主办：陕西省汽车工程学会
ISSN 1671-7988  CN 61-1394/TH
创刊：1976年
汽车实用技术

汽车实用技术 ›› 2024, Vol. 49 ›› Issue (11): 110-114.DOI: 10.16638/j.cnki.1671-7988.2024.011.022

• 工艺·材料 • 上一篇    

基于图像配准的车架缺陷检测与识别方法研究

许振华 1，迪茹侠 2，张延鹏 1，茹 强 1，丁道霖 1，李海鸽 2   

  1. 1.比亚迪汽车有限公司； 2.西安汽车职业大学 机电与智能制造工程学院
  • 发布日期:2024-06-26
  • 通讯作者: 许振华
  • 作者简介:许振华（1989－），男，硕士，工程师，研究方向为电动汽车软件开发，E-mail:2392649013@qq.com。
  • 基金资助:
    教育部科技发展中心 2022 年度《虚拟仿真技术在职业教育教学中的创新应用》专项课题：虚拟仿真技术赋 能职业本科数智实训教学的创新研究与实践（ZJXF2022153）；西安汽车职业大学校长 2019 年度科研基金项 目“多自由度机械臂控制系统的研究与设计”（2019KJ003）

Research on Frame Defect Detection and Recognition Method Based on Image Registration

XU Zhenhua1 , DI Ruxia2 , ZHANG Yanpeng1 , RU Qiang1 , DING Daolin1 , LI Haige2   

  1. 1.BYD Automobile Company Limited; 2.School of Mechanical, Electrical and Intelligent Manufacturing Engineering, Xi'an Vocational University of Automobile
  • Published:2024-06-26
  • Contact: XU Zhenhua

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摘要： 针对流水线上底盘车架外形缺陷检测和识别存在效率低、准确度不高、劳动强度大的 缺点，提出一种基于图像配准的车架缺陷检测与识别方法。获取标准图像，通过最大类间方 差法与形态学等操作建立形状匹配模板。在线采集待测车架图像，利用形状模板匹配算法查 找待测车架图像在标准图像中的位置与旋转角度，对待测车架图像进行配准，使其与标准车 架图像处于同一空间位置关系。通过逻辑异或把待测目标图像与标准库图像进行匹配运算， 采用形态学算法去除系统中干扰缺陷杂质。RGB 分量滤波后，进行图像重叠并调整透明度， 从而得到缺陷图。研究结果表明，该方法可有效提取车架外形特征，进而得到过铆、漏铆、 多孔、少孔等多种外形缺陷，其检测速度快，具有较好的鲁棒性。

关键词: 车架；图像配准；形状模板匹配；MATLAB；缺陷检测

Abstract: Aiming at the shortcomings of low efficiency, low accuracy and high labor intensity in the detection and recognition of chassis frame shape defects on the assembly line, a frame defect detection and recognition method based on image registration is proposed. The standard image is obtained, and the shape matching template is established by the maximum between class variance method and morphology. The frame image to be tested is collected online, and the position and rotation angle of the frame image to be tested in the standard image are found by using the shape template matching algorithm. The frame image to be tested is registered so that it is in the same spatial position relationship with the standard frame image. The target image to be tested is matched with the standard library image by logical XOR, and the interference defects and impurities in the system are removed by morphological algorithm. After RGB component filtering, the image is overlapped and the transparency is adjusted to obtain the defect image. The research results show that this method can effectively extract the shape characteristics of the frame, and then obtain a variety of shape defects such as over riveting, missing riveting, porous, few holes, etc., with fast detection speed and good robustness.

Key words: Frame; Image registration; Shape template matching; MATLAB; Defect detection