中国机械工程2019，Vol.30Issue(4)：455-460,6.DOI:10.3969/j.issn.1004-132X.2019.04.011
边缘扩展的皮带撕裂支持向量机视觉检测
Visual Inspection for Extended Edge Belt Tearing Based on SVM
摘要
Abstract
A belt safety monitoring method was proposed based on vision, and a visual monitoring system for belt tearing was constructed.Aiming at the image degradation from interference during operations of belt conveyor, Wiener filtering method was used to restore the degraded images.In order to recognize the belt cracks with high-speed moving in real time, CamShift algorithm was used to track and capture the targets of fast-moving sequence images of belt cracks.Canny operator was used to extract the edges of belt cracks, and the detected edges of belt cracks were expented outwards by adding a valueδ, increasing the weights of the detected cracks, and more robust edge detection results were obtained.Finally, belt crack prediction model was constructed based on SVM, geometric characteristics, such as pixel area and length width ratio of the belt crack images were taken as the model inputs to predict belt crack states.Experimental results show the effectiveness of the method of belt tearing detection method proposed herein.关键词
皮带撕裂/图像分割/Canny边缘提取/支持向量机/裂纹识别Key words
belt tearing/image segmentation/Canny edge extraction/support vector machine (SVM)/crack recognization分类
信息技术与安全科学引用本文复制引用
王福斌,孙海洋,TU Paul..边缘扩展的皮带撕裂支持向量机视觉检测[J].中国机械工程,2019,30(4):455-460,6.基金项目
国家自然科学基金资助项目(71601039) （71601039）
