Research on the Design and Modeling of a Railway Brake Shoe Replacement System Based on NFC and Intelligent Optimization Algorithms - Song, Chengyi; Yang, Wei (Transactions on Computer Science and Intelligent Systems Research, 2025)
This research addresses the issues of low efficiency, high error rates in traditional manual railway brake shoe replacement, and the mismatch between existing automated equipment and actual needs due to insufficient technical adaptability. It designs an intelligent management and control system integrating NFC technology and intelligent optimization algorithms, adopting a hierarchical architecture (perception, transmission, decision-making layers). NFC realizes automatic data acquisition; SVM and GAM models achieve data matching and traceability; a hybrid GA-PSO algorithm optimizes scheduling. Experimental verification shows the system significantly improves recognition accuracy, scheduling efficiency, and anomaly response speed. Innovations include an NFC-based full-link data acquisition pathway, an SVM-KNN integrated model for accurate data alignment, and a GA-PSO hybrid mechanism for optimal resource allocation. It shifts from manual to algorithm-driven operations, providing a promotable paradigm for digital transformation of railway operation and maintenance.