Quantitative evaluation of the influence of coal particle size distribution on gas diffusion coefficient by image processing method

被引:8
|
作者
Liu, Jingjing [1 ]
Cheng, Deqiang [1 ]
Li, Yunlong [1 ]
Zhao, Kai [1 ]
Kou, Qiqi [2 ]
机构
[1] China Univ Min & Technol, Sch Informat & Control Engn, Xuzhou 221116, Jiangsu, Peoples R China
[2] China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 221116, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Image processing; Particle size distribution; Diffusion coefficient; Laser particle analyzer; Coal particles; SHAPE;
D O I
10.1016/j.fuel.2021.122946
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Coal particles have been widely used to measure the gas diffusion coefficient which is a key parameter to characterize the gas diffusion behavior, and the average particle size is a necessary parameter for calculating the diffusion coefficient. At present, people often use the arithmetic mean of upper and lower sieve surface specifications to characterize the average diameter of coal particles, which has large errors. It is necessary to obtain the particle size distribution in advance to determine the average diameter scientifically and accurately. A laser particle analyzer is usually used to measure particle size distribution, but due to the limitation of its measurement principle, it has poor measurement accuracy for irregular and large particles. In this article, we offer an integrated approach for quantitative evaluation of the influence of coal particle size distribution on gas diffusion coefficient. Laser particle analyzer and image analysis were used to measure the particle size distribution of 6 coal samples with the size range of 1 similar to 2 mm. Based on obtaining the size distribution, the average diameter was calculated. Then the diffusion coefficient was calculated by using the average diameter obtained by different methods. The results show that the particle size distribution measured by the laser method has a large deviation and poor repeatability, and the volume mean diameter calculated by it is far less than the arithmetic mean value of 1.5 mm. The imaging method can extract the morphological data of each particle, and so the obtained particle size distribution is more accurate and reliable. The equivalent area mean diameter calculated by the image method is close to 1.5 mm. The average diameter obtained by considering the particle size distribution can more truly reflect the particle size characteristics of coal samples, while the conventional method of using the arithmetic mean to calculate the diffusion coefficient will produce a non-negligible deviation. This also reveals the importance of obtaining particle size distribution when using the particle method to solve the diffusion coefficient.
引用
收藏
页数:11
相关论文
共 50 条
  • [11] Influence of particle size distribution on colloidal processing of alumina
    Tari, G
    Ferreira, JMF
    Fonseca, AT
    Lyckfeldt, O
    JOURNAL OF THE EUROPEAN CERAMIC SOCIETY, 1998, 18 (03) : 249 - 253
  • [12] The desorption laws and diffusion model of coal gas in different particle size
    Wang, Cuixia
    Li, Shugang
    Liu, Jikun
    Qin, Yueping
    Shen, Zhuo
    PROGRESS IN MINE SAFETY SCIENCE AND ENGINEERING II, 2014, : 363 - 368
  • [13] An image segmentation method of pulverized coal for particle size analysis
    Li, Xin
    Li, Shiyin
    Dong, Liang
    Su, Shuxian
    Hu, Xiaojuan
    Lu, Zhaolin
    INTERNATIONAL JOURNAL OF MINING SCIENCE AND TECHNOLOGY, 2023, 33 (09) : 1181 - 1192
  • [14] Influence of particle size distribution on coal dust explosion sensitivity
    Ren, Xiaofeng
    Li, Hao
    Xuan, Wufan
    Li, Yongtun
    Teng, Chenzi
    Liu, Chang
    POWDER TECHNOLOGY, 2025, 457
  • [15] An image segmentation method of pulverized coal for particle size analysis
    Xin Li
    Shiyin Li
    Liang Dong
    Shuxian Su
    Xiaojuan Hu
    Zhaolin Lu
    International Journal of Mining Science and Technology, 2023, 33 (09) : 1181 - 1192
  • [16] THE INFLUENCE OF PARTICLE-SIZE DISTRIBUTION OF COAL ON THE FLUIDITY OF COAL WATER MIXTURES
    TODA, M
    KURIYAMA, M
    KONNO, H
    HONMA, T
    POWDER TECHNOLOGY, 1988, 55 (04) : 241 - 245
  • [17] Study on Soil Particle Size Distribution by Digital Image Processing
    Hou, Jianshu
    ADVANCED RESEARCH ON MATERIAL ENGINEERING, CHEMISTRY AND ENVIRONMENT, 2013, 788 : 627 - 630
  • [18] Effect of particle size on difference of gas desorption and diffusion between soft coal and hard coal
    Liu, Yan-Wei
    Liu, Ming-Ju
    Meitan Xuebao/Journal of the China Coal Society, 2015, 40 (03): : 579 - 587
  • [19] A novel particle size distribution correction method based on image processing and deep learning for coal quality analysis using NIRS-XRF
    Gao, Rui
    Yin, Jiaxin
    Liu, Ruonan
    Liu, Yang
    Li, Jiaxuan
    Dong, Lei
    Ma, Weiguang
    Zhang, Lei
    Zhang, Peihua
    Tian, Zhihui
    Zhao, Yang
    Yin, Wangbao
    Jia, Suotang
    TALANTA, 2025, 285
  • [20] STUDY ON DEFOCUSED IMAGE PROCESSING METHOD FOR PARTICLE SIZE MEASUREMENT
    Hu, J. R.
    Zhou, W.
    Cai, X. S.
    PARTICLE SCIENCE AND ENGINEERING, 2014, 347 : 52 - 61