ZHANG Yongqi, WANG Jie, ZHOU Yuhao, et al. Research status and development trends of dust concentration monitoring technology[J]. Journal of Mine Automation,2024,50(12):111-119, 165. DOI: 10.13272/j.issn.1671-251x.2024100076
Citation: ZHANG Yongqi, WANG Jie, ZHOU Yuhao, et al. Research status and development trends of dust concentration monitoring technology[J]. Journal of Mine Automation,2024,50(12):111-119, 165. DOI: 10.13272/j.issn.1671-251x.2024100076

Research status and development trends of dust concentration monitoring technology

  • This paper introduces the measurement principles of various domestic and international dust concentration continuous monitoring technologies, including the filter weighing method, β-ray method, light scattering method, charge induction method, and micro-oscillating balance method. It compares and analyzes the advantages and limitations of these monitoring technologies in terms of accuracy, sensitivity, and real-time performance. The paper also delves into the continuous separation technologies and standards for respirable dust particles on a global scale and systematically examines the challenges that current dust concentration continuous monitoring technologies face in terms of instrumental measurement precision, reliability, stability, environmental adaptability, intelligent automatic calibration, and power consumption optimization. The discussion covers the development trends in dust concentration monitoring technology: the shift from traditional single total dust concentration monitoring to a combined monitoring of total and respirable dust, and rapid transition from point monitoring to area monitoring and regional monitoring. It is proposed that future efforts should be dedicated to integrating dust concentration monitoring technologies with emerging technologies such as machine learning, deep learning, computer vision, and big data analysis and prediction. This integration will facilitate the integration and application of intelligent detection technologies with dust-related occupational hazard monitoring and early warning systems and provide reference for intelligent and automated dust control in future industrial scenarios.
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