信息通信技术与政策

信息通信技术与政策

信息通信技术与政策 ›› 2021, Vol. 47 ›› Issue (1): 20-26.doi: 10.12267/j.issn.2096-5931.2021.01.005

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表面微观缺陷检测方法及其应用研究

Research on surface micro-defect detection method and application

陈虎, 王成, 卢仁谦   

  1. 1. 重庆忽米网络科技有限公司,重庆,400000; 2. 西安电子科技大学,西安,710071
  • 出版日期:2021-01-15 发布日期:2021-01-26
  • 作者简介:
    陈虎:重庆忽米网络科技有限公司高级副总裁兼CTO,西安电子科技大学硕士生导师,清华大学AI专家,工业和信息化部工业互联网专家池成员之一,《工业互联网白皮书》主要编委成员,拥有两项工业互联网领域人工智能方向发明专利
    王成:重庆忽米网络科技有限公司高级产品总监,多年工业信息化、智能化应用实践经验,曾服务于中国建筑、宝钢集团、振华重工、广船集团等众多央企及跨国公司
    卢仁谦:重庆忽米网络科技有限公司高级技术总监,多年企业管理及大型集团信息化建设经验,主导设计并研发了工业互联网平台、标识解析二级节点平台、工业品交易服务平台等大型信息化平台

CHEN Hu,  WANG Cheng, LU Renqian   

  1. 1. Chongqing Humi Network Technology Co., Ltd., Chongqing 400000, China;
    2. Xidian University, Xi􀆳an 710071, China
  • Online:2021-01-15 Published:2021-01-26

摘要: 基于多技术融合的表面微观缺陷检测方法结合最新的物体成像、云计算、人工智能和5G 等前沿技术,建立微观缺陷检测系统,对微观领域的缺陷进行精确检测,具有识别速度快、准确率高、成本低、可追溯性强、数据分析、智能反控等优点,克服了传统检测手段的弊端,且在典型工业场景中得到了较好的应用。

关键词: 工业互联网, 视觉检测, 表面微观缺陷, 工业人工智能

Abstract: Surface micro-defect detection has a pivotal position in the industrial field. At present, a large number of manual or traditional machine vision methods are still used for surface micro-defect inspection, which leads to unstable defect detection accuracy on the sub-micron level, which are difficult to be fully promoted in the industrial field. The surface micro-defect detection method based on multi-technology fusion combines the latest object imaging technologies, cloud computing, AI and 5G and other cutting-edge technologies to establish a micro defect detection system to accurately detect defects in the micro field with fast recognition speed and high accuracy, low cost, strong traceability, data analysis, intelligent counter-control, etc., which overcomes the shortcomings of traditional detection methods, such as single-point detection, low accuracy, high cost, lagging response, poor analysis, and weak system.Finally, the application of this technology in typical industrial scenarios is discussed.

Key words: Industrial Internet, visual inspection, surface micro-defects, artificial intelligence