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Image analysis algorithm and verification for on-line molecular sieve size and shape inspection

机译:在线分子筛尺寸和形状检测的图像分析算法和验证

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摘要

An online machine vision inspection method is proposed to implement feedback control of molecular sieve growth process in rotary drum granulation. An experimental platform, comprising of a high-resolution digital camera and an image analysis system, has been developed to confirm the validity of the method on particle size distribution (PSD) and sphericity measurements. Experiments were performed with non-uniform molecular sieve particles (1-3 mm diameter) obtained from production line. The particle images are first obtained through digital camera and are then processed by image analysis system. After separating the overlap particles and removing non-target particles of the images, the molecular sieve size and shape are computed in less than 0.9 s. The validity of the size measuring accuracy is confirmed through comparing with the results from micrometer. The experimental results show that the repetitive precision of the proposed inspection system is about ±1%, the diameter measurement error between image method and micrometer is about ±3%, single image inspection speed is around 0.9 s/frame. The proposed method is reliable to provide feedback information for control system in rotary drum granulation.
机译:提出了一种在线机器视觉检测方法,以实现转鼓造粒中分子筛生长过程的反馈控制。已经开发了一个由高分辨率数码相机和图像分析系统组成的实验平台,以确认该方法对粒径分布(PSD)和球形度测量的有效性。对从生产线获得的不均匀分子筛颗粒(直径1-3 mm)进行了实验。颗粒图像首先通过数码相机获取,然后通过图像分析系统进行处理。分离出重叠颗粒并去除图像的非目标颗粒后,分子筛的大小和形状的计算时间不到0.9 s。通过与测微计的结果进行比较,可以确定尺寸测量精度的有效性。实验结果表明,所提出的检测系统的重复精度约为±1%,图像方法与千分尺之间的直径测量误差约为±3%,单幅图像检测速度约为0.9 s /帧。所提出的方法能够可靠地为转鼓造粒控制系统提供反馈信息。

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