Research on Catenary condition maintenance strategy based on multi-objective optimization

Xuan Chen; Haigang Zhang; Piao Liu; Decheng Zhao

doi:10.1117/12.2628493

22 April 2022 Research on Catenary condition maintenance strategy based on multi-objective optimization

Xuan Chen, Haigang Zhang, Piao Liu, Decheng Zhao

Proceedings Volume 12174, International Conference on Internet of Things and Machine Learning (IoTML 2021); 121740D (2022) https://doi.org/10.1117/12.2628493
Event: International Conference on Internet of Things and Machine Learning (IoTML 2021), 2021, Shanghai, China

Abstract

On the basis of Petri net analysis of contact network system reliability, the state maintenance theory is applied to contact network system operation analysis, the reliability of contact network in each maintenance cycle is quantitatively calculated, the optimization model of contact network maintenance plan based on "reliability-maintenance cost" is established, and the multi-objective particle swarm optimization algorithm (MMOPSO) with multi-search strategy is used to optimize it. The Pareto optimal solution set is obtained by model validation in MATLAB. By making the contact network system run reliably and safely while reducing maintenance costs, it can provide reference and reference for the actual maintenance work.

Citation Download Citation

Xuan Chen, Haigang Zhang, Piao Liu, and Decheng Zhao "Research on Catenary condition maintenance strategy based on multi-objective optimization", Proc. SPIE 12174, International Conference on Internet of Things and Machine Learning (IoTML 2021), 121740D (22 April 2022); https://doi.org/10.1117/12.2628493

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