IR@CIMFR - Central Institute of Mining and Fuel Research (CSIR)
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2618 research outputs found
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Intelligent driving system at opencast mines during foggy weather
No full textThe fog in mining operations minimises the visibility, preventing drivers from a clear view, causing accidents and vehicle collisions. This paper provides an intelligent driving system for heavy earthmoving machinery operators in opencast mines, including hardware and software. Hardware contains high definition and thermal cameras, a global navigation satellite system (GNSS), radar, laser light, wireless devices, graphical processing unit, touch screen, etc. The software covers image stitching, image enhancement, and convolution neural network-based object detection. The display dashboard is divided into four windows. Each window represents a different view, i.e. 180° panorama view of the driving lane, GNSS tracking map, proximity radar detection view, and rear thermal camera view. An additional colour transfer method has been used in the existing image stitching method to reduce misalignment and ghost effect in the panorama output. The proposed method outperformed the existing methods, namely contrast limited adaptive histogram equalisation (CLAHE) and dark channel prior (DCP). The proposed image enhancement technique has increased contrast, entropy, and colour average by 0.069, 0.43, and 13.96, respectively, than CLAHE, and 0.994, 0.43, and 42.07 than DCP. The accuracy of the object detection model is 97%, and the overall processing time of all the algorithms is 0.44949 seconds
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
No full textA 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
Investigation of Failure Mechanism of Inclined Coal Pillars: Numerical Modelling and Tensorial Statistical Analysis with Field Validations
No full textAnalysis of the failure mechanism of inclined coal pillars is one of the complicated issues. The wide variability of dip angles of inclined coal pillars makes it more complex. The asymmetric stress distribution and the tendency of shearing along the bedding planes make the inclined coal pillars to behave differently from the flat coal pillars. There is a need for in-depth investigation of the failure mechanism for addressing the instability problems of the inclined coal pillars. Most of the literature quantifies only the magnitudes of the mean principal stresses by classical statistics. As the stress is a second-order tensor having six independent components, the classical statistics is not appropriate to calculate the mean and variability of the principal stresses at the onset of failure of the pillars. In this paper, a comprehensive analysis is done to understand the complex failure mechanism of the inclined coal pillar using numerical modelling as well as tensorial statistics and validated the results with field measurement data of failure cases. The failure mechanism is analysed by quantification of the characteristics of the inclined coal pillars by the principal-stress magnitude and its orientation, induced at the time of failure. Since the spatial variability of the magnitudes and orientations of the induced principal stresses exist within the inclined coal pillars, the mean induced principal stresses (σ1¯¯¯¯¯,σ2¯¯¯¯¯ and σ3¯¯¯¯¯) are used to quantify the stress states within it. The failure stress states within the coal pillars having different dip angles are generated by the calibrated elasto-plastic numerical modelling with the ubiquitous joint model. Several statistical parameters are calculated to quantify the stress-tensor variability and the correlation among the stress-tensor components. It is found that the correlation coefficients among the shear components increase significantly with the increase of the coal pillar dip angle. Therefore, the inclined coal pillars are highly susceptible to shear failure. The magnitudes, as well as orientations of the mean induced principal stresses within the coal pillars obtained through numerical modelling, are quantified by the tensorial as well as classical statistics. It is found that the magnitude of the mean major induced principal stress (σ1¯¯¯¯¯) at the time of failure, i.e. the strength of the pillar decreases with the increase of the dip angles. The validation of the results with the actual stress measurement data shows that all the failed pillar cases are correctly predicted by the tensorial statistical approach whereas the classical statistical approach does not effectively predict the actual failed condition of the pillars. The study would help to characterise the behaviour of the inclined pillars and address the instability issues for safe and efficient mining of inclined coal seams
Applicability of Low-Pressure CO2 and N2 Adsorption in Determining Pore Attributes of Organic-Rich Shales and Coals
