During routine rail maintenance, rail grinding of sharp curves is challenging. In particular, setting up the grinding pattern is essential. A rail-grinding pattern optimisation method is proposed based on the mathematical relationship between the grinding pattern parameters and geometric parameters of the rail grinding profile. In this method, the design variables and constraints are reasonably selected, and a multi-objective optimisation function considering the wheel-rail contact stress, wheel-rail lateral force, and rail grinding amount is established. The optimisation model is solved using a chaotic microvariation adaptive genetic algorithm. The optimisation method is applied to the repairable grinding of a worn rail in a metro curve section. The results demonstrate that using this method can realise an ideal grinding pattern with the expected grinding effect in addition to high accuracy and high optimisation speed. The wheel-rail contact characteristics, wear characteristics, and train dynamic performance are significantly improved after rail grinding; this is significant for conducting grinding operations and improving the train’s curve-passing ability. Therefore, this study provides theoretical guidance for formulating rail-grinding patterns.
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