Research on quality monitoring technology of fertilizer granulation based on deep learning

Tao Wang; Linli Zhou; Jiahao Shui; Jianqiao Xiong

doi:10.1117/12.2656485

20 October 2022 Research on quality monitoring technology of fertilizer granulation based on deep learning

Tao Wang, Linli Zhou, Jiahao Shui, Jianqiao Xiong

Proceedings Volume 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022); 124514R (2022) https://doi.org/10.1117/12.2656485
Event: 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 2022, Chongqing, China

Abstract

Fertilizer is the food of grain, which has a decisive impact on grain yield. The granulation particle size of fertilizers is one of the important factors affecting product quality. Today, fertilizer production plants still observe the granulation particle size manually. This method is timeconsuming, labor-intensive, and unstable. For this reason, this study uses computer vision technology and high-speed cameras to quickly capture fertilizer granulation particles, uses a control system to control industrial cameras to capture particle size, and then train and optimize the neural network model. Achieve the monitoring of fertilizer granulation production quality, adjust the production factors in real time, and improve the production quality. Finally, it can replace manual work and accomplish unmanned and intelligent granulation detection.

Citation Download Citation

Tao Wang, Linli Zhou, Jiahao Shui, and Jianqiao Xiong "Research on quality monitoring technology of fertilizer granulation based on deep learning", Proc. SPIE 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 124514R (20 October 2022); https://doi.org/10.1117/12.2656485

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