基于激光摄像式传感器的轨底坡动态检测方法研究
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摘要
动态检测轨底坡可高效指导铁路运营维护,合理设置坡角有利于保证钢轨轨头与车轮踏面的合理接触,延长钢轨的使用寿命。提出一种基于激光摄像技术,可在线、连续提取钢轨轮廓图像的轨底坡动态检测方法;考虑摄像机镜头畸变对钢轨轮廓图像的影响,建立了用于轨底坡动态检测的两个激光摄像式传感器空间姿态关系的非线性标定解算模型;利用Kalman滤波算法的数据融合功能建立了对多传感器信号融合的状态空间模型,消除因车体振动对轨底坡计算结果的影响。选用GJ-4型轨道检测车进行实车试验,验证了轨底坡计算方法切实、可行,通过Kalman滤波后的传感器数据能很好地对轨底坡坡角计算结果进行补偿。
The dynamic detection of rail cants can efficiently guide the railway operation and maintenance.Reasonably setting rail cant angle is beneficial to ensure the reasonable contact between rail head and wheel tread,therefore increasing the rail service life. A method was proposed based on the laser camera technology,which can continually extract the contour of rail on line. Considering the influence of the camera lens distortion on the rail contour image,a nonlinear calibration resolver model for the spatial attitude relationship of two laser camera sensors was established. By using the data fusion function of the Kalman filtering algorithm,a state space model for the multi-sensor signal fusion was established to eliminate the effect of car body vibration on the calculating results of rail cants. At last,a GJ-4 type track inspection vehicle was taken to perform the real vehicle test and it is verified the rail cant calculation method proposed is feasible and practical. The sensor data after Kalman filtering can compensate the results of the rail cant angle calculation very well.
The dynamic detection of rail cants can efficiently guide the railway operation and maintenance.Reasonably setting rail cant angle is beneficial to ensure the reasonable contact between rail head and wheel tread,therefore increasing the rail service life. A method was proposed based on the laser camera technology,which can continually extract the contour of rail on line. Considering the influence of the camera lens distortion on the rail contour image,a nonlinear calibration resolver model for the spatial attitude relationship of two laser camera sensors was established. By using the data fusion function of the Kalman filtering algorithm,a state space model for the multi-sensor signal fusion was established to eliminate the effect of car body vibration on the calculating results of rail cants. At last,a GJ-4 type track inspection vehicle was taken to perform the real vehicle test and it is verified the rail cant calculation method proposed is feasible and practical. The sensor data after Kalman filtering can compensate the results of the rail cant angle calculation very well.
引文
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[2]陶功权,温泽峰,陆文教,等.不同轨底坡下地铁车辆轮轨型面匹配的静态接触分析[J].铁道学报,2015,37(9):82-89.TAO Gongquan,WEN Zefeng,LU Wenjiao,et al.Static contact analysis of matching relationship of metro vehicle wheel and rail profiles under different rail cant conditions[J].Journal of the China Railway Society,2015,37(9):82-89.
[3]李霞,温泽峰,金学松.钢轨轨底坡对LM和LMA两种轮对接触行为的影响[J].机械工程学报,2008,44(3):64-69.LI Xia,WEN Zefeng,JIN Xuesong.Effect of rail cant on the rolling contact behavior of LM and LMAwheelsets[J].Journal of Mechanical Engineering,2008,44(3):64-69.
[4]ALIPPI C,CASAGRANDE E,SCOTTI F,et al.Composite real-time image processing for railways track profile measurement[J].IEEE Transactions on Instrumentation and Measurement,2000,49(3):559-564.
[5]ZHANG Z.A flexible new technique for camera calibration[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2000,22(11):1330-1334.
[6]占栋,于龙,肖建,等.轨道检测中激光摄像式传感器标定方法研究[J].机械工程学报,2013,49(16):39-47.ZHAN Dong,YU Long,XIAO Jian,et al.Calibration approach study for the laser camera transducer of track inspectiong[J].Journal of Mechanical Engineering,2013,49(16):39-47.
[7]POPOV D V,RYABICHENKO R B.Calibration of the CCDphotonic measuring system for railway inspection[C]//International Society for Optics and Photonics.[S.l.]:[s.n.],2005.
[8]WENG J,COHEN P,HERNIOU M.Camera calibration with distortion models and accuracy evaluation[J].IEEETransactions on Pattern Analysis and Machine Intelligence,1992,14(10):965-980.
[9]RICOLFE-VIALA C,SNCHEZ-SALMERN A J.Robust metric calibration of non-linear camera lens distortion[J].Pattern Recognition,2010,43(4):1688-1699.
[10]WANG J,SHI F,ZHANG J,et al.A new calibration model of camera lens distortion[J].Pattern Recognition,2008,41(2):607-615.
[11]LEE J S,CHOI S,KIM S S,et al.Displacement estimation from axle-box acceleration using Kalman filter[C]//In Proc.Autumn Conf.Annu.Meeting Korean Soc.Railway.[S.l.]:[s.n.],2009.
[12]ZHAO L,NIE Q,GUO Q.Unscented Kalman filtering for SINS attitude estimation[C]//2007 IEEE International Conference on Control and Automation.Guangzhou:IEEE,2007.
[13]LEE J S,CHOI S,KIM S S,et al.A mixed filtering approach for track condition monitoring using accelerometers on the axle box and bogie[J].IEEE Transactions on Instrumentation and Measurement,2012,61(3):749-758.