Design and Application of Vehicle Front Chassis Assembly Visual Inspection System
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.
automobile manufacturingautomobile assembly parts inspectionYOLOv3fringe detectionnon-maximum suppression
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