Applying the similarity theory to model dust dispersion during coal-mine tunneling

Jiang, Wan; Xu, Xiangyu; Wen, Zhihui; Wei, Le

doi:10.1016/j.psep.2020.10.026

Cited by 49 publications

(13 citation statements)

References 12 publications

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“…Generally, the airflow state of the working surface is regarded as an incompressible fluid, and the continuity equation is 27 , 28 where ρ is the gas density (kg/m 3 ), and t is the time. When the airflow is in a steady state, the density does not change with time and can be written as …”

Section: Mathematical Modelmentioning

confidence: 99%

Research on dust dispersion law of fully mechanized mining faces under different inclinations and tracking closed dust control method

Zhou

Kong

Meng

et al. 2022

Sci Rep

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Based on the gas–solid two-phase flow theory, numerical simulation of the dust dispersion law of fully mechanized mining work under different inclination angles and comparative analysis of field-measured data show that with the increase of working face inclination, the inclination of airflow into the unmined zone increases from 25° to 50° and the maximum wind speed increases from 2.16 to 2.25 m/s after the mixing of cutting turbulent wind and system ventilation. Meanwhile, the range of high-concentration dust clusters, suspension time, lateral migration intensity, and deposition zone increase to varying degrees; dust clusters increases from 62.02 to 202.46 m3. When X < 53.96 m, the dust concentration in the sidewalk-breathing zone shows a sine function with the length of the working face, and when X ≥ 53.96 m, it satisfies the exponential decay function. Based on this, the tracking closed dust control technology is proposed. Combining the offset angle of the airflow and t the gathering position of dust mass, the wind curtain angle and air velocity are automatically controlled to ensure that the dust is restricted to one side of the cable trough.

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Section: Mathematical Modelmentioning

confidence: 99%

Research on dust dispersion law of fully mechanized mining faces under different inclinations and tracking closed dust control method

Zhou

Kong

Meng

et al. 2022

Sci Rep

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show abstract

“…The most important factor accompanying the rock mining process is dust. It is a harmful factor in a hard coal mine for many reasons [28,29]. It reduces visibility, can be explosive, and additionally, the respirable fraction [30] is harmful to human health.…”

Section: Testing the Impact Of Dust Concentration On The Propagation Time Of Ultrasonic Wavesmentioning

confidence: 99%

Impact of the Selected Disturbing Factors on Accuracy of the Distance Measurement with the Use of Ultrasonic Transducers in a Hard Coal Mine

et al. 2021

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The article presents tests on the possibility of using ultrasonic transducers for accurate distance measurement in hard coal mines. In order to check the impact of selected disturbing factors on the measurement results, test stands were built, and then a full cycle of measurements with the use of different transducers (AR30 and AR41), which were selected and pre-tested in previous research projects, was realized. The impact of such disturbing factors as airborne dust (coal, stone, lime and mixed dust), changes in temperature and humidity on the propagation of ultrasonic waves, amplitude and measurement accuracy was investigated. The tests were preceded by theoretical analysis. It was found that the transducers selected for the tests had a sufficient accuracy and range, so they can be used in the devices planned to be designed, allowing for the determining of the location of a roadheader in hard coal mine roadways, taking into account technical and legal restrictions. It was also specified which disturbing factors should be compensated and what methods and parameters of this compensation should be used.

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“…It is impossible to build a complete model of the excavation roadway by measurement and other methods due to environmental characteristics of the excavation roadway such as low illumination, high humidity, and high density of particulate dust [3][4][5], re ectivity changes caused by the blockage of large particles and dust in the air, the properties of the surface of the object, the material and transparency of the surface, etc., and characteristics of excavation roadways, such as harsh working conditions, narrow spaces, and complex environments, which cannot be characterized [6,7]. To construct the environment model around the excavation roadway, a suitable coordinate system is needed to merge the three-dimensional point clouds obtained from various perspectives into a unified coordinate system to form a complete data point cloud.…”

Section: Introductionmentioning

confidence: 99%

Establishment of a Coal Mine Roadway Model Based on Point Cloud Feature Matching

Yang

Luo

Zhang

et al. 2022

Mathematical Problems in Engineering

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A coal mine roadway is a longitudinally limited space with curves and branches, low illumination and high humidity, a large amount of dust, and an unstructured terrain environment. Traditional ICP algorithms have the defects of slow convergence speed and it is easy to fall into local optimums. While the NDT algorithm in the NDT + ICP algorithm has high registration efficiency, poor stability, and low registration accuracy, which are not suitable for point clouds with noise and a large amount of data. By calculating the FPFH value, the detailed description of the point cloud will be greatly increased to increase the robustness and accuracy Therefore, a feature registration method based on the FPFH + ICP algorithm is proposed to reduce the modeling error of excavation roadways and meet the requirements of intelligent excavation. First, outliers caused by dust are treated by the Euclidean clustering point cloud segmentation method, and then the calculation of the normal vector in the FPFH feature descriptor is optimized based on extracting key points from the roadway structure. The surface normal vector of each key point and its neighborhood point is estimated according to the measured point and its neighborhood point. The initial coordinate transformation matrix of a point cloud of an excavated roadway is obtained by the SAC-IA algorithm and transferred to the ICP algorithm. Finally, KD-tree is introduced into the ICP algorithm to accelerate the search speed of corresponding point pairs, and the Gauss–Newton method is used to optimize the solution of the nonlinear objective function of the algorithm to complete accurate registration of point clouds in an excavation roadway.

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Applying the similarity theory to model dust dispersion during coal-mine tunneling

Cited by 49 publications

References 12 publications

Research on dust dispersion law of fully mechanized mining faces under different inclinations and tracking closed dust control method

Research on dust dispersion law of fully mechanized mining faces under different inclinations and tracking closed dust control method

Impact of the Selected Disturbing Factors on Accuracy of the Distance Measurement with the Use of Ultrasonic Transducers in a Hard Coal Mine

Establishment of a Coal Mine Roadway Model Based on Point Cloud Feature Matching

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Applying the similarity theory to model dust dispersion during coal-mine tunneling

Cited by 49 publications

References 12 publications

Res﻿earch on dust dispersion law of fully mechanized mining faces under different inclinations and tracking closed dust control method

Res﻿earch on dust dispersion law of fully mechanized mining faces under different inclinations and tracking closed dust control method

Impact of the Selected Disturbing Factors on Accuracy of the Distance Measurement with the Use of Ultrasonic Transducers in a Hard Coal Mine

Establishment of a Coal Mine Roadway Model Based on Point Cloud Feature Matching

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Product

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Research on dust dispersion law of fully mechanized mining faces under different inclinations and tracking closed dust control method

Research on dust dispersion law of fully mechanized mining faces under different inclinations and tracking closed dust control method