肖军华;郭佳奇;张德;薛立华;

• 1:同济大学上海市轨道交通结构耐久与系统安全重点实验室
• 2:同济大学道路与交通工程教育部重点实验室
• 3:上海公路桥梁(集团)有限公司

摘要(Abstract)：

道砟颗粒几何形态特征对其力学特性影响显著。为了量化研究铁路道砟形态特征,以真实的铁路一级碎石道砟颗粒为例,采用3D激光扫描获取道砟颗粒点云数据,引入道砟整体形态特征指标(长轴、中轴、短轴、球度指数),提出道砟局部形态特征指标(曲率指数),统计并建立上述整体和局部形态特征指标的概率密度分布函数。在此基础上,基于本征正交分解(POD)及径向基(RBF)神经网络提出了基于颗粒形态指标概率密度分布的道砟样本的重生成算法,重构道砟颗粒样本库。采用上述重生成算法分别重构了600及4 000个颗粒道砟,结果表明:重构道砟样本形态特征指标的统计分布结果均与真实扫描试样结果接近,证明该方法能够快速实现基于颗粒形态指标概率密度分布的任意数量道砟样本的建立。

关键词(KeyWords)： 道砟形态特征;曲率指数;本征正交分解;径向基神经网络;道砟重生成

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金(51678447)

作者(Author): 肖军华;郭佳奇;张德;薛立华;

Email:

DOI:

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