摘要
针对现有轨检车里程信息存在偏差进而影响检测数据应用性的问题,研究了一种针对轨道动态检测系统的精确里程修正方法。首先,针对系统采样频率随检测速度变化的特点,设计了基于最小均方自适应滤波的惯性数据预处理方法;其次,设计了基于扩展卡尔曼滤波的多源融合精准定位和里程确定方法;然后,根据线路台账参数生成曲线数据,使用最小二乘法与互相关性法对检测数据的里程在离线端进行修正。将算法应用于轨道检测系统中,验证了该方法能有效提升里程定位精度,检测数据重复性精度相较之前提升了77%~81%。
Aiming at the problem that the mileage information of existing track inspection car has deviation,which affects the applicability of the detection data,an accurate mileage correction method for the track dynamic inspection system was studied. Firstly,according to the characteristics that the sampling frequency of the system changes with the inspection speed,an inertial data preprocessing method based on least mean square adaptive filtering was designed.Secondly,a multi-source fusion accurate positioning and mileage determination method based on extended Kalman filtering was designed. Then,the curve data was generated according to the line account parameters,and the mileage of the inspection data was corrected at the offline end by using the least square and cross-correlation methods. The algorithm is applied to the track inspection system to verify that this method can effectively improve the accuracy of mileage location,and the repeatability accuracy of inspection data is improved by 77% ~ 81% compared with the previous one.
作者
陈仕明
魏世斌
秦哲
王昊
李颖
程朝阳
李浩然
CHEN Shiming;WEI Shibin;QIN Zhe;WANG Hao;LI Ying;CHENG Zhaoyang;LI Haoran(Postgraduate Department,China Academy of Railway Sciences,Beijing 100081,China;Infrastructure Inspection Research Institute,China Academy of Railway Sciences Corporation Limited,Beijing 100081,China)
出处
《铁道建筑》
北大核心
2022年第7期52-56,共5页
Railway Engineering
基金
中国国家铁路集团有限公司科技研究开发计划(K2021T015)
中国铁道科学研究院集团有限公司基金(2020YJ065)。
关键词
高速铁路
动态检测
轨检车
里程修正
卡尔曼滤波
台账
high speed railway
dynamic inspection
track inspection car
mileage correction
Kalman filtering
account
