基于深度学习的黄色工业金刚石检测方法  

Detection method based on deep learning for yellow industrial diamond

作　　者：杨建新 兰小平 王波 闫蕾 赵振 冯亚东 YANG Jianxin;LAN Xiaoping;WANG Bo;YAN Lei;ZHAO Zhen;FENG Yadong(Information Center of China North Industries Group Corporation, Beijing 100089, China;Zhongnan Diamond Co.,Ltd., Nanyang 473264, Henan, China)

机构地区：[1]中国兵器工业信息中心,北京100089 [2]中南钻石有限公司,河南南阳473264

出　　处：《金刚石与磨料磨具工程》2020年第6期13-19,共7页Diamond & Abrasives Engineering

摘　　要：为解决工业生产中黄色工业金刚石人工检测速度慢、劳动强度大、质量一致性不高等问题,提出一种基于深度学习的黄色工业金刚石检测方法。针对黄色工业金刚石晶体结构特点,设计了一套硬件系统采集黄色工业金刚石样本数据;通过图像处理方法对黄色工业金刚石样本数据进行预处理,再利用VGG-16、Inception-V3和ResNet-50等3种网络结构构建3个基分类器后,采用集成融合的方法实现多个基分类器的信息融合和黄色工业金刚石的分类决策。试验验证结果表明:识别的2240、2280、2290等3种品级的黄色工业金刚石综合评价指标均达到85%以上,该方法具有较高的实时性和应用价值。To solve problems such as low manual testing speed,high labor intensity and limited quality consistency of yellow industrial diamond test,we proposed a testing method based on deep learning for yellow industrial diamond.Firstly,a hardware system was developed to collect the data of the yellow industrial diamond by its structural characteristics.Then,the data were pre-processed by image processing,using three basic classifiers,namely VGG-16,inception-V3 and ResNet-50 to construct three network structures respectively.The information fusion of each basic classifiers and classification decision were realized by integrating fusion method.It is confirmed by verifying test that the comprehensive recognition evaluation indicators of yellow industrial diamonds with grades of 2240,2280 and 2290 are all over 85%.This testing method is valuable and highly practicableness.

关 键 词：深度学习 图像处理 工业金刚石 集成分类器 

分 类 号：TQ164[化学工程—高温制品工业] TP183[自动化与计算机技术—控制理论与控制工程]