铁道科学与工程学报2026，Vol.23Issue(7)：3073-3086,14.DOI:10.19713/j.cnki.43-1423/u.T20251356
横向振动条件下高铁梯形螺栓松动规律与结构优化设计
Loosening behavior and structural optimization design of high-speed railway trapezoidal bolted joints under lateral vibration
摘要
Abstract
Trapezoidal bolted joints serve as the primary fastening method for the skirt and bottom plate locks of high-speed train equipment compartments.During service,these joints are subjected to severe vibrational loads,which can lead to preload attenuation and even fatigue fracture,threatening safety.This study aimed to elucidate the loosening mechanism and identify critical conditions under transverse vibration,and conduct structural optimization for enhanced anti-loosening performance and reliability.A high-fidelity finite element model was developed using structured hexahedral meshing for the thread teeth,with mesh sensitivity analysis conducted to ensure convergence.Transverse vibrational loads of varying amplitudes were applied to investigate the loosening behavior and identify critical thresholds,revealing the evolution of contact state and contact stress on the threaded surfaces.A deep neural network(DNN)surrogate model was employed to capture the nonlinear relationship between the bearing surface inclination,clamped component thickness,and preload attenuation rate.Bayesian optimization was subsequently applied to minimize preload attenuation through structural parameter tuning.The DNN model demonstrated superior predictive accuracy compared to surrogate models based on support vector regression,random forest regression,and Gaussian process regression.Results indicate the existence of a critical transverse vibration amplitude.Below this value,the preload attenuation is caused by stress redistribution.Above it,the rotational loosening between internal and external threads can result in progressive preload loss.The optimized joint configuration can reduce preload attenuation by 14.73%and thread surface slip by 78%under 0.2 mm amplitude vibration,significantly improving anti-loosening performance.The integration of the deep neural network surrogate model with Bayesian optimization enables efficient structural parameter identification,substantially enhancing the joint's vibration resistance without additional anti-loosening components.This approach aligns with the lightweight and high-reliability requirements of high-speed rail applications.The results can provide valuable insights for the anti-loosening design and assembly of critical bolted connections such as train skirt locks.关键词
高铁/梯形螺纹/横向振动/松动/结构优化Key words
high-speed railway/trapezoidal thread/lateral vibration/loosening/structural optimization分类
交通工程引用本文复制引用
王清华,朱志鹏,巩浩,刘检华,敖晓辉,李鹏..横向振动条件下高铁梯形螺栓松动规律与结构优化设计[J].铁道科学与工程学报,2026,23(7):3073-3086,14.基金项目
河北省自然科学基金重点项目(E2023105059) （E2023105059）
国家自然科学基金"叶企孙"科学基金资助项目(U2341274) （U2341274）
