吉林大学学报(工学版) ›› 2023, Vol. 53 ›› Issue (12): 3415-3423.doi: 10.13229/j.cnki.jdxbgxb.20220092

• 交通运输工程·土木工程 • 上一篇    

基于轮胎滑移率与单目视觉的半挂汽车列车制动时序检测

张立斌1(),冯诗源1,单洪颖2,王冠然1   

  1. 1.吉林大学 交通学院,长春 130022
    2.吉林大学 机械与航空航天工程学院,长春 130022
  • 收稿日期:2022-01-25 出版日期:2023-12-01 发布日期:2024-01-12
  • 作者简介:张立斌(1971-),男,教授,博士生导师.研究方向:车辆智能化检测与诊断.E-mail:zlb@jlu.edu.cn
  • 基金资助:
    国家自然科学基金项目(50775094);吉林省重点科技攻关项目(20150204025GX)

Braking timing detection of tractor⁃trailer⁃train based on tire slip rate and monocular vision

Li-bin ZHANG1(),Shi-yuan FENG1,Hong-ying SHAN2,Guan-ran WANG1   

  1. 1.College of Transportation,Jilin University,Changchun 130022,China
    2.School of Mechanical and Aerospace Engineering,Jilin University,Changchun 130022,China
  • Received:2022-01-25 Online:2023-12-01 Published:2024-01-12

摘要:

半挂汽车列车在制动过程中由于各车轴制动顺序的不同,导致车辆在特殊工况下制动时会出现车辆失稳现象。针对现有方案和设备无法对制动时序进行检测,本文提出了一种智能化非接触式的车辆制动时序动态检测方案。基于单目视觉原理,识别张贴在轮胎边缘的标志物,对采集的图像进行处理,求解出轮胎滑移率;利用基于轮廓的模板匹配算法识别待匹配图像中的标志物区域。最后,进行了实车试验,结果表明,本文方法的滑移率求解误差在4.2%以下。

关键词: 车辆工程, 半挂汽车列车, 制动时序, 单目视觉, 滑移率

Abstract:

In the braking process of tractor-trailer-train, due to the different braking sequence of each axle, vehicle instability occurs when braking under special conditions. Since the existing schemes and equipment can not detect the brake timing, an intelligent non-contact dynamic detection scheme for vehicle brake timing is proposed. Based on the principle of monocular vision, the markers affixed to the tire edge are identified. The collected images are processed to solve the tire slip rate. The template matching algorithm based on contour is used to identify the marker region in the image to be matched. In order to verify the effectiveness of the scheme, a real vehicle test is carried out. The test results show that the slip rate solution error is below 4.2%.

Key words: vehicle engineering, tractor-trailer-train, brake timing schemes, monocular vision, slip rate

中图分类号: 

  • U472.9

图1

纵向滑移率与附着系数关系"

图2

轮胎边缘标志物滑移轨迹图"

图3

轮胎滑移位移关系图"

图4

双标志物轮胎运动轨迹图"

图5

棋盘格图像采集"

表1

单目相机标定参数"

参数参数值
内参数矩阵 G1679.91710?????964.29510????1680.3922?602.19300????0?????1?????
径向畸变系数[k1k2k3-0.133730.11465-0.00067
切向畸变系数[p1p20.0000.0003

表2

棋盘格标定算法重复性试验结果"

试验次数内参数矩阵 G
11685.1429??????0.0085966.18260????1683.9237601.77010????0????1??????
21688.9924?-0.0074964.52140????1687.2231?598.90580????0?????1??????
31697.9517?????0.0045958.31320????1699.5614?596.33520????0?????1??????
41691.5519?????0.0107963.88420????1694.9245?602.25120????0?????1??????
51685.2547?-0.0055962.77140????1688.9102?603.52580????0?????1??????

表3

棋盘格标定算法试验数据离散性"

相机参数数据离散系数
fx3.1387×10-3
fy3.7093×10-3
u03.0779×10-3
v04.8335×10-3

图6

单目相机采集的圆形标识图像"

图7

图像噪声处理"

图8

标志物环形特征筛选图"

图9

Sobel算子边缘检测图"

图10

同心圆标志物识别效果图"

图11

滑移率检定装置结构图"

图12

加速至10 km/h滑移率随时间的变化曲线"

图13

实车试验硬件布置图"

图14

试验车左、右侧轮胎滑移率拟合曲线"

表4

汽车列车制动时序试验检测数据"

轴1轴2轴3轴4轴5轴6
0.490.480.330.330.370.380.310.30.410.420.450.44
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