Treffer: A novel distributed fine-grained energy consumption monitoring for large-scale nonlinear dynamic industrial processes.

To accelerate the transition of large-scale industrial processes toward green and low-carbon directions, reducing energy consumption is a top priority, large-scale industrial processes are characterised by nonlinearity and dynamics, and there are coupling relationships between the cascaded sub-blocks, which pose challenges for energy consumption monitoring. We propose a distributed energy consumption monitoring framework for large-scale nonlinear dynamic industrial processes in this paper. First, Mutual Information is employed to assess the relationship between process variables and energy consumption metrics, selecting relevant variables for energy consumption monitoring. Second, an AutoEncoder (AE)-Long and Short-Term Memory network (LSTM)-minimum Redundancy-Maximum Relevance analysis (mRMR) monitoring model is constructed. For series-coupled sub-blocks, the parallel AE-LSTM method can extract nonlinear and dynamic features and fuse them to comprehensively capture the mechanism of the energy consumption changes, while the mRMR method is capable of reducing the impact of redundant information. Then, based on the deep features, statistics are constructed for each sub-block using Support Vector Data Description to complete the energy consumption monitoring and detect whether it exceeds the limit. Finally, the method is validated using actual data from the real hot strip mill process, demonstrating its ability to accurately and effectively monitor excessive energy consumption. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Volltext ist im Gastzugang nicht verfügbar. Login für vollen Zugriff.