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基于视觉检测系统技术的产品质量检测

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  产品质量检测是上市之前缺一不可的环节,传统的质检存在很多弊端,质检合格率也偏低。基于视觉检测系统技术的产品质量检测被越来越多的企业运用到品控中来。尤其是一些在高温、粉尘、震动的环境下工作会对人的身体造成一定程度的伤害,而机器视觉检测系统就有效的解决了这一问题。
  Product quality inspection is an indispensable link before listing. There are many disadvantages in traditional quality inspection, and the qualified rate of quality inspection is also low. Product quality inspection based on visual inspection system technology is used in quality control by more and more enterprises. In particular, some work in high temperature, dust, vibration environment will cause a certain degree of harm to the human body, and the machine vision detection system can effectively solve this problem.
  基于视觉检测系统技术的产品质量检测过程中,起着主要作用的技术有以下几方面:
  In the process of product quality inspection based on visual inspection system technology, the main technologies are as follows:
基于视觉检测系统技术的产品质量检测
  1.光源照明技术:特征提取、稳定性、均匀性、色温、光谱;
  Light source lighting technology: feature extraction, stability, uniformity, color temperature, spectrum;
  2.光电转换:CCD、CMOS、信噪比、像元尺寸、线阵、面阵;
  Photoelectric conversion: CCD, CMOS, SNR, pixel size, linear array, area array;
  3.图像数据传输:CamLink、USB、以太网、1394;
  Image data transmission: camlink, USB, Ethernet, 1394;
  4.数据采集及同步控制;
  Data acquisition and synchronous control;
  5.图像校正技术:平场校正、暗场校正、颜色校正、畸变校正、多台相机一致性校正;
  Image correction technology: flat field correction, dark field correction, color correction, distortion correction, multi camera consistency correction;
  6.图像处理算法:定位、Blob分析、动态掩膜;
  Image processing algorithm: positioning, blob analysis, dynamic mask;
  在视觉自动化检测过程中,对于每一种图像,都要经过分析综合考虑各种手段来进行处理达到效果。一般来说,产品存在瑕疵、缺陷部分的灰度值和周围正常部分相比要暗,也就是瑕疵部分灰度值偏小;而且,大多都是在光滑表面,所以整幅图的灰度变化总体来说非常均匀,缺乏纹理特征。也就是说瑕疵的检测一般使用基于统计的灰度特征或者阈值分割的方法将瑕疵部分标出。
  In the process of visual automatic detection, for each kind of image, it is necessary to analyze and comprehensively consider various means to process to achieve the effect. Generally speaking, the gray value of the defective part is darker than that of the surrounding normal part, that is, the gray value of the defective part is smaller; moreover, most of them are on smooth surface, so the gray change of the whole picture is generally very uniform, lacking of texture features. That is to say, the defect detection generally uses the method of statistical gray level feature or threshold segmentation to mark the defect part.
  山东红宝自动化有限公司是一家集研发、生产、销售、服务于一体的自动化检测设备和在线检测设备的高新技术企业,已服务机器视觉领域多年,有效帮助生产型企业实现苛刻的生产和包装目标,保证产品的质量和安全性。如磁瓦缺陷视觉检测系统,根据客户需求,检测磁性产品的表面检测如刮伤、裂纹、针眼、粘粉、凹槽等。
  Shandong Hongbao Automation Co., Ltd. is a high-tech enterprise integrating R & D, production, sales and service of automatic detection equipment and online detection equipment. It has served the field of machine vision for many years, effectively helping production enterprises to achieve harsh production and packaging objectives and ensure the quality and safety of products. Such as magnetic tile defect visual inspection system, according to customer demand, detect the surface of magnetic products, such as scratches, cracks, pinholes, sticky powder, grooves, etc.
  视觉检测技术在工业4.0自动化中扮演着重要的角色,不仅能够有效地提高生产效率、还能够提升产品的质量。山东红宝自动化有限公司基于丰富的自动化行业经验,为企业客户定制开发先进的视觉检测技术解决方案。
  Visual inspection technology plays an important role in industry 4.0 automation, which can not only effectively improve the production efficiency, but also improve the quality of products. Based on rich experience in automation industry, Shandong Hongbao Automation Co., Ltd. develops advanced visual inspection technology solutions for enterprise customers.