铁道科学与工程学报2018，Vol.15Issue(2)：292-301,10.
一种基于GBRT算法的CA砂浆脱空检测方法
A detection method of CA mortar disengaging based on GBRT algorithm
摘要
Abstract
Different from the existing detection methods, the GBRT algorithm of machine learning was applied in the CA mortar disengaging detection field using the difference between the sound signal of track slab collected at void and non-void situation for the first time. Using the data collected at the void and non-void situation, a binary classification model was trained with the GBRT algorithm. Category-decision was made for the input data and whether corresponding gathering place is void was judged. The algorithm principle was explained in detail, and the use skills of the model were analyzed combined with the CA mortar disengaging detection. Other mainstream machine learning classification algorithms were introduced for comparative analysis. And the result shows that the GBRT algorithm is much better and has a great application prospect in this field.关键词
无砟轨道/CA砂浆/脱空/GBRT算法/机器学习分类算法Key words
ballastless track/CA mortar/disengaging/GBRT algorithm/machine learning classification algorithm分类
交通工程引用本文复制引用
李自法,谢维波,刘涛..一种基于GBRT算法的CA砂浆脱空检测方法[J].铁道科学与工程学报,2018,15(2):292-301,10.基金项目
国家自然科学基金资助项目(61271383) （61271383）
华侨大学研究生科研创新能力培育计划资助项目(1511314017) （1511314017）
