%0 Journal Article
%T 一种基于GBRT算法的CA砂浆脱空检测方法<br>A detection method of CA mortar disengaging based on GBRT algorithm
%A 李自法
%A 谢维波
%A 刘涛&lt
%A br&gt
%A LI Zifa
%A XIE Weibo
%A LIU Tao
%J 铁道科学与工程学报
%D 2018
%X 不同于现有检测方法，利用CA砂浆脱空和非脱空情况下采集到的声音信号不同，提出把机器学习领域中的GBRT算法应用到CA砂浆脱空检测领域。利用脱空和非脱空情况下采集到的数据，使用GBRT算法训练出一个二分类模型；通过对输入数据做类别决策，判断对应的采集位置是否脱空。介绍算法原理，并结合CA砂浆脱空问题，分析模型的使用技巧；引入其他主流机器学习分类算法进行比较分析。实验结果证明，GBRT算法构造的模型性能较好，在CA砂浆脱空检测领域具有应用前景。<br>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
%K 无砟轨道
%K CA砂浆
%K 脱空
%K GBRT算法
%K 机器学习分类算法&lt
%K br&gt
%K ballastless track
%K CA mortar
%K disengaging
%K GBRT algorithm
%K machine learning classification algorithm
%U http://www.jrse.cn/paper/paperView.aspx?id=paper_317551