISSN:0019-0578
Container-title:ISA Transactions
language:en
Short-container-title:ISA Transactions

Author:

Cai Peipei,Deng Xiaogang

Funder

National Natural Science Foundation of China

Major Scientific and Technological Projects of CNPC

Research Fund for the Creative Research Team of Young Scholars at Universities in Shandong Province

Publisher

Elsevier BV

Subject

Applied Mathematics,Control and Systems Engineering,Electrical and Electronic Engineering,Computer Science Applications,Instrumentation

Reference43 articles.

1. Review on data-driven modeling and monitoring for plant-wide industrial process;Ge;Chemometr Intell Lab,2017

2. Data-based techniques focused on Modern industry: An overview;Yin;IEEE Trans Ind Electron,2015

3. Nonlinear process fault diagnosis based on serial principal component analysis;Deng;IEEE Trans Neural Netw Learn Syst,2018

4. Distributed partial least squares based residual generation for statistical process monitoring;Tong;J Process Control,2019

5. A cumulative canonical correlation analysis-based sensor precision degradation detection method;Chen;IEEE Trans Ind Electron,2019

Cited by 51 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. Incipient fault detection for dynamic processes with canonical variate residual statistics analysis;Chemometrics and Intelligent Laboratory Systems;2024-09

2. Wasserstein local slow feature analysis and its application to process monitoring;Measurement Science and Technology;2024-06-20

3. Industrial process fault diagnosis based on domain adaptive broad echo network;Journal of the Taiwan Institute of Chemical Engineers;2024-06

4. Dimensionality reducing Gaussian mixture‐based reconstruction for fault detection in multimode processes;The Canadian Journal of Chemical Engineering;2024-05-09

5. Distributed incipient fault detection with causality-based multi-perspective subblock partitioning for large-scale nonlinear processes;Process Safety and Environmental Protection;2024-05

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