基于统计聚类的火车车体模块化粒度分析

Modular Particle Size Analysis of Train Body Based on Statistical Clustering

为增强火车车体的坚硬化程度,使外部车体结构达到高度模块化状态,提出基于统计聚类的火车车体模块化粒度分析方法。按照聚类网格的分割状态,度量车体数据的结构形式,在符合模块节点分布统计要求的基础上,完成火车车体模块的统计聚类处理。通过获取火车车体粒度参数的方式,划分车体模块化构件的层次结构,建立标准的粒度映射关系,实现基于统计聚类的火车车体模块化粒度分析。实验结果表明,与密度网格分析法相比,应用模块化粒度分析方法后,车体结构的WIR指标与WTR指标均出现一定程度提升,整个车体的坚硬化程度大幅增强,火车结构的高度模块化状态得以保障。

In order to enhance the hardening degree of the train body and make the external car body structure highly modular,a modular particle size analysis method based on statistical clustering is proposed.Measure the structural form of the car body data according to the segmentation state of the clustering grid.On the basis of meeting the statistical requirements of the module node distribution,the statistical clustering processing of the train body module is completed.Dividing the hierarchical structure of the modular components of the vehicle body by obtaining the size parameters of the train body.Establishing standard granular mapping relationship to realize modular granularity analysis of train body based on statistical clustering.The experimental results show that compared with the density grid analysis method,after applying the modular particle size analysis method,the WIR index and WTR index of the vehicle body structure are improved to some extent.The hardening degree of the entire car body is greatly enhanced,and the highly modular state of the train structure is guaranteed.