Assessment of Different Technologies for Improving Visibility during Foggy Weather in Mining and Transportation Sectors

Generally during foggy weather in winter season, mining operation remains suspended for hours due to problem of visibility. Foggy weather also leads to accidents, loss of life and infrastructure damages in mining and transportation sectors. This paper discusses about the existing technologies for improving visibility in transportation sector and suitability assessment of these technologies in mines for uninterrupted mining operations in foggy weathe

Performance Analysis of IoT-based underground miner’s tracking and wireless voice communication system

This paper addresses an integrated wireless-fidelity (Wi-Fi) and radio frequency identification (RFID) based wireless system which has been developed for tracking of miners, wireless communication between miners and officials on surface. The system provides a walk through model in mine display and can predict mine-hazards. The system has been developed for providing emergency response using Internet of Things (IoT) enabled devices for tracking of trapped miners in a particular underground mine located using monitoring system and thereby sends real-time location to the concerned management and rescue team. The network performance has been analysed to assess the maximum operating distance, packet delivery ratio (PDR) and data communication capabilities. PDR was 6-7% more in normal surface conditions than mine environment for same transmission distance. This network analysis shows that with increase in distance between miner and the end device, the PDR decreases. Also increases in the number of hops in between end device and mine coordinator reduces the PD

Prediction of Strata Monitoring System in Underground Coal Mines Using IoT

Underground coal mines are known for being one of the most hazardous sectors due to its working environment. The mine workers are usually prone to many risk factors leading to heavy casualties. As per the statistical records of Directorate General of Mines Safety, roof fall is one of the major causes of accident in Indian underground coal mines. One of the critical contributing factors of such accidents is lack of roof fall prediction system, thereby leading to failure to withdraw or removal of working persons before the actual failure. Real-time monitoring of strata movement and analysing the acquired data for predicting possible roof fall well in advance through an effective intelligent system can certainly pave way in reducing the accidents due to roof fall. The paper presents an integrated strata management system for continuous monitoring of strata behaviour and analysing the data using artificial intelligence for prediction of failure of strata ahead of time. This web-based monitoring system initially sets the customizable threshold values according to the mine conditions followed by continuously monitoring of the strata conditions including triggering an alarm system when the retrieved data crosses the set threshold limit

Modernization of Indian coal mining industry: Vision 2025

28-35In view of vision 2025, CIMFR, Dhanbad has developed a web-based information and decision support system for coal mining industry. Paper summaries scope of proposed IT based system by highlighting existing problems and proposed solutions under different modules, and briefly enumerates the methodology to develop the proposed system

Studies on radio frequency propagation characteristics for underground coalmine communications

418-422A basic understanding of the behaviour of electromagnetic wave propagation through strata is the fundamental requirement to design a suitable wireless communication system for underground mines. Background information on radio propagation and its limitations, in a particular confined space can be known only after the measurement. Both electromagnetic propagation studies and modelling of propagation coverage, ultimately help in selecting the best suitable frequency and designing appropriate wireless communication system for underground mine. The paper discusses different aspects for propagation modelling and the experiment conducted in the laboratory to understand the propagation characteristics through coal. It is found that 6 MHz frequency is the best suitable frequency for propagation of electromagnetic wave through coal

Intelligent dry fog dust suppression system: an efficient technique for controlling air pollution in the mineral processing plant

