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The Tires Worn Monitoring Prototype System Using Image Clustering Technology

机译:基于图像聚类技术的轮胎磨损监测原型系统

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摘要

In order to improve traffic safety, researchers studied the driver's physical or mental monitoring, vehicle structure, airbags, brake systems and tires and so on for continuous improvement. The tires need to carry the vehicle loading, to enhance grip, to improve the drainage ability and to reduce the friction noise. Accordingly, tire wear will affect the aforementioned features. This study had designed an experiment platform which can detect the main tread depth, applying image clustering technique, under conditions of low tire speed. In addition, the proposed image clustering algorithm FCM_sobel, could measure the depth of the main tread, at α = 0.5 (the influence weighting of the neighboring pixels) and rotating cycle equal 2.5 seconds/rotation. The imple-mental results show that the precision rates were 93.41%, 96.86 % for the depths of the main tread Ⅰand Ⅱ respectively. Consequently, detected the depth of the main tread Ⅰ, the precision rate improved 3% compared with FCM_S1.
机译:为了提高交通安全性,研究人员研究了驾驶员的身体或精神监控,车辆结构,安全气囊,制动系统和轮胎等,以进行持续改进。轮胎需要承载车辆载荷,以增强抓地力,改善排水能力并减少摩擦噪音。因此,轮胎磨损将影响前述特征。这项研究设计了一个实验平台,该平台可以在低轮胎速度的情况下应用图像聚类技术检测主胎面深度。此外,提出的图像聚类算法FCM_sobel可以在α= 0.5(相邻像素的影响权重)和等于2.5秒/旋转的旋转周期下测量主胎面的深度。实验结果表明,主胎面Ⅰ和Ⅱ的深度精度分别为93.41%,96.86%。因此,检测主胎面Ⅰ的深度,与FCM_S1相比,精度提高了3%。

著录项

  • 来源
  • 会议地点 Amsterdam(NL)
  • 作者单位

    Department of Computer Science and Information Engineering National Chin-Yi University of Technology;

    Department of Computer Science and Information Engineering National Chin-Yi University of Technology;

    Department of Industrial Engineering and Management,National Chin-Yi University of Technology Taichung 411, Taiwan, R.O.C;

    Department of Industrial Engineering and Management,National Chin-Yi University of Technology Taichung 411, Taiwan, R.O.C;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Tire wear; image clustering technique; FCM; FCM_sobel;

    机译:轮胎磨损;图像聚类技术; FCM; FCM_sobel;

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