摘要
表面缺陷检测是汽车安全带质量检测中的关键环节之一,目前人工检测方法存在效率低、稳定性差的问题,无法满足实际检测需求。搭建一个汽车安全带表面缺陷检测平台,构建基于机器视觉的表面缺陷检测系统。针对汽车安全带的表面缺陷特征,提出一种基于频谱分析的特征提取方法,并讨论频域滤波器的选择和参数的计算。实验结果表明:频谱分析法同Bob特征分析法、直方图法等相比,能更好地满足汽车安全带表面缺陷检测的准确率和实时性要求。
Surface defect detection is one of the key links in the quality inspection of seat belt. At present, low efficiency andpoor stability exist in artificial detection, so actual detection needs can not meet. The seat belt surface defect detection algorithm wasexplored based on image processing algorithms to meet the actual demand, and the seat belt surface defect detection system based onmachine vision was constructed. Aiming at the characteristics of surface defect of seat belt, a method of feature extracting based onspectrum analysis was presented, and the selection of the filter and the calculation of the parameters were discussed. The experimentalresults show that the spectrum analysis method has better effect on the detection of surface defects than other detection methods, whichcan meet the requirements of real-time and accuracy.
出处
《机床与液压》
北大核心
2018年第2期134-138,共5页
Machine Tool & Hydraulics
关键词
缺陷检测
机器视觉
滤波器
频谱分析
Defect detection
Machine vision
Filter
Spectrum analysis
