Fault Detection of Tennessee Eastman Process using Kernel Dissimilarity Scale Based Singular Spectrum Analysis-Reference-Cited by-同舟云学术

Fault Detection of Tennessee Eastman Process using Kernel Dissimilarity Scale Based Singular Spectrum Analysis

Published:2019 Issue:29 Volume:52 Page:204-209
ISSN:2405-8963
Container-title:IFAC-PapersOnLine
language:en
Short-container-title:IFAC-PapersOnLine

Author:

Krishnannair S

Publisher

Elsevier BV

Subject

Control and Systems Engineering

Reference16 articles.

1. Multiscale Process Monitoring with Singular Spectrum Analysis;Aldrich;Proceedings of 12th IFAC Symposium on Automation in Mining and Metal Processing,2007

2. Multiscale PCA with applications to mul tivariate statistical process monitoring;Bakshi;AIChE Journal,1998

3. Extracting Qualitative Dynamics from Experimental Data;Broomhead;Physica D,1986

4. A plant-wide industrial process control problem;Downs;Computers and Chemical Engineering,1993

5. Predictive on-line monitoring of continuous processes;Chen;Journal of Process Control,1998

Cited by 6 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. Data-Driven Fault Classification in Large-Scale Industrial Processes Using Reduced Number of Process Variables;IEEE Transactions on Automation Science and Engineering;2023

2. Rolling bearing fault feature extraction via improved SSD and a singular-value energy autocorrelation coefficient spectrum;Measurement Science and Technology;2022-05-26

3. Machine Learning Algorithms Used in PSE Environments: A Didactic Approach and Critical Perspective;Industrial & Engineering Chemistry Research;2022-05-24

4. Improved Random Forest Algorithm Based on Decision Paths for Fault Diagnosis of Chemical Process with Incomplete Data;Sensors;2021-10-09

5. A fault detection method for FADS system based on interval-valued neutrosophic sets, belief rule base, and D-S evidence reasoning;Aerospace Science and Technology;2021-07