No full textLow-pressure gas adsorption (LPGA) using N2 and CO2 has been widely used by researchers to evaluate the porous structures present within shales and coals. For a suite of shale and coal samples from India, a drop in the N2-BET specific surface area (SSA) was observed with an increase in total organic carbon content (TOC), with low-TOC shales showing a higher SSA than high-TOC shales and coals. Previous research works have demonstrated the limitations of using N2 at −196 °C to penetrate complex microporous structures in coals and thus yielding a low SSA. Likewise, the limitations of N2 to decipher complex porous structures in coals will hold for shales as well. An overall trend of decreased N2-SSA with increasing TOC content, especially for shales with TOC >10 wt %, and higher N2-SSA at lower TOC levels indicates that N2 does not completely detect the porous structures in organic-rich rocks. It mostly accesses the porous structures in minerals, thereby yielding a generally high SSA for low-TOC shales. In light of these facts, correlating and evaluating SSA in shales based on organic richness and thermal maturity levels can be misleading. On the other hand, while LPGA studies using CO2 are also debated, we propose an improved relationship between organic matter abundance and CO2-SSA in coals and shales
Tree responses to foliar dust deposition and gradient of air pollution around opencast coal mines of Jharia coalfield, India: gas exchange, antioxidative potential and tolerance level
No full textAtmospheric pollution by opencast mining activities affects tree species around the mining area. The present study evaluated the responses of five native tree species to air pollution in Jharia coalfield. Sites were selected as closest to farthest from the mining area. Foliar dust deposition and foliar sulphate content affected stomatal conductance, superoxide dismutase activity and ascorbic acid and, thus, increased the susceptibility of sensitive species. Ficus benghalensis and Butea monosperma showed maximum dust deposition, while Adina cordifolia showed minimum deposition. Maximum dust deposition in Ficus benghalensis lowered stomatal conductance and, thus, checked the flux of other acidic gaseous pollutants which led to minimum variation in leaf extract pH. Higher stomatal conductance in Adina cordifolia and Aegle marmelos, on the other hand, facilitated the entry of acidic pollutants and disrupted many biological functions by altering photosynthesis and inducing membrane damage. Low variations in Ficus religiosa, Ficus benghalensis and Butea monosperma with sites and seasons suggest better physiological and morphological adaptations towards pollution load near coal mining areas. Tree species with better adaptation resisted variation in leaf extract pH by effectively metabolising sulphate and, thus, had higher chlorophyll content and relative water content
Indoor Quality of Residential Homes and Schools of an Industrial Area in Asansol: Characterization, Bioaccessibility and Health Risk Assessment of Potentially Toxic Elements
No full textBioaccessibility of eight potentially toxic elements (PTEs), their human exposure and health risk assessments were determined in the indoor dust of residence and schools from the Asansol Industrial area, India. The PTEs concentrations were maximum during the winter both at houses and schools. The average PTEs concentrations throughout the year in Asansol were 3.16, 120, 156, 41708, 2354, 61.3, 115 and 345 mg.kg-1 for Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn respectively. X-ray powder diffraction indicated an abundance of quartz in the indoor dust. Principal component analysis (PCA) indicated multiple sources such as traffic, industries, and lithogenic sources for PTEs in indoor dust. Percentage of bioaccessibility was maximum for Cd (55.3% throughout the year). Total PTEs concentration and a bioaccessible fraction of PTEs both were used for health risk assessment, and non-carcinogenic health risk was <1 for total PTEs and the bioaccessible fraction of PTEs. Health risk of total PTEs’ (HItotal) for Mn was high for both children and adult (6.76E-01 and 1.3E-01, respectively). Monte Carlo simulation model indicated that all the cumulative probability of Hazard Quotient (HQ) for collectively eight metals was below 1
Trait of subsidence under high rate of coal extraction by longwall mining: some inferences
No full textTransformation in surface topography is a common phenomenon caused due to underground mining. With a view to focus outward, underground mining at a depth of 410 m although earlier considered as mothball is indispensable as on date to meet the production target. Subsidence investigation has been carried out over longwal panel no. 1 in Adriyala mine of Singareni Collieries Company Limited (SCCL) located in Godavari Valley Coalfield. The rate of face advance varied between 2.7 and 4.8 m/day. The present study envelops cementing relation of subsidence due to underground mining by longwall method with the active and old dumps, partially covered over the panel. Symmetric subsidence profile has been observed across the panel with higher angle of draw in dip side. Resettlement of dump led to higher vertical displacement and found to be an indispensable investigation for stability viewpoint. The angle of draw has been analyzed to be a controlling parameter with respect to the rate of face advance. The impact of subsidence on surface has been evaluated by constructing walls at maximum possible tensile zones and development of cracks after subsidence has been observed. Hydrogeological study has also been conducted, from seepage viewpoint, to evaluate the extent of damage in the strata for safe underground working. The investigation has been conducted during and after mining, with and without release of canal water, to assess the influence of seepage in ground. The assorted subsidence and hydrogeological investigations can be applied to interpret the extent of damage and for comprehensive understanding of the trait of cracks on the surface, in the strata and their continuity thereof
