[1]李雪飞,吴月菊,孙艳红,等.基于离线监督性学习的高铁轮轨关系在线检测技术[J].机械与电子,2022,(04):61-65.
 LI Xuefei,WU Yueju,SUN Yanhong,et al.On Line Detection Technology of Wheel Rail Relationship Based on Off-line Supervised Learning[J].Machinery & Electronics,2022,(04):61-65.
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基于离线监督性学习的高铁轮轨关系在线检测技术()
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机械与电子[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2022年04期
页码:
61-65
栏目:
自动控制与检测
出版日期:
2022-04-27

文章信息/Info

Title:
On Line Detection Technology of Wheel Rail Relationship Based on Off-line Supervised Learning
文章编号:
1001-2257 ( 2022 ) 04-0061-05
作者:
李雪飞吴月菊孙艳红王宇超
中车长春轨道客车股份有限公司,吉林 长春 130000
Author(s):
LI Xuefei WU Yueju SUN Yanhong WANG Yuchao
( CRRC Changchun Railway Vehicles Co. , Ltd. , Changchun 130000 , China )
关键词:
离线监督性学习轮轨关系k 均值算法类中心横向力平衡方程
Keywords:
off-line supervised learning wheel rail relationship k-means algorithm class center lateral force balance equation
分类号:
TP399 ; U211.5
文献标志码:
A
摘要:
为维持高铁稳定运行,提升资源运输安全,在离线监督性学习算法的基础上,提出了一种轮轨关系在线检测技术。通过高速摄像机获取待检测图像,并进行拼接处理;计算加速度、轮轨力和轮轨间关系,依据关键部分的振动值得到列车的加速度值,以此判断列车是否处于平稳运行状态;通过间接测量法计算列车的横向力平衡方程和侧滚力矩平衡方程,得到轮轨力具体值;通过 k 均值算法聚类处理以明确各个样本的类中心,找出样本数量最少的类,设为异常类,完成高铁轮轨关系的在线检测。仿真实验结果表明,在稳定性、数据可靠性和实际应用方面,各项参数曲线变化幅度极为相同,曲线走向几乎一致,且使用后的轮轨接触状态较好,满足高铁轮轨关系在线检测技术的实际应用需求。
Abstract:
In order to maintain the stable operation of high-speed railway and improve the safety of resource transportation , an on-line detection technology of wheel rail relationship is proposed based on off-line supervised learning algorithm.The image to be detected is obtained through the high-speed camera and splicing processing is performed ; the acceleration , wheel rail force and the relation between wheel and rail are calculated to obtain the acceleration value of the train according to the vibration value of the key part , so as to judge whether the train is in a stable running state ; the lateral force balance equation and rolling moment balance equation of the train are calculated by indirect measurement method , and the specific value of wheel rail force is obtained ; through k-means algorithm clustering processing and clarifying the class center of each sample , the class with the least number of samples is found and is set as abnormal class to complete the on-line detection of wheel rail relationship of high-speed railway.The simulation results show that in terms of stability , data reliability and practical application , the variation range of each parameter curve is same , the curve trend is almost the same , and the wheel rail contact state after use is good , which meets the practical application requirements of high-speed rail wheel rail relationship on-line detection technology.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2021-09-10
作者简介:李雪飞 ( 1978- ),女,吉林龙井人,硕士,研究方向为城铁、高铁总体和高铁机械设备维护;吴月菊 ( 1979- ),女,吉林长春人,学士,高级工程师,研究方向为城市轨道交通车辆电气工艺技术开发;孙艳红 ( 1979- ),女,吉林长春人,学士,高级工程师,研究方向为城市轨道交通车辆电气工艺技术开发;王宇超 ( 1988- ),男,吉林长春人,学士,高级工程师,研究方向为城市轨道交通车辆辅助供电、电气连接技术。
更新日期/Last Update: 2022-04-29