New insights on ground control in intelligent mining with Internet of Things

Abstract The conception of Smart city has been gaining momentum in recent years. Coal mines as a part of city should be characterized with smart or intelligent features. Production and safety are two major themes in coal mining. With the development of automation, Internet of Things (IoT), big data, artificial intelligence, and cloud computing in Fourth Industrial Revolution, Intelligence Mining has been put forward by Chinese Academy of Engineering to achieve the goal of unmanned workface production. However, safety is not highlighted in the novel idea. In this paper, ground control in intelligent mining with IoT is studied. An architecture of ground control with IoT is proposed. The previous research on theoretical modeling and on-site monitoring methods are reviewed. Then the IoT based ground control method is proposed. An on-going dynamic platform on ground control are proposed based on our research of nondestructive testing (NDT) on rock bolt anchorage quality assessment. The research progress is introduced with equipment introduction, principles, and an on-site experiment. Future developments on combination of NDT and IoT of ground control is discussed. The ideas, frameworks, and results in this paper can make efforts on safety control and spark new ideas in the much-anticipated Intelligence Mining.

[1]  Byung-Wan Jo,et al.  A Fiber Bragg Grating-Based Condition Monitoring and Early Damage Detection System for the Structural Safety of Underground Coal Mines Using the Internet of Things , 2018, J. Sensors.

[2]  Zilong Zhou,et al.  Effects of height/diameter ratio on failure and damage properties of granite under coupled bending and splitting deformation , 2019, Engineering Fracture Mechanics.

[3]  Yang Hao,et al.  An innovative yielding prop with high stable load capacity and long shrinkage distance in coal mine , 2019 .

[4]  Xing Huang,et al.  Application and prospect of hard rock TBM for deep roadway construction in coal mines , 2018 .

[5]  Yujing Jiang,et al.  Influence of confining pressure-dependent Young’s modulus on the convergence of underground excavation , 2019, Tunnelling and Underground Space Technology.

[6]  Yaodong Jiang,et al.  Fracture evolution law and control technology of roadways with extra thick soft roof , 2018 .

[7]  Shanyong Wang,et al.  Mechanical tests and engineering applicability of fibre plastic concrete used in tunnel design in active fault zones , 2019, Tunnelling and Underground Space Technology.

[8]  Jamal Rostami,et al.  Review of Ground Characterization by Using Instrumented Drills for Underground Mining and Construction , 2016, Rock Mechanics and Rock Engineering.

[9]  Xibing Li,et al.  Effects of seepage-induced erosion on nonlinear hydraulic properties of broken red sandstones , 2019, Tunnelling and Underground Space Technology.

[10]  Yuan Guangxiang.  RETROSPECTIVE ANALYSIS OF TBM ACCIDENTS FROM ITS POOR FLEXIBILITY TO COMPLICATED GEOLOGICAL CONDITIONS , 2007 .

[11]  Hadi Fattahi,et al.  Feasibility of Monte Carlo simulation for predicting deformation modulus of rock mass , 2019, Tunnelling and Underground Space Technology.

[12]  Byung-Wan Jo,et al.  An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning , 2018, Sensors.

[13]  Yang Hao,et al.  The Load Capacity Model and Experimental Tests of a New Yielding Steel Prop , 2017 .

[14]  V. B. Maji,et al.  Performance Prediction of Rock TBMS Considering Uncertainties in the Geotechnical Parameters , 2015 .

[15]  M. Pradhan,et al.  Development of a model to estimate strata behavior during bord and pillar extraction in underground coal mining , 2019, Arabian Journal of Geosciences.

[16]  Kamran Ali,et al.  A WSN for Monitoring and Event Reporting in Underground Mine Environments , 2018, IEEE Systems Journal.

[17]  Dan Ma,et al.  Effect of particle erosion on mining-induced water inrush hazard of karst collapse pillar , 2019, Environmental Science and Pollution Research.

[18]  Jian Zhou,et al.  Predicting pillar stability for underground mine using Fisher discriminant analysis and SVM methods , 2011 .

[19]  Wu He,et al.  Internet of Things in Industries: A Survey , 2014, IEEE Transactions on Industrial Informatics.

[20]  Arash Ebrahimabadi,et al.  Prediction of roadheaders' performance using artificial neural network approaches (MLP and KOSFM) , 2015 .

[21]  Zhu Shunbing,et al.  Study On Key Technologies Of Internet Of Things Perceiving Mine , 2011 .

