基于车身垂直位移的过载和载荷质心识别方法

Yiran Ding, Daolin Zhou, Zhenyu Wang, Haoyu Wang, Ming Li, Shimin Yu
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引用次数: 2

摘要

重型车辆的运输能力大。重载车辆的载荷值和载荷质心位置随载货质量和行驶条件的不同而变化,影响车辆的行驶安全性和操纵稳定性。车辆的载荷值和载荷质心位置通常在固定的测试平台上进行测量,在测量过程中车辆是静止的或缓慢通过平台的。本文提出了一种基于机器视觉和车身垂直位移的车辆载荷和载荷质心测量系统,该系统在行驶过程中进行测量。首先,建立了车轴对应的车体位移和车辆载荷的数学模型,并建立了载荷质心识别模型;然后,根据具体要求布置路基设施,搭建识别环境。基于机器视觉技术,由侧摄像头识别垂直特征距离。最后,通过对参数的解析,得到整车载荷值。与数据库中的额定载荷数据进行比较,得出车辆的过载判断。车辆的载荷质心也可以被识别。通过对机器视觉识别的特征距离数据进行滤波,有效地减小了特征距离测量误差。车辆试验用五十铃ql5050和跃进尚军X500进行。实验结果验证了该系统的有效性,可用于识别过载和偏移载荷,载荷识别误差小于20%,并得到了载荷质心的位置。研究结果指导驾驶员合理装货,安全驾驶。重型车辆的载荷值和载荷质心位置也可以作为主动安全系统的输入,提高主动安全系统对复杂工况的适应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Overload and Load Centroid Recognition Method Based on Vertical Displacement of Body
The heavy-duty vehicles have large transportation capacity. Load value and load centroid position of the heavy-duty vehicles vary with the cargo mass and the driving condition, which affect driving safety and handling stability. Load value and load centroid position of the vehicles are usually measured on fixed test platform, and the vehicles are stationary or pass the platform slowly in the measurement process. This paper proposes a vehicle load and load centroid measurement system based on the machine vision and vertical displacement of the body, which is measured during the driving process. First, a mathematical model of the body displacement and vehicle load corresponding to the axles is established, and load centroid recognition model is established. Then, roadbed facilities are arranged according to specific requirements, and the identification environment is built. Based on the machine vision technology, the vertical characteristic distance is recognized by the side camera. Finally, the vehicle load value can be obtained by resolve the parameters. Compared with the rated load data in the database, the overload judgment of the vehicle is obtained. The load centroid of the vehicle can also be identified. By filtering the characteristic distance data recognized by the machine vision, the characteristic distance measurement error is effectively reduced. The vehicle experiments were carried out with ISUZU QL5050and Yuejin Shangjun X500. The experimental results verify the effectiveness of the system and can be used to identify overloads and offset loads, the load identification error is less than 20%, and the position of the load centroid is obtained. The result guide the driver to load cargoes reasonably and drive safely. Load value and load centroid position of the heavy-duty vehicles could be also used as the inputs of active safety system, which could improve the adaptability of active safety system to complex conditions.
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