吉林大学学报(工学版) ›› 2021, Vol. 51 ›› Issue (1): 206-216.doi: 10.13229/j.cnki.jdxbgxb20190836

• 交通运输工程·土木工程 • 上一篇    

基于滑移率辨识的汽车制动时序视觉检测方法

吴岛1(),张立斌1(),张云翔2,单洪颖3,单红梅1   

  1. 1.吉林大学 交通学院,长春 130022
    2.吉林大学 生物与农业工程学院,长春 130022
    3.吉林大学 机械与 航空航天工程学院,长春 130022
  • 收稿日期:2019-08-24 出版日期:2021-01-01 发布日期:2021-01-20
  • 通讯作者: 张立斌 E-mail:wudao16@mails.jlu.edu.cn;zlb@jlu.edu.cn
  • 作者简介:吴岛(1991-),男,博士研究生.研究方向:车辆智能化检测与诊断. E-mail: wudao16@mails.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)

Visual detection method for vehicle braking time sequence based on slip rate identification

Dao WU1(),Li-bin ZHANG1(),Yun-xiang ZHANG2,Hong-ying SHAN3,Hong-mei SHAN1   

  1. 1.College of Transportation,Jilin University,Changchun 130022,China
    2.College of Biological and Agricultural Engineering,Jilin University,Changchun 130022,China
    3.School of Mechanical and Aerospace Engineering,Jilin University,Changchun 130022,China
  • Received:2019-08-24 Online:2021-01-01 Published:2021-01-20
  • Contact: Li-bin ZHANG E-mail:wudao16@mails.jlu.edu.cn;zlb@jlu.edu.cn

摘要:

针对现有制动性能检测方法存在的缺陷,提出了一种非接触式汽车制动时序动态检测方法。该方法以汽车制动过程中车轮滑移率变化作为切入点,根据滑移率与附着系数的关系,提出了基于滑移率的制动时序测量目标;基于双目立体视觉测量原理,建立了基于视觉的车轮滑移率测量模型;借助LM(Levenberg-Marquardt)算法对标定参数进行非线性优化,运用伪中值双边滤波、Canny边缘检测、冗余边界清除及Hough变换等图像处理技术,对图像分别进行去噪、边缘提取、精简和特征提取,得到圆形标识的中心坐标。为验证所提方法的可行性,进行了实车试验,并给出测量误差的标准不确定度评定结果。结果表明:在拓展不确定度U=2.52、置信因子k=2的条件下,本文方法最大相对误差为2.74%,重复性误差最大为3.88%。

关键词: 车辆工程, 半挂汽车列车, 制动时序, 立体视觉, Levenberg-Marquardt算法, 不确定度

Abstract:

To overcome the shortcomings of existing braking performance testing methods, a non-contact dynamic testing method for vehicle braking time sequence was proposed. Based on the relationship between slip rate and adhesion coefficient, a measurement target of braking time sequence based on slip rate was put forward. Based on the measurement principle of binocular stereo vision, a measurement model for wheel slip rate based on vision was established. With the help of LM (Levenberg-Marquardt) algorithm, the calibration parameters were optimized nonlinearly. Image processing techniques such as pseudo-median bilateral filtering, Canny edge detection, redundant boundary clearance and Hough transform were used to denoise, extract edges, simplify and extract features respectively, by which the central coordinates of circular markers were obtained. To verify the feasibility of the proposed method, a real-time test was carried out and the standard uncertainty evaluation results of measurement errors were given. The results show that the maximum relative error of the proposed method was 2.74% and the maximum repeatability error was 3.88% under the conditions of U=2.52 and k=2.

Key words: vehicle engineering, tractor-semitrailer, braking time sequence, stereo vision, Levenberg-Marquardt algorithm, uncertainty

中图分类号: 

  • U472.9

图1

附着系数与滑移率间的关系图"

图2

双目立体视觉测量原理"

图3

车轮滑移率测量模型"

图4

车轮圆形标识运动轨迹"

图5

曲线行驶矫正模型"

图6

双目摄像机采集的标定图像对"

表1

双目摄像机的内部参数和外部参数"

参数左摄像机右摄像机
Kαx(像素)2515.24672517.5498
αy(像素)2513.10342514.3697
u0(像素)513.2687512.4456
v0(像素)381.1249382.6125
Kck1,k2-0.0551,0.0265-0.0426,-0.0254
R0.9998-0.0141?-0.01520.00550.9986-0.0017-0.0047-0.00570.9972
T[-402.1589-6.21474.5368]

图7

重投影误差分布图"

图8

双目摄像机采集的圆形标识图像"

图9

伪中值双边滤波效果图"

图10

Canny边缘检测"

图11

冗余边界清除及圆形标识圆心坐标提取"

图12

汽车制动时序视觉检测系统整体布置"

图13

轮速信号采集单元"

表2

实车试验数据及检测结果 (s)"

检测方法编号一轴二轴三轴四轴五轴六轴
左轮右轮左轮右轮左轮右轮左轮右轮左轮右轮左轮右轮
本文方法10.760.770.970.990.930.920.720.740.820.841.121.08
20.780.770.950.980.910.920.710.730.850.831.101.09
30.750.780.981.010.920.930.730.750.830.841.141.12
轮速信号采集单元10.770.780.960.970.920.920.730.720.830.841.111.09
20.790.780.960.980.910.930.720.720.840.841.121.11
30.760.770.980.990.920.920.740.730.830.851.141.12

表3

标准不确定度评定结果"

轴数合成标准不确定度u(δ)/%

拓展不确定度

U/%

置信因子k
一轴左轮1.222.442
右轮1.232.46
二轴左轮1.242.48
右轮1.252.5
三轴左轮1.242.48
右轮1.242.48
四轴左轮1.222.44
右轮1.222.44
五轴左轮1.232.46
右轮1.232.46
六轴左轮1.262.52
右轮1.262.52
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