An online detection system for aggregate sizes and shapes based on digital image processing

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• 作者：Jianhong Yang ; Sijia Chen
• 关键词：Aggregate ; Online detection ; Particle size ; Grain shape ; Digital image processing ; Particle size distribution
• 刊名：Mineralogy and Petrology
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：111
• 期：1
• 页码：135-144
• 全文大小：
• 刊物类别：Earth and Environmental Science
• 刊物主题：Mineralogy; Inorganic Chemistry; Geochemistry;
• 出版者：Springer Vienna
• ISSN：1438-1168
• 卷排序：111

文摘

Traditional aggregate size measuring methods are time-consuming, taxing, and do not deliver online measurements. A new online detection system for determining aggregate size and shape based on a digital camera with a charge-coupled device, and subsequent digital image processing, have been developed to overcome these problems. The system captures images of aggregates while falling and flat lying. Using these data, the particle size and shape distribution can be obtained in real time. Here, we calibrate this method using standard globules. Our experiments show that the maximum particle size distribution error was only 3 wt%, while the maximum particle shape distribution error was only 2 wt% for data derived from falling aggregates, having good dispersion. In contrast, the data for flat-lying aggregates had a maximum particle size distribution error of 12 wt%, and a maximum particle shape distribution error of 10 wt%; their accuracy was clearly lower than for falling aggregates. However, they performed well for single-graded aggregates, and did not require a dispersion device. Our system is low-cost and easy to install. It can successfully achieve online detection of aggregate size and shape with good reliability, and it has great potential for aggregate quality assurance.