Study of strata behaviour in longwall workings

Dec 2018 / by P. Raghupathi, G. Budi, R. M. Battacharjee and A. K. Sinha

Coal has been one of the energy resources of the country and it is extracted from earth crust by different methods. Longwall mining is the most popular and productive method of coal mining in the world. Majority of the longwall mines in India have not become as successful as they were envisaged. The main reasons for the underperformance of the longwalls in India, among others, have been strata control problems due to inadequate geological and geotechnical assessment, poor understanding of strata behaviour and selection of under rated supports. Complex strata mechanics issues like excessive stress concentrations, strata dilation or convergence of roof strata in longwall workings are potential hazard of strata failure. Therefore, proper understanding of geo-mechanics of strata and continuous strata monitoring in longwall workings is prerequisite for its effective control and ensuring safe workings. This paper discusses the strata control problems in Indian longwall mines and presents the instrumentation for strata monitoring. It also suggests a general scheme of strata monitoring in a longwall workings and explains a case study.
Keywords: Longwall mining, strata behaviour, strata monitoring, instrumentation

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Research on risk assessment of debris flow in a mining area in western China based on the game theory empowering normal cloud theory

Dec 2018 / by Li Li, Qiang Yue and Li Shaohong

Risk assessment of debris flow is an uncertain problem involving randomness and fuzziness. The cloud model is used to distinguish for assessing the risk of debris flow scientifically and rationally. Firstly, the system standard of debris flow risk assessment is constructed; secondly, impact factor of each assessment system which belonging to cloud droplet of each risk level produced by normal cloud generator, the subjective weights and objective weights of the debris flow influence factors are coupled by using game theory, and consider the fuzziness of debris flow basic data, using the Monte Carlo modelling thought, and by generating large cloud droplets and statistics of the average value in a mini zone near the basic data for evaluating debris flow as the basic data belonging to some hierarchical average degree of certainty; finally, the proposed model is used for case research, and compared to several existing mature methods to prove the proposed model is feasible and reasonable.
Keywords: Debris flow, risk assessment, cloud model, game theory, Monte Carlo modelling

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A recognition method of mineral shape based on extreme learning machine

Dec 2018 / by Ding Dehong, Li Wuke, Li Hao and Li Ling

In view of the situation of the existing algorithm for mineral shape recognition is relatively complex, the individual of strong pertinence and poor robustness, the use of infrared thermal images of minerals multifractal feature data classification recognition method is put forward. Multifractal can describe not only the local details, but also the overall characteristics that has the scale independence and theoretically is suitable for describing the texture characteristics and the distribution of mineral as well as that of energy resource. This paper uses multifractal as parameters of singularity detection of highdimensional data and learning and understanding of highdimensional data to distinguish the object/target from infrared heat map. The experimental result show that the infrared thermal image of mineral target in line with the multifractal characteristics, which can be used as one of the effective methods of infrared thermal images detection target. When three kinds of neural network ELM, PNN, GRNN is used for machine learning with obtain fractal parameters, ELM’s accuracy is as high as 84%. While the same training with face natural images is done, ELM is still best, but accuracy is less than 15%. It shows that ELM combining with mineral fractal data has a better performance in classification and pattern recognition.
Keywords: Mineral recognition, mineral shape, feature data classification, extreme learning machine

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Research on change of micro-structure and mechanical performance Si/C matrix composites for thermal process

Dec 2018 / by Ding Dehong, Zhao Shuang and Wen Yan

Silicon carbide fiber reinforced silicon carbide composite material (Si/C) is a highly promising high-temperature structural material. The Si/C composites are prepared by means of the precursor impregnation (PIP) process. Under inert atmosphere, 1399-1801°C temperature range of Si/C composites for thermal process, as temperature measurement with infrared thermal imaging device tool monitoring temperature of the material, thermal process temperature on the Si/C composites are studied the effect of the microstructure and mechanical performance. The results show that the 1399°C composites matrix crystallization degree increased after thermal process, the overall mechanical performance increase. While the temperature is rising further, the fiber of composite material is damaged, and the mechanical property also is decreased rapidly.
Keywords: Si/C matrix composite, thermal process, micro-structure, mechanical performance, infrared thermometer

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Prediction and application of mine roadway surrounding rock deformation based on AdaBoost-GA-ELM-model

