Data-driven monitoring of multimode continuous processes: A review
Abstract The Internet of Things benefits connectivity and functionality in industrial
environments, while Cloud Computing boosts computational capability. Hence, historical …
environments, while Cloud Computing boosts computational capability. Hence, historical …
Data mining and clustering in chemical process databases for monitoring and knowledge discovery
MC Thomas, W Zhu, JA Romagnoli - Journal of Process Control, 2018 - Elsevier
Modern chemical plants maintain large historical databases recording past sensor
measurements which advanced process monitoring techniques analyze to help plant …
measurements which advanced process monitoring techniques analyze to help plant …
Process analytical chemistry
J Workman Jr, B Lavine, R Chrisman… - Analytical chemistry, 2011 - ACS Publications
REVIEW an earlier paper of special significance is referenced. The key aspects of this
review include advances in measurement technologies that are applicable for at-line or …
review include advances in measurement technologies that are applicable for at-line or …
Modeling and performance monitoring of multivariate multimodal processes
A multimodal modeling and monitoring approach based on maximum likelihood principal
component analysis and a component‐wise identification of operating modes are presented …
component analysis and a component‐wise identification of operating modes are presented …
Data-driven fault diagnosis of chemical processes based on recurrence plots
H Ziaei-Halimejani, R Zarghami… - Industrial & …, 2021 - ACS Publications
A method for the detection and diagnosis of various faults in chemical processes based on
the combination of recurrence quantification analysis and unsupervised learning clustering …
the combination of recurrence quantification analysis and unsupervised learning clustering …
Monitoring for nonlinear multiple modes process based on LL-SVDD-MRDA
This study proposes an online monitoring technique for nonlinear multiple-mode problems
in industrial processes. The contributions of the proposed technique are summarized as …
in industrial processes. The contributions of the proposed technique are summarized as …
Designing dynamic alarm limits and adjusting manipulated variables for multivariate systems
Y Yu, J Wang, Z Ouyang - IEEE Transactions on Industrial …, 2019 - ieeexplore.ieee.org
Alarm systems are of paramount importance for safe and efficient operations of industrial
plants. This paper proposes a method to design dynamic alarm limits and adjust …
plants. This paper proposes a method to design dynamic alarm limits and adjust …
Fault detection for a class of industrial processes based on recursive multiple models
G Yong, W Xin, W Zhenlei - Neurocomputing, 2015 - Elsevier
Traditional multiple model process monitoring methods usually yield satisfactory results for
multi-mode processes under the assumption that the processes are time invariant. However …
multi-mode processes under the assumption that the processes are time invariant. However …
SOM-based visualization monitoring and fault diagnosis for chemical process
B Zhong, J Wang, H Wu, J Zhou… - 2016 Chinese Control …, 2016 - ieeexplore.ieee.org
Data-based fault diagnosis technology applied in chemical industry process has attracted
great attention, in which the effective methods for visualizing the process variation are still …
great attention, in which the effective methods for visualizing the process variation are still …
Multi-model quality prediction approach using fuzzy c-means clustering and support vector regression
M Zhang, Z Cai, W Cheng - Advances in Mechanical …, 2017 - journals.sagepub.com
Quality prediction of complex production process has increasingly attracted the interests of
manufacturers and researchers. Complex production process has the characteristics of sub …
manufacturers and researchers. Complex production process has the characteristics of sub …