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Multi-objective optimization design of rail grinding profile in Curve Section of Subway based on wear Evolution and representative worn profile

Zhou Jun, Liu Linya, Li Jiyang

Eksploatacja i Niezawodność

2024

Vol. 26, no. 4

art. no. 191472

The grinding of curved rails is a crucial aspect of subway maintenance and repair. It effectively reduces wear. This paper proposes a multi-objective optimization design method for grinding profiles in curved sections. First, the Dynamic Time Regularisation (DTW) algorithm selects representative grinding profiles as the initial population. Then, the optimal design region is determined through wear characterization analysis. Mathematical expressions of wheel profiles are selected as design variables to build a parametric model. Next, the predictive model that considers the evolution of wheel wear is incorporated into the multi-objective function. The objective function's adaptive weight adjustment coefficient factors are introduced to establish the multi-objective optimization model for wheel profiles. The Latin hypercubic sampling method establishes the RBF agent model for simulation calculation. The optimization design of wheel profiles is carried out using the TS-NSGA-II multi-objective algorithm. Finally, a comparative verification analysis is conducted to assess the profiles before and after optimization. This analysis includes three key aspects: wheel wear evolution analysis, wheel-rail static contact analysis, and vehicle dynamics performance analysis.