摘要
轨道探伤小车是新一代铁路轨道探伤设备,现已具备伤损点自动识别功能,但其定位依赖单一里程计,仍需人工标定来完成伤损点的实时地理位置定位,无法满足伤损定位的精度要求和实现全面自动伤损扫查检测功能的需求。针对铁路线上伤损扫查过程中的自动定位问题,使用扩展卡尔曼滤波(EKF)实现了里程计与全球卫星导航系统(GNSS)的多传感器数据融合,并基于新息自适应估计(IAE)对融合算法作自适应处理,建立GNSS/里程计组合定位模型,以提高探伤小车定位的精确性与可靠性。最后设计开发了硬件板卡,并通过沪杭线上测试实验,对组合定位模型进行验证。实验表明基于EKF的组合定位相较于单一GNSS定位其定位精度和鲁棒性明显提高。
Dual rail inspection vehicle is a new generation of railway inspection equipment,which has the function of automatic inspection of rail defect points.Conventionally,the localization of the inspection vehicle uses an odometer and the real-time localization of rail defect points still needs manual calibration.Thus,it cannot achieve the localization accuracy as well as the requirements of vehicle automatic operation.The automatic localization methods were discussed in this paper.The Extended Kalman Filter(EKF)was employed for the multi-sensor data fusion of the odometer and the Global Navigation Satellite System(GNSS).Then the fusion algorithm was processed using the Innovation Adaptive Estimation(IAE).The GNSS/odometer combined localization model has been built to improve the accuracy and reliability of the inspection vehicle localization.The hardware board was designed.Finally the on-line test has been performed on the Shanghai-Hangzhou railway line.The experimental results show that our combined localization method can significantly improve the accuracy and robustness compared with that of the single GNSS method.
作者
刘长军
王黛月
余天乐
郭建志
李锦
LIU Changjun;WANG Daiyue;YU Tianle;GUO Jianzhi;LI Jing(School of Mechanical and Power Engineering,East China University of Science and Technology,Shanghai 200237,China;Shanghai Oriental Maritime Affairs Engineering Technology Co.,Ltd.,Shanghai 200011,China)
出处
《铁道科学与工程学报》
CAS
CSCD
北大核心
2020年第10期2649-2655,共7页
Journal of Railway Science and Engineering
基金
国家重点研发计划项目(2017YFC0805704)。
关键词
轨道探伤
扩展卡尔曼滤波
数据融合
自适应
组合定位
rail inspection
extended Kalman filter
data fusion
adaptive
combined localization
