LS-SVM算法在无缝线路锁定轨温检测中的应用  

Application of LS-SVM algorithm in detecting the stress-free temperature of continuous welded rail

作　　者：陈蜀鹏 陈娟[1] 黄顺昊 祁欣[1] 李帅 邸锦玉 李鹏博 CHEN ShuPeng;CHEN Juan;HUANG ShunHao;QI Xin;LI Shuai;DI JinYu;LI PengBo(College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029;Baoding Works Business Section, China Railway Beijing Group Co. Ltd, Baoding 071000, China)

机构地区：[1]北京化工大学信息科学与技术学院,北京100029 [2]中国铁路北京局集团有限公司保定工务段,保定071000

出　　处：《北京化工大学学报（自然科学版）》2019年第3期87-92,共6页Journal of Beijing University of Chemical Technology(Natural Science Edition)

基　　金：国家自然科学基金(51275029/60971019)

摘　　要：提出一种改进的基于磁巴克豪森噪声(MBN)技术的无缝线路实际锁定轨温检测方法。该方法使用MBN技术检测钢轨温度应力,使用轨温计检测表面轨温,并采用最小二乘支持向量机(LS-SVM)算法建立线路的钢轨温度应力随钢轨表面轨温与实际锁定轨温差值变化的预测模型,最后将预测模型得到的温差和钢轨的表面轨温用于计算实际锁定轨温。通过对河北保定的一段无缝线路进行钢轨温度应力及表面轨温检测,证明该方法能提高检测的精度。Magnetic Barkhausen noise (MBN) technology has been used to detect the actual stress-free temperature of continuous welded rail. The method uses MBN technology to detect the rail temperature stress, and uses the rail thermometer to detect the surface rail temperature. Using the least squares support vector machine (LS-SVM) al-gorithm, a predictive model has been established to predict the relationship between the rail temperature stress and the difference between the surface rail temperature and the actual stress-free temperature. Finally, the temperature difference obtained by the predictive model and the surface rail temperature of the rail have been used to calculate the actual stress-free temperature. The rail temperature stress and surface rail temperature have been tested on a section of continuous welded rail in Baoding, Hebei Province, and the results show that the method improves the accuracy of detection.

关 键 词：最小二乘支持向量机(LS-SVM)算法 磁巴克豪森噪声(MBN) 温度应力 锁定轨温 

分 类 号：U213.913[交通运输工程—道路与铁道工程]