Technology of intelligent sensing of longwall shield supports status and roof strata based on massive shield pressure monitoring data

被引：0
|
作者：
Cheng J. [1 ,2 ]
Wan Z. [1 ,2 ]
Peng Syd S. [3 ]
Zhang H. [4 ]
Xing K. [1 ]
Yan W. [1 ]
Liu S. [1 ]
机构：
[1] School of Mines, China University of Mining and Technology, Xuzhou
[2] State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Xuzhou
[3] Department of Mining Engineering, West Virginia University, Morgantown
[4] School of Energy and Mining Engineering, China University of Mining and Technology (Beijing), Beijing
来源：
Meitan Xuebao/Journal of the China Coal Society | 2020年 / 45卷 / 06期
关键词：
Characteristic parameters of multi-dimensional working cycle; Intelligent analysis of mine pressure; Intelligent sensing; Longwall face; Longwall shield supports; Massive data of shield pressure;
D O I：
10.13225/j.cnki.jccs.ZN20.0353
中图分类号：
学科分类号：
摘要：
It is of great importance to sense the roof weighting and roof caving in advance and self-evaluate initial resistance and working resistance for promoting the safety, efficiency and intelligent mining level in longwall penal.Based on the scientific principles of intelligent sensing of supports-roof status, this paper used the massive data collected by the electro-hydraulic controlled two-leg shield supports, data mining and working cycle analysis technique to extract the characteristic parameters.Then the supporting characteristics of a single support and the load transformation and distribution on the longwall panel considering setting pressure, yielding, and shearer's cutting, as well as neighboring shields' advance were investigated.On the basis of in-depth explanation on the temporal-sequence curve of supporting resistance and the indicating relationship between support and surrounding rocks, the intelligent sensing model was constructed.The study concludes that ① the rated working pressure should not be employed as the main indicator for evaluating the loading capacity of hydraulic support.Parameters, such as initial support pressure, rated working resistance and safety valve opening characteristics, would co-determine the bearing characteristics and capacity of hydraulic support.② By analyzing the massive data of support pressure, the goals of intelligent roof disaster warning, support quality evaluation and fault diagnosis can be achieved.③ The in-depth analysis and utilization of massive monitored pressure data is the foundation to realize intelligent mining goals such as the self-control of hydraulic support pressure and adaptive adjustment of support parameters. © 2020, Editorial Office of Journal of China Coal Society. All right reserved.
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页码：2090 / 2103
页数：13
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