[22]  Jing Tao,et al.  Non-destructive inspection on anchorage defect of hollow grouted rock bolt using wavelet transform analysis , 2018, EURASIP J. Image Video Process..

[23]  Feng Du,et al.  Automation in U.S. longwall coal mining: A state-of-the-art review , 2019, International Journal of Mining Science and Technology.

[24]  Lalatendu Muduli,et al.  Application of wireless sensor network for environmental monitoring in underground coal mines: A systematic review , 2017, J. Netw. Comput. Appl..

[25]  Xiangyu Wang,et al.  Response and control technology for entry loaded by mining abutment stress of a thick hard roof , 2016 .

[26]  Hua Guo,et al.  Displacement, stress and seismicity in roadway roofs during mining-induced failure , 2008 .

[27]  Murat Alp,et al.  Assessment of the factors affecting the advance rate of the Tunnel Gerede, the longest and one of the most problematic water transmission tunnels of Turkey , 2019, Tunnelling and Underground Space Technology.

[28]  Fuqiang Gao,et al.  A physical and numerical investigation of sudden massive roof collapse during longwall coal retreat mining , 2018 .

[29]  Athanasios V. Vasilakos,et al.  A review of industrial wireless networks in the context of Industry 4.0 , 2015, Wireless Networks.

[30]  Mohammad Ataei,et al.  An intelligent approach to predict pillar sizing in designing room and pillar coal mines , 2014 .

[31]  Xiexing Miao,et al.  Non-destructive testing and pre-warning analysis on the quality of bolt support in deep roadways of mining districts , 2017 .

[32]  Robert X. Gao,et al.  Deep learning and its applications to machine health monitoring , 2019, Mechanical Systems and Signal Processing.

[33]  Masoud Monjezi,et al.  Application of artificial intelligence algorithms in predicting tunnel convergence to avoid TBM jamming phenomenon , 2012 .

[34]  Syd S. Peng,et al.  Topical areas of research needs in ground control – A state of the art review on coal mine ground control , 2015 .

[35]  Jaydip Sen,et al.  Internet of Things - Applications and Challenges in Technology and Standardization , 2011 .

[36]  Feng Gao,et al.  Theoretical and technological exploration of deep in situ fluidized coal mining , 2019, Frontiers in Energy.

[37]  Ray Y. Zhong,et al.  Intelligent Manufacturing in the Context of Industry 4.0: A Review , 2017 .

[38]  Jian-guo Li,et al.  Intelligent Mining Technology for an Underground Metal Mine Based on Unmanned Equipment , 2018, Engineering.

[39]  Hua Zhu,et al.  Mobile platform of rocker-type coal mine rescue robot , 2010 .

[40]  Nan Zhou,et al.  Mechanism by Which Backfill Body Reduces Amount of Energy Released in Deep Coal Mining , 2019, Shock and Vibration.

[41]  Yunliang Tan,et al.  A new approach for predicting bedding separation of roof strata in underground coalmines , 2013 .

[42]  Enrique Alba,et al.  Smart City and information technology: A review , 2019, Cities.

[43]  Masoud Monjezi,et al.  An intelligent approach to predict unconfined compressive strength of rock surrounding access tunnels in longwall coal mining , 2012, Neural Computing and Applications.

[44]  Guofa Wang,et al.  Intelligent and ecological coal mining as well as clean utilization technology in China: Review and prospects , 2019, International Journal of Mining Science and Technology.

[45]  Yang Hao,et al.  Non-destructive testing on anchorage quality of hollow grouted rock bolt for application in tunneling, lessons learned from their uses in coal mines , 2019, Tunnelling and Underground Space Technology.

[46]  Marimuthu Palaniswami,et al.  An Information Framework for Creating a Smart City Through Internet of Things , 2014, IEEE Internet of Things Journal.

[47]  M. F. Marji,et al.  A 3D numerical model to determine suitable reinforcement strategies for passing TBM through a fault zone, a case study: Safaroud water transmission tunnel, Iran , 2019, Tunnelling and Underground Space Technology.

[48]  Davide Elmo,et al.  Numerical modelling of the effects of weak immediate roof lithology on coal mine roadway stability , 2012 .

[49]  Mahdi Shabanimashcool,et al.  A numerical study of stress changes in barrier pillars and a border area in a longwall coal mine , 2013 .

[50]  Kai Wang,et al.  A dynamic information platform for underground coal mine safety based on internet of things , 2019, Safety Science.