Informatics Publishing Limited

Anand Kumar ¹, Pusker Singh ¹, Sanjay Kumar Sharma ¹, Nawal Kishore ¹, C. S. Singh ¹

Affiliations
1 Department of Mining Engineering, Indian Institute of Technology (BHU), Varanasi 221 005, IN

Abstract

Blast-induced ground vibration (BIGV) velocities and frequencies are of major concern due to their adverse effects and damage to structures. Therefore, it becomes essential to assess the velocities and frequencies induced by blasting in terms of quantitative and qualitative assessment to overcome the problems. There is a need for scientific studies using devices like triaxial geophone associated with a seismograph to measure the peak particle velocity (PPV) and dominant frequency which cause damage to domestic or residential structures near an opencast mine. Each mine has specific geo-mining conditions, and scientific studies provide appropriate results. In total, 32 number of blasting data sets were recorded at every 50 m from the blast site to the last observation point near the village. Ground vibration associated damage criteria is defined in terms of the PPV at different frequency levels and the strength of the structures under study. The permissible limits of BIGV has been provided by the Directorate General of Mines Safety, Dhanbad, India. The permissible PPV values of the BIGV in India is 2, 5, 10 for the historical and sensitive structures, 5, 10, 15 for domestic houses and 10, 20, 25 for industrial buildings at 25 Hz dominant excitation frequencies respectively. The recorded dataset has been proposed through standard models. The velocity amplitude versus frequency gives a reliable relationship about damage criteria of structures. The structures were analysed vis-à-vis PPV and dominant frequency to correlate the damage possibility. The present study carried out in a mega opencast project provides the basic knowledge to assess the safe distance from blasting site for specific charge of explosive, waves which are responsible for more damage to nearby structures and to determine the correlation coefficient between measured and predicted PPV values.

Keywords

Frequency, Ground Vibration, Opencast Mine, Peak Particle Velocity, Structural Response.

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ANAND KUMAR ¹, SANJAY KUMAR SHARMA ¹, NAWAL KISHORE ¹

Affiliations
1 Department of Mining Engineering, IIT (BHU), Varanasi 221005, IN

Abstract

The consumption of hydrocarbon is increasing day by day. A number of technologies are being used to meet out the demanded quality. The drilling and blasting is a cheapest way to exploration and excavation in mining industries. The blasting creates excessive amount of energy in different form of ground vibration as shaking of Earth, flyrock, removal and transportation of overburden rockmass and other noise. Blast-induced ground vibration has some adverse effects on surrounding environment as well as community living nearby the opencast mine. The study was conducted at opencast coal mine in Chhattisgarh. A total number of 32 data sets have been measured with different parameters such as; maximum charge per delay (MCPD), observation distance, charge length, spacing, burden, blast hole depth, hole diameter, etc. as well as peak particle velocity (PPV), frequency and peak vector sum (PVS). In present study, main focus on measurement and prediction of peak particle velocity by different predictor model (USBM, Indian Standard, DGMS) and multi-variate statistical regression analysis (MVSRA). Simple linear regression model (SLRM) is used to determine the site characteristics constants. The constants are used to establish new prediction model equations among different parameters. Finally, assess the blast induced ground vibration on the basis of measured and predicted peak particle velocity.

Keywords

Blasting, ground vibration, PPV, maximum charge per delay, MVSRA

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Vikram Seervi ¹, Nawal Kishore ¹, Amit Kumar Verma ¹

Affiliations
1 Department of Mining Engineering, IIT-BHU Varanasi 221005, Uttar Pradesh, IN

Abstract

With the expansion of mines for higher rated outputs, the operation of a dragline in tandem has gained significance in the field. The tandem operation enhances capacity utilization of draglines which are highly capital-intensive equipment. To maximize the return on investment and improve the dragline’s performance, its mode of operation and influencing parameters must be understood and carefully analysed. The balancing diagram (a graphical representation of dragline cuts and spoil geometry) for the draglines operating in tandem is the most essential tool to deploy the dragline successfully. This task manually is normally both difficult and time-consuming and requires an analytical solution. This is best suited to the application of computer graphics methods. Therefore, a balancing diagram in a 3-dimensional graphics package has been developed to assist the mine planner in planning dragline operations. The purpose of this paper is to select the most appropriate mode of dragline operation, operating in tandem, and by analysing the two indices, i.e., rate of coal exposure and percentage rehandle. The analysis will be case studyoriented with practical mining considerations and comparatives indices being formulated for better understanding. In the present study, field data pertaining to the dragline operations have been collected from one of the prestigious mines of Northern Coalfields Limited, a subsidiary of Coal India Limited, and an attempt has been made to decide the mode of operation under the existing field conditions.

Keywords

Balancing diagram, 3-dimensional balancing diagram, tandem operation, rate of coal exposure, rehandling percentage.

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Vikram Seervi ¹, Nilesh Pratap Singh ¹, Nawal Kishore ², Rajeev Verma ³

Affiliations
1 PhD Research Scholar, Department of Mining Engineering, IIT-BHU, Varanasi - 221005, Uttar Pradesh, India;, IN
2 Assistant Professor, Department of Mining Engineering, IIT-BHU, Varanasi - 221005, Uttar Pradesh, India., IN
3 Assistant Professor, Department of Mining Engineering, College of Technology and Engineering, Udaipur - 313001, Rajasthan, India., IN

Abstract

Dragline operations play a major role in the overall production of coal in open cast mining. Hence, it becomes necessary to maximize the working hours and minimize the idle and breakdown hours as it affects the overall production of a mine. There is also a shortage of skilled labour for dragline operations and combined with the time-to-time breakdown of dragline, it results in a production deficit. In this study, extensive research is carried out using machine learning algorithms on data obtained from one of the largest opencast mines in Singrauli. The data consists of the parameters that were maintained by the staff on a regular basis, and the algorithm tried to learn the underlying patterns between the independent and dependent variables and find the correlation between the parameters that have a significant impact on productivity and breakdown, which were the dependent variables. The results obtained from the algorithms are encouraging and, with certain improvements in data collection procedures, can improve the prediction accuracy to an effective level. An increase in the frequency of data collection and expanding the data recording using sensors to the electrical and mechanical parameters along with the specific type of failure in the dragline machine will further improve the accuracy of the model and can provide beforehand information so that the machine could be handed over to maintenance department for the change of faulty parts and necessary precautions that can be taken to prevent the breakdown which will result in an overall reduction of idle and breakdown hours and increase in overall production.

Keywords

Artificial Neural Network, Breakdown Hours, Dragline, Machine Learning, Productivity

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