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Seeding Status Monitoring System for Toothed-Disk Cotton Seeders Based on Modular Optoelectronic Sensors

Author

Listed:
  • Tao Jiang

    (College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China)

  • Xuejun Zhang

    (College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China
    Xinjiang Key Laboratory of Smart Agricultural Equipment, Urumqi 830052, China)

  • Zenglu Shi

    (College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China
    Xinjiang Key Laboratory of Smart Agricultural Equipment, Urumqi 830052, China)

  • Jingyi Liu

    (College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China)

  • Wei Jin

    (College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China
    Xinjiang Key Laboratory of Smart Agricultural Equipment, Urumqi 830052, China)

  • Jinshan Yan

    (College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China
    Xinjiang Key Laboratory of Smart Agricultural Equipment, Urumqi 830052, China)

  • Duijin Wang

    (Xinjiang Tiancheng Agricultural Machinery Manufacturing Company Limited, Tiemenguan 841007, China)

  • Jian Chen

    (Xinjiang Tiancheng Agricultural Machinery Manufacturing Company Limited, Tiemenguan 841007, China)

Abstract

In precision cotton seeding, the toothed-disk precision seeder often experiences issues with missed seeding and multiple seeding. To promptly detect and address these abnormal seeding conditions, this study develops a modular photoelectric sensing monitoring system. Initially, the monitoring time window is divided using the capacitance sensing signal between two seed drop ports. Concurrently, a photoelectric monitoring circuit is designed to convert the time when seeds block the sensor into a level signal. Subsequently, threshold segmentation is performed on the time when seeds block the photoelectric path under different seeding states. The proposed spatiotemporal joint counting algorithm identifies, in real time, the threshold type of the photoelectric sensor’s output signal within the current monitoring time window, enabling the differentiation of seeding states and the recording of data. Additionally, an STM32 micro-controller serves as the core of the signal acquisition circuit, sending collected data to the PC terminal via serial port communication. The graphical display interface, designed with LVGL (Light and Versatile Graphics Library), updates the seeding monitoring information in real time. Compared to photoelectric monitoring algorithms that detect seed pickup at the seed metering disc, the monitoring node in this study is positioned posteriorly within the seed guide chamber. Consequently, the differentiation between single seeding and multiple seeding is achieved with greater accuracy by the spatiotemporal joint counting algorithm, thereby enhancing the monitoring precision of the system. Field test results indicate that the system’s average accuracy for single-seeding monitoring is 97.30%, for missed-seeding monitoring is 96.48%, and for multiple-seeding monitoring is 96.47%. The average probability of system misjudgment is 3.25%. These outcomes suggest that the proposed modular photoelectric sensing monitoring system can meet the monitoring requirements of precision cotton seeding at various seeding speeds.

Suggested Citation

  • Tao Jiang & Xuejun Zhang & Zenglu Shi & Jingyi Liu & Wei Jin & Jinshan Yan & Duijin Wang & Jian Chen, 2025. "Seeding Status Monitoring System for Toothed-Disk Cotton Seeders Based on Modular Optoelectronic Sensors," Agriculture, MDPI, vol. 15(15), pages 1-20, July.
  • Handle: RePEc:gam:jagris:v:15:y:2025:i:15:p:1594-:d:1709190
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    References listed on IDEAS

    as
    1. Shenghe Bai & Yanwei Yuan & Kang Niu & Zenglu Shi & Liming Zhou & Bo Zhao & Liguo Wei & Lijing Liu & Yuankun Zheng & Sa An & Yihua Ma, 2022. "Design and Experiment of a Sowing Quality Monitoring System of Cotton Precision Hill-Drop Planters," Agriculture, MDPI, vol. 12(8), pages 1-14, July.
    2. Ling Ren & Shuang Wang & Bin Hu & Tao Li & Ming Zhao & Yuquan Zhang & Miao Yang, 2023. "Seed State-Detection Sensor for a Cotton Precision Dibble," Agriculture, MDPI, vol. 13(8), pages 1-18, July.
    3. Seung-Jun Kim & Hyeon-Seung Lee & Seok-Joon Hwang & Jeong-Hun Kim & Moon-Kyeong Jang & Ju-Seok Nam, 2023. "Development of Seeding Rate Monitoring System Applicable to a Mechanical Pot-Seeding Machine," Agriculture, MDPI, vol. 13(10), pages 1-18, October.
    Full references (including those not matched with items on IDEAS)

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