Artificial intelligence for smart energy systems in process industries

Qian, Feng; Bogle, David; Wang, Meihong; Pistikopoulos, Stratos; Yan, Jinyue

doi:10.1016/j.apenergy.2022.119684

Cited by 3 publications

(2 citation statements)

References 21 publications

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“…The papermaking process involves a large number of complex physical and chemical reactions [1], accompanied with characteristics of multi-variable, strong coupling and non-linear etc., hindering the intelligent development process of the papermaking industry [2]. At present, the process models and control systems, established by paper-making enterprises based on a new generation of information technology, have not yet solved the problem of "data silos" and cannot integrate material flow and energy flow information to achieve real-time monitoring and control of paper production, which affects the sustainability of the process dramatically.…”

Section: Introductionmentioning

confidence: 99%

Knowledge-data Collaborated Digital Twin Model of Papermaking Process

Liu,

Hong,

2024

Advanced Materials &Amp; Sustainable Manufacturing

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The structure of the drying section in papermaking process is complex and too compacted to install sensors. In order to monitor the parameters in dynamic and manage the process practically with virtual simulations instead of physical experiments, a digital twin-based process parameter visualization model is constructed in this study. Regarding to the possible missing data in the modeling framework, it is proposed to combine industrial data, and knowledge of mechanism with intelligent algorithms to fill in the missing parameters. Upon which, a digital twin-based data visualization model is established using CADSIM Plus simulation software. Both of the knowledge -based mechanism solution model and the random forest-based parametric prediction model perform well, and the predicted parameters can support the digital twin visualization model in CADSIM Plus. Visual modeling of surface condenser in the paper drying section was realized for example, and results show that the model is capable of monitoring the dynamic changes of parameters in real time, so as to support the optimization and decision making of papermaking process such as formation, drying, et al.

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Section: Introductionmentioning

confidence: 99%

Knowledge-data Collaborated Digital Twin Model of Papermaking Process

Liu,

Hong,

2024

Advanced Materials &Amp; Sustainable Manufacturing

View full text Add to dashboard Cite

show abstract

“…Modern automated industrial plants, as designed for Industry 4.0, have seen an ever-increasing need for process monitoring and health management across various operational modes, as well as reliable and efficient fault-tolerant control schemes [1] , [2] , [3] , [4] . Since fault detection and isolation (FDI) is a sub-field of process monitoring, the methods and techniques of FDI are also key to Industry 4.0 applications [5] .…”

Section: Introductionmentioning

confidence: 99%