Dec 2018 / by Qiang Yue, Wu Shuang, Liu Chaoqiong and Li Shaohong

Aiming at the shortcomings of one-sole-model with low accuracy and instability in the deformation prediction for mine roadway surrounding rock, this article comes up with an AdaBoost-GA-ELM model, which combines the ideas of AdaBoost algorithm, genetic algorithm and extreme learning machine, is proposed. The verification of engineering example about trough roof and floor section, I01091004 working surface, Tun-Bao coal mine shows that the AdaBoost-GA-ELM model has almost equal shares in the area of mine roadway surrounding rock deformation, which can bring gratifying prediction results, compared to GAELM, GA-BP and gray model, the prediction accuracy of which has a better effect, containing certain value for engineering application.
Keywords: Mine roadway engineer; surrounding rock deformation; ELM; genetic algorithm; AdaBoost algorithm

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UAV applications on projects monitoring in mining and civil engineering

Dec 2018 / by Ramesh Murlidhar Bhatawdekar, Suryanshu Choudhury and Edy Tonnizam Modmad

Worldwide all the industries have endorsed immense technology driven exponential growth since last two to three decades. Focus of every industry’s focus is on the improved utilization of the assets by improving machine productivity, automation, optimization which goes in hand in hand with the safer and environment friendly operation. Unmanned aerial vehicle (UAV) has wider application with advancement of various technologies – accuracy in geographical position system (GPS), high resolution digital camera, development of various sensors, processing power of computers and software development. Application of the unmanned arial vehicle (UAV) is one of such technology driven solution which is upcoming during last one decade to almost all mining and civil engineering projects of the performance improvements, reducing the cost of production, safe operating practices etc. Present paper focusses upon the implication of UAVs projects monitoring of the mining engineering projects.UAV is useful in exploration for preparation of topographical maps, identification of different rock types, airborne survey. UAV technology ensures the availability of miniature global navigation satellite system (GNSS). Number of critical situations during mining operation are handled with the ability of quick delivery of high temporal and spatial resolution image information. Digitized terrain models (DTM) are developed based on images captured by UAV which can be imported in autodesk or mine planning software – Surpac, Datamine etc. Various volumetric calculations can be done for OB removal, excavation, waste dump and stockpiles of minerals by measurement through photogrammetric method. With UAV advancement of faces can be monitored periodically. Due to the vastness of the modern mining engineering projects, the monitoring and control of different activities need the adoption of UAV based solutions on real time basis. The imagery and video acquired through UAV can be processed through photogrammetry software to develop two dimensional orthoimages and 3-dimensional surface models. The data acquired and products generated are fully compatible with AutoCAD and other civil 3D design software. Legal framework in very country is being formed. Legal implications and liability are to be examined. Project authorities for every project has to consider pros and cons before deployment of UAV technology.Location and movement of heavy earthmoving machinery is monitored including maintenance activities. Fragmentation of blasted rock, blast volume can be estimated with the support of UAV. Any hazardous work can be monitored remotely on UAV platform. During closure stage slope monitoring, reclamation of land which can be reviewed with the help of UAV. UAV technology is also useful in emergency in handling any breakdown, disaster or accidents at mines.
Keywords: Unmanned aerial vehicle (UAV), projects monitoring, mining engineering, civil engineering, photogrammetry software

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A calibration method based on dual quadratic fitting and nine parameters for mining non-cooled infrared thermal imager

Dec 2018 / by Ding Dehong, Cui Daijun and Li Ling

Infrared detection method is mainly used to detect infrared energy field, through which the spontaneous combustion zone of coal can be comprehensively judged. In order to ensure the accuracy of the temperature of the test target under the mine, the paper mainly studies the calibration method of the uncooled infrared imager under the influence of the environment temperature, distance, the effect of the working temperature of the detector and the other factors. A new method of calibration model of dual quadratic fitting and the calibration equation of nine parameters method are proposed. Compared to existing methods, the proposed method is used to process the experiment, and it is concluded that the average error is within 1oC, which can meet the requirements of temperature measurement-thermal imaging under the mine.
Keywords: Mining non-cooled infrared thermal imager, dual quadratic fitting, nine parameters, calibration steps, downhole temperature, anomalous region

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