中国铁道科学2023，Vol.44Issue(6)：46-56,11.DOI:10.3969/j.issn.1001-4632.2023.06.05
基于改进Faster R-CNN和正交投影的无砟轨道板裂缝精细化测量
Fine-Grained Measurement of Ballastless Track Slab Cracks Based on Improved Faster R-CNN and Orthogonal Projection
摘要
Abstract
Crack detection and width identification is an important basis for the of maintenance and repair operations of ballastless track slab.To this end,a crack width measurement method based on improved Faster R-CNN and orthogonal projection is proposed.Based on the virtual model synthesis data,the depth network is fully trained to realize accurate detection of surface cracks on ballastless track slab in complex background in order to improve the reliability of crack geometric feature quantization.Firstly,a parametric 3D BIM model of ballastless track structure is established based on 2D CAD drawings,and a random fusion of real crack features and virtual track model and the rendering of real inspection scene are realized through UE5 physics engine.Then,the virtual camera output is configured to simulate virtual crack images of real inspection scenarios;the improved Faster R-CNN network is adequately trained and tested on the original images captured by the track inspection vehicle.Finally,the width of the cracks in the detection results is calculated pixel by pixel using the orthogonal projection method and compared with the manual point-taking measurement results.The results show that the average precision of the improved Faster R-CNN network for crack detection is increased by approximately 10％.The network performance varies with the proportion of virtual and real images of the training data and reaches saturation at 4:1,with an average precision of 95.12％.In addition,the network trained with the fusion crack dataset can achieve higher recall while maintaining high accuracy,effectively reducing the missing detection of cracks.Compared with manual measurement,the minimum and maximum crack widths measured by the orthogonal projection method are increased by 3.64％and 22.40％respectively,and the measurement results are more stable and are close to the real value,which have higher reliability.关键词
轨道板表面裂缝/虚拟数据/改进FasterR-CNN/正交投影法/裂缝宽度测量Key words
Surface cracks of track slab/Virtual data/Improved Faster R-CNN/Orthogonal projection method/Crack width measurement分类
交通工程引用本文复制引用
王卫东,张晨雷,胡文博,邱实,王万齐,李娜,王劲..基于改进Faster R-CNN和正交投影的无砟轨道板裂缝精细化测量[J].中国铁道科学,2023,44(6):46-56,11.基金项目
国家自然科学基金-高铁联合基金资助项目(U1734208) （U1734208）
国家自然科学基金资助项目(52178442) （52178442）
