Wan Lirong, Wang Jiantao, Zeng Qingliang, Ma Dejian, Yu Xuehui, Meng Zhaosheng
College of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao 266590, China.
College of Information Science and Engineering, Shandong Normal University, Jinan 250358, China.
ACS Omega. 2022 Jan 19;7(4):3656-3670. doi: 10.1021/acsomega.1c06279. eCollection 2022 Feb 1.
The existing research on coal gangue identification based on vibration usually assumes that coal gangue particles are ideal shapes. To understand the vibration response difference in hydraulic support caused by coal and gangue with real shapes, this paper uses a three-dimensional (3D) scanning technology to determine the real shape of coal particles. The process of coal and gangue impacting the tail beam at different angles was simulated in the LS-DYNA software package, and the effects of shape parameters, velocity, and coal strength on the difference in vibration signals caused by the two were analyzed statistically. The conclusions are as follows: the vibrational response of the tail beam is concentrated mainly in the area between the ribs. The regularity of the velocity signal caused by gangue is better than the regularity of the velocity signal caused by coal, and the attenuation speed of the acceleration signal of gangue is slower than the attenuation speed of the acceleration signal of coal. The probability distributions of the velocity and acceleration responses were analyzed statistically, and the results show that the results from coal can be well fitted by a logarithmic normal function, and the standard deviations of velocity and acceleration are 0.05591 and 489.8, respectively. The gangue results are fitted by the gamma function and the Weibull function, and the standard deviations are 0.13531 and 737.9, respectively, showing that the fitting function has the potential to be used as the basis for coal gangue identification. The change in coal strength has little effect on the vibration response of the tail beam. With increasingly falling velocity, the vibration signal intensity of the tail beam increases, but the discrimination between coal and gangue weakens; therefore, measures should be taken to reduce the falling velocity of the rock mass. The research results of this paper can provide a reference for further study of coal gangue identification methods based on vibration.
现有的基于振动的煤矸石识别研究通常假定煤矸石颗粒为理想形状。为了解真实形状的煤与矸石在液压支架中引起的振动响应差异，本文采用三维（3D）扫描技术确定煤颗粒的真实形状。在LS-DYNA软件包中模拟了煤和矸石以不同角度撞击尾梁的过程，并对形状参数、速度和煤强度对两者引起的振动信号差异的影响进行了统计分析。结论如下：尾梁的振动响应主要集中在肋板之间的区域。矸石引起的速度信号规律性优于煤引起的速度信号规律性，矸石加速度信号的衰减速度慢于煤加速度信号的衰减速度。对速度和加速度响应的概率分布进行了统计分析，结果表明煤的结果可用对数正态函数很好地拟合，速度和加速度的标准差分别为0.05591和489.8。矸石的结果用伽马函数和威布尔函数拟合，标准差分别为0.13531和737.9，表明该拟合函数有潜力作为煤矸石识别的依据。煤强度的变化对尾梁的振动响应影响较小。随着下落速度的增加，尾梁的振动信号强度增加，但煤与矸石之间的区分度减弱；因此，应采取措施降低岩体的下落速度。本文的研究结果可为进一步研究基于振动的煤矸石识别方法提供参考。
