Review of Multiscale Methods for Process Monitoring, With an Emphasis on Applications in Chemical Process Systems
Author:
Affiliation:
1. Department of Chemical Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Perak, Malaysia
2. School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough, U.K.
Funder
Universiti Teknologi PETRONAS
Yayasan Universiti Teknologi Petronas
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09766148.pdf?arnumber=9766148
Reference145 articles.
1. A Review on Fault Detection and Process Diagnostics in Industrial Processes
2. Review and Perspectives of Data-Driven Distributed Monitoring for Industrial Plant-Wide Processes
3. Bridging data-driven and model-based approaches for process fault diagnosis and health monitoring: A review of researches and future challenges;khaoula;Ann Rev Control,2016
4. Data-driven design of monitoring and diagnosis systems for dynamic processes: A review of subspace technique based schemes and some recent results
5. A Review on Basic Data-Driven Approaches for Industrial Process Monitoring
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