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Research on Grain Temperature Detection Based on Rational Sound-Source Signal

Author

Listed:
  • Hongyi Ge

    (Key Laboratory of Grain Information Processing & Control, Ministry of Education, Henan University of Technology, Zhengzhou 450001, China
    Henan Provincial Key Laboratory of Grain Photoelectric Detection and Control, Zhengzhou 450001, China
    College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China)

  • Bo Feng

    (Key Laboratory of Grain Information Processing & Control, Ministry of Education, Henan University of Technology, Zhengzhou 450001, China
    Henan Provincial Key Laboratory of Grain Photoelectric Detection and Control, Zhengzhou 450001, China
    College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China)

  • Yuying Jiang

    (Key Laboratory of Grain Information Processing & Control, Ministry of Education, Henan University of Technology, Zhengzhou 450001, China
    Henan Provincial Key Laboratory of Grain Photoelectric Detection and Control, Zhengzhou 450001, China
    School of Artificial Intelligence and Big Data, Henan University of Technology, Zhengzhou 450001, China)

  • Yuan Zhang

    (Key Laboratory of Grain Information Processing & Control, Ministry of Education, Henan University of Technology, Zhengzhou 450001, China
    Henan Provincial Key Laboratory of Grain Photoelectric Detection and Control, Zhengzhou 450001, China
    College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China)

  • Chengxin Cai

    (Key Laboratory of Grain Information Processing & Control, Ministry of Education, Henan University of Technology, Zhengzhou 450001, China
    Henan Provincial Key Laboratory of Grain Photoelectric Detection and Control, Zhengzhou 450001, China
    College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China)

  • Chunyan Guo

    (Key Laboratory of Grain Information Processing & Control, Ministry of Education, Henan University of Technology, Zhengzhou 450001, China
    Henan Provincial Key Laboratory of Grain Photoelectric Detection and Control, Zhengzhou 450001, China
    College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China)

  • Heng Wang

    (Key Laboratory of Grain Information Processing & Control, Ministry of Education, Henan University of Technology, Zhengzhou 450001, China
    Henan Provincial Key Laboratory of Grain Photoelectric Detection and Control, Zhengzhou 450001, China
    College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China)

  • Ziyu Liu

    (Key Laboratory of Grain Information Processing & Control, Ministry of Education, Henan University of Technology, Zhengzhou 450001, China
    Henan Provincial Key Laboratory of Grain Photoelectric Detection and Control, Zhengzhou 450001, China
    School of Artificial Intelligence and Big Data, Henan University of Technology, Zhengzhou 450001, China)

  • Xinxin Liu

    (National Grain and Oil Information Center, Beijing 100834, China)

Abstract

The selection of sound-source signals is a pivotal aspect of temperature measurement in stored grain using the acoustic method, as their characteristics directly influence the propagation effects of sound waves in grain media and the accuracy of temperature measurement. To identify a sound-source signal with optimal propagation performance, this study focused on analyzing the signal attenuation levels of typical sound sources, including simulated pulse signals and linear swept signals, during propagation. The results demonstrated that the linear swept signal exhibited superior propagation characteristics in grain media, with significantly lower signal attenuation compared to other sound-source signals. Specifically, a linear swept signal with a duration of 0.5 s and a frequency range of 200 Hz to 1000 Hz showed the best propagation performance. Finally, based on this rational signal, the temperature of grain samples was measured, yielding a mean absolute error of 1.62 °C.

Suggested Citation

  • Hongyi Ge & Bo Feng & Yuying Jiang & Yuan Zhang & Chengxin Cai & Chunyan Guo & Heng Wang & Ziyu Liu & Xinxin Liu, 2025. "Research on Grain Temperature Detection Based on Rational Sound-Source Signal," Agriculture, MDPI, vol. 15(10), pages 1-17, May.
    • Handle: RePEc:gam:jagris:v:15:y:2025:i:10:p:1035-:d:1653259
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    References listed on IDEAS

    as
    1. Benjamin Plumier & Dirk Maier, 2021. "Effect of Temperature Sensor Numbers and Placement on Aeration Cooling of a Stored Grain Mass Using a 3D Finite Element Model," Agriculture, MDPI, vol. 11(3), pages 1-14, March.
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