Dust suppression system plays a significant role in mining and allied industries. It has become an integral part of the environmental management system. Dust emission from mining and mineral processing industries poses environmental and health problems to workers and surrounding people. Dust creates a reliability issue in machinery and ventilation systems, causing infrastructural damage and the industry’s financial losses. This paper deals with a smart dry fog dust suppression system which has been developed for effectively controlling dust emission from mining and mineral processing activities. The system has been implemented in an iron ore crushing and screening plant in India, and its efficacy has been evaluated for controlling dust emission. The installed dry fog system reduced dust concentration to 0.10–0.17 mg m−3 from the prevailing dust concentration of 0.62–1.73 mg m−3 in work zone areas, which was much below the permissible limit below 1 mg m−3 where silica content in the dust was less than 5%. Percentage of free silica in the work zone dust reduced to traces from 3.61 to 4.80%. Similarly, PM10 and PM2.5 concentrations in the ambient air were decreased to 90–99 μg m−3 and 49–58 μg m−3 from 185 to 250 μg m−3 and 148–200 μg m−3, respectively. Further, concentrations of PM10 and PM2.5 were drastically reduced by 51.35–60.4% and 69.69–71.0%, respectively. The reduced dust concentrations in the ambient air were within the prescribed limit of PM10 (100 μg m−3) and PM2.5 (60 μg m−3). The system significantly reduces dust and free silica concentration in the work zone areas below the permissible limit. The system controls dust emission with an increase in production as it has been found that the number of nozzles is directly correlated with a reduction in dust. Furthermore, the system does not change the raw material’s mass as water added to dust is less than 0.01% of the raw material. The system is designed to give the best results within the closed environment of the plant. The system helps in eco-friendly and clean mining. The system reduces the breakdown and maintenance cost of mining equipment, thereby decreasing overall operating costs. Further, the system minimizes mine workers’ health problems, like silicosis and severe other occupation diseases. The system is automatic, cost-effective, energy efficient, and easy to maintain. Further, the system is capable of handling dust problems in the closed environment of crushing and screening plants. These properties make the system techno-economically feasible for installation in mineral processing plants

Wireless information and safety system for mines

107-117This study presents a wireless information and safety system for mines developed by CIMFR, Dhanbad. System consists of hardware devices and application software. Hardware module is ZigBee-compliant active radio frequency identification (RFID) devices/ transceivers, which can be programmed to act as end device (tag), router or coordinator that enables them to form an IEEE 802.15.4-based mesh network. It uses a unified wireless mesh-networking infrastructure to locate, trace and manage mobile assets and people as well as monitor different environmental conditions using sensors. Another core module is wireless sensor network (WSN) software, which is developed for tracking of underground miners and moveable equipment by wireless sensor networking in mines. Software is especially designed for tracking of miners and vehicles, route tracking in opencast mines, preventing fatal accidents and vehicle collisions, environmental monitoring, observing miners’ unsafe practice, sending alert message, and preparing computerized miners’ duty hour

t-SNE and variational auto-encoder with a bi-LSTM neural network-based model for prediction of gas concentration in a sealed-off area of underground coal mines

A deep learning network is introduced to predict concentrations of gases in the underground coal mine enclosed region using various IoT-enabled gas sensors installed in a metallic gas chamber. The air is sucked automatically at specific intervals from the sealed-off site utilizing a solenoid valve, suction pump, and programmed microprocessor. The gas sensors monitor the gas content in the underground coal mine and communicate gas concentration to the surface server room through a wireless network and cloud storage media. The t-SNE_VAE_bi-LSTM model is proposed in this study as a prediction model that combines the t-SNE, VAE, and bi-LSTM networks. The proposed model's t-SNE method aims to minimize the dimensionality of the recorded gas concentration; and VAE layer intends to retrieve the inner characteristics of low-dimensional gas concentration. Finally, the given model's Bi-LSTM layer tries to forecast the concentrations of CH4, CO2, CO, O2, and H2 gases. The proposed model's prediction accuracy is compared with the existing two models, namely auto-regressive integrated average moving (ARIMA) and chaos time series (CHAOS). The experiment findings demonstrate that the t-SNE_VAE_bi-LSTM model forecasted mean square error (MSE) is more accurate, and it has lesser MSE value of 0.029 and 0.069 for CH4; 0.037 and 0.019 for CO2; 0.092 and 0.92 for CO; 1.881 and 1.892 for O2; and 1.235 and 1.200 for H2 than the ARIMA and CHAOS models, respectively

Assessment of Coal Mine Road Dust Properties for Controlling Air Pollution

The paper describes analytical results of physico�chemical parameters and proximate analysis of coal dust collected from road surface of four opencast coal mines located in different coalfields of India. Value of pH, water holding capacity, ash percentage, moisture content, volatile matter, bulk density, specific gravity and fixed carbon was found to be in the range of 5.1–7.7, 21.17−31.71%, 45−76%, 0.5−3.0%, 12.6−20.0%, 1.15–1.70 g cm−3, 1.73–2.30, and 10.2–45.3%, respectively. The study revealed that the coal dust abundantly available on road surface of opencast coal mines may be used as domestic fuel. Hence, collection and utilization of coal dust accumulated on mine road would not only reduce air pollution in mining regions but also help in enhancing economic benefit of coal mining industry by selling waste coal dust as domestic fuel