铁道标准设计2017，Vol.61Issue(2)：43-46,47,5.DOI:10.13238/j.issn.1004-2954.2017.02.010
基于奇异滤波及稳健回归的轨道曲线主点定位方法研究
Localization Algorithm for Track Curve Feature Point Based on Singular Value Decomposition and Robust Regression
摘要
Abstract
The localization of feature points on the curve is essential in track maintenance. How to calculate the position of the feature points accurately without line type mark remains the problem of concern by the industry. Based on the analysis of the characteristics of curve version diagram, this paper proposes a method based on singular value decomposition algorithm and robust regression to locate track curve feature point. The singular value decomposition is used to filter shock component in the vector data by means of interceptive matrixes, and robust regression is employed to reduce fitness bias due to slight data changes and compute feature point. Test results show that this method can find feature point rapidly and accurately, less affected by segment point selection bias and is suitable for engineering application.关键词
铁路轨道/奇异值分解/轨道曲线/曲线主点/稳健回归Key words
Railway track/Singular value decomposition/Track curve/Curve feature point/Robust re-gression分类
交通工程引用本文复制引用
殷华,朱洪涛,王志勇..基于奇异滤波及稳健回归的轨道曲线主点定位方法研究[J].铁道标准设计,2017,61(2):43-46,47,5.基金项目
国家自然科学基金地区科学基金(51468042) （51468042）
江西省自然科学基金(20142BAB206003) （20142BAB206003）
