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Novel Coal Gangue Mixing Ratio Sensing Technique Based on Synthetic Parity-Time Symmetry

  • Yuanhong Meng
  • , Zhenyu Liang
  • , Zhiwei Guo
  • , Xiaoqiang Su
  • , Yanhong Liu
  • , Fusheng Deng
  • , Caixia Feng
  • , Lijuan Dong*
  • , Weidong Hu*
  • *此作品的通讯作者
  • Shanxi Datong University
  • Tongji University
  • Beijing Institute of Technology

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

In the process of comprehensive mechanized caving coal mining, the monitoring technology for coal gangue mixing ratios at coal discharge outlets has long relied on manual experience judgment, lacking automated monitoring methods. This has led to widespread overdischarge or underdischarge phenomena during coal release, severely affecting mining efficiency and quality. To address this technical challenge, this article innovatively designs and develops an integrated sensing monitoring system based on the parity-time (PT) symmetry principle. By constructing a three-coil LC resonant circuit system, we utilize the high-sensitivity characteristics of third-order PT symmetry at exceptional points (EPs) to achieve stable monitoring of resonant frequency variations. Experimental results show that the sensitivity enhancement factor of the synthetic third-order PT system reaches up to 1.8 times that of second-order systems, effectively detecting frequency differences caused by changes in coal gangue mixture dielectric constants. Based on this, we establish a quantitative relationship model between coal gangue ratios and resonant frequencies, enabling precise determination of mixing ratios. Additionally, combining synthetic dimension theory, we design a sensing system with PT symmetric circuit architecture, achieving high-sensitivity monitoring of minute gangue ratio variations. This sensing monitoring system not only significantly reduces equipment size but also demonstrates excellent detection accuracy and stability. It provides reliable technical support for improving coal quality and achieving automated mining in coal mine working faces, playing a significant role in advancing intelligent development in the coal industry.

源语言英语
页(从-至)7670-7679
页数10
期刊IEEE Sensors Journal
卷26
期5
DOI
出版状态已出版 - 2026
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