Energy-saving optimization of copper foil electrolysis process with high reliability based on partial multi-scale filtering
HUANG Da-jian
ZHANG Wen-an
GUI Wei-hua
Abstract：The insufficient accuracy of energy consumption modeling in the copper foil electrolysis process compromis-es the reliability of energy-saving optimization,posing significant challenges to existing optimization methods.To address this issue,particularly given the difficulty of further enhancing modeling accuracy,this study proposes a novel energy-saving optimization approach for copper foil electrolysis based on local multi-scale filtering and systematically analyzes its reliability.Firstly,to investigate the impact of modeling accuracy on energy consumption optimization,models with varying levels of accuracy are generated through a loop-judgment structure,which enables analysis of the underlying influ-ence mechanisms.Secondly,a reliability analysis method is developed based on the goodness-of-fit metrics from existing regression models,enabling a quantitative assessment of the reliability of energy-saving optimization.Additionally,an improved strategy employing local multi-scale filtering is introduced to mitigate the influence of prediction errors on the intelligent bionic optimization algorithm,thereby addressing reliability issues arising from modeling accuracy limitations;relevant theoretical derivations are also provided.Finally,an industrial experiment in a copper foil electrolysis enterprise demonstrates that the proposed method reduces the absolute error of energy consumption optimization from 4.29％to 1.53％,indicating that this approach can substantially enhance the reliability of intelligent bionic optimization algorithms even with lower model accuracy.
Keywords：electrolytic copper foilelectrolytic processenergy-saving optimizationmulti-scale filteringprocess reliability enhancement
Publication Date：2025-11-30
Online Publishing Date：2025-12-29(First online date of this platform, not the publication date of the document)
Pages：14( 2207-2220 )