Secure decision tree twin support vector machine training and classification process for encrypted IoT data via Blockchain platform
No full textA secure decision tree twin support vector machine (DT-TSVM) multi-classification algorithm has been proposed in this paper for improving the reliability and security of the collected IoT data from multiple data providers. The multiclass secure DT-TSVM algorithm has been employed to train a machine learning model using the encrypted training dataset. The training dataset is collected via a blockchain platform. A blockchain method has been adopted to construct a secure and reliable distributed platform among dataset providers. The Paillier homomorphic cryptosystem has been applied for encrypting the IoT dataset. Then, the dataset has been recorded on the distributed ledger. The secure DT-TSVM algorithm's-based train model effectiveness has been compared with the other two available algorithms, namely the multiclass binary support vector machine (MBSVM) and one-to-one SVM algorithms. The experiment results showed that the privacy-preserving multiclass secure DT-TSVM-based model did not reduce the accuracy, but it increased the average precision and recall by 0.53% and 0.44% than MBSVM and 0.82% and 0.71% than one-to-one SVM, respectively. Further, the time consumption of data providers and data analysts did not change significantly with the increase of number of data provider
Evaluation of factors influencing surface water quality in a coalfield area of Damodar valley, India: a sustainable uses
No full textA systematic study on the major ions and heavy metals was carried out for surface water resources of EB coalfield for water quality assessment, source apportionment and studying the geochemical processes controlling the surface water quality. Seasonal effect was not very prominent for the surface water quality parameters inclusive of metals, though some dilution was observed in some parameters during the monsoon season. Some of the parameters exceeded the drinking water limits like TDS, turbidity, NO3−, F−, total hardness and Mg2+ in surface water. The Fe concentrations exceeded the desirable limit of the BIS standard in about 26% of the water sample. The surface water chemistry of the EB coalfield is influenced by extensive coal mining activities. The principal component analysis of metals and health concerning anions demonstrated that the data were synthesised into three loading factors with Eigen values >1 and explaining about 71.4% of the total variance. The extracted factors seem to indicate geogenic sources, coal mining and associated transportation. The quality assessment of the surface water for irrigation suitability suggested that the calculated parameters (SAR, %Na, RSC and MH) of water to be in the range of good to permissible; however, at a few sites, SAR values and MH make it unsuitable for irrigation. Thus, the study exemplified the need for awareness about the contamination of surface water within EB coalfield area. The findingsof the present study may be useful to decision-makers in developing plans for surface water quality management and sustainable use
Evaluation of load transfer mechanism under axial loads in a novel coupler of dual height rock bolts
No full textThe effective reinforcement of two or more overlying layers of mine openings in a single installation is usually done by coupling of two standard rock bolts mainly during the extraction of medium-thick coal seams. However, field observations show that the couplers of multiple bolts often degrade or break mostly at their connections. These types of failures can be avoided by strengthening the couplers of such multi-bolts assemblies. To achieve this, a novel threaded coupler system with an expansion shell was suggested in this paper. The newly designed coupler consists of a threaded tapered-plug-cum-connector with an expansion shell for connecting and tightening two standard rock bolts. An analytical model for evaluating the load distribution along the coupler subject to axial load was derived. Numerical analysis was performed to analyse the load transfer, deformation, and strains across the coupler including the factor of safety for the bolt-coupler-resin and bolt-coupler-expansion shell. The results validated the analytical model of the proposed coupler design, which provides better anchorage near the interface of the host rock mass. Thus, the developed coupler design would reduce the failures of the proposed coupler and stabilize laminated roof strata above the medium-thick coal seams in underground mines