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Research and implementation of ceramic valve spool surface defect detection system based on region and multilevel optimisation

机译:基于区域和多级优化的陶瓷阀阀型缺损检测系统的研究与实现

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摘要

A sub-regional and multilevel ceramic valve spool (CVS) surface defects algorithm is proposed to improve the adaptation of the existing surface defect detection algorithm and reduce missing rate. According to the different reflectivities in CVS surface, the surface was divided into two regions: polished surface (P) and non-polished surface (Non P), by the characteristics of CVS surface defect, it was divided into two types of defect: G defects and C defects. The P region and Non P region are extracted by searching template image pyramid information, adjusting the target grey-scale image position and posture, regional registration. The defects of the P region and Non P region are extracted by blob detection and crack detection. Through experimental research, the feasibility and applicability of the detection algorithm were verified. The experimental results showed that the detection algorithm was suitable for different types of CVS surface defects, and the missing rate was low, and it can improve the detection efficiency through the reasonable setting of priority.
机译:提出了一种亚区域和多级陶瓷阀阀芯(CVS)表面缺陷算法,以改善现有表面缺陷检测算法的适应并降低缺失率。根据CVS表面的不同反射症,表面分为两个区域:抛光表面(P)和非抛光表面(非P),通过CVS表面缺陷的特点,分为两种类型的缺陷:G缺陷和C缺陷。通过搜索模板图像金字塔信息来提取P区域和非P区域,调整目标灰度图像位置和姿势,区域注册。通过BLOB检测和裂纹检测提取P区域和非P区域的缺陷。通过实验研究,验证了检测算法的可行性和适用性。实验结果表明,检测算法适用于不同类型的CVS表面缺陷,缺失率低,可以通过合理的优先设置来提高检测效率。

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