汽车前底盘装配视觉检测系统设计与应用
Design and Application of Vehicle Front Chassis Assembly Visual Inspection System
李硕 1苑明哲 2王文洪 3史洪岩 4肖金超 2宋纯贺 5曹飞道3
作者信息
- 1. 沈阳化工大学信息工程学院;中国科学院沈阳自动化研究所;广州工业智能研究院
- 2. 中国科学院沈阳自动化研究所;广州工业智能研究院
- 3. 广州工业智能研究院
- 4. 沈阳化工大学信息工程学院
- 5. 中国科学院沈阳自动化研究所
- 折叠
摘要
为解决汽车底盘混流装配错装、漏装和人工检测效率低的问题,设计了基于YOLOv3-Tiny的在线检测系统.该检测系统利用4 套光源-相机组合的成像系统,从多角度获取前底盘模块的全貌图像,利用基于差分统计的条纹识别算法剔除低质量图像;根据检测目标特性,简化非极大值抑制算法,优化检测过程.实验和现场运行结果表明:检测系统目标无遮挡检出率达到 100%,综合识别准确率达到99.95%,平均检测时间 3.5 s,较之前人工检测效率提升 94.55%,检测系统具有较高的准确度和检测效率,在汽车工业中实现了柔性化和智能化的目标检测应用.
Abstract
In order to solve the problems of wrong assembly,missing assembly and low efficiency of manual inspection in au-tomobile chassis mixed-flow assembly,an on-line detection system based on YOLOv3-Tiny was designed.The detection system used four sets of imaging systems consisting of light sources and cameras to obtain the panoramic image of the front chassis mod-ule from multiple angles.And the detection system used the fringe recognition algorithm based on differential statistics to eliminate the low-quality image.According to the characteristics of the detection target,the non-maximum suppression algorithm was simpli-fied.And the detection process was optimized.The results of experiment and field operation show that the unoccluded detection rate,comprehensive recognition accuracy and average detection time are 100%,99.95%and 3.5 s.The average detection time is 94.55%lower than that of manual detection.The detection system has higher accuracy and higher efficiency,and has achieved flexible and intelligent target detection applications in the automotive industry.
关键词
汽车制造/汽车装配部件检测/YOLOv3/条纹检测/非极大值抑制Key words
automobile manufacturing/automobile assembly parts inspection/YOLOv3/fringe detection/non-maximum suppression引用本文复制引用
基金项目
国家自然科学基金面上项目(62273332)
国家自然科学基金面上项目(62273337)
中科院科技服务网络计划(STS)-东莞专项(20211600200072)
出版年
2024
NETL
NSTL
万方数据