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Prakash, A.
- Chip Size Characterization for Selecting Optimum Production Parameters of Surface Miner Operating in a Coal Mine
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PDF Views:119
Authors
Affiliations
1 Central Institute of Mining and Fuel Research, Dhanbad 826 015, IN
2 Department of Mining Engineering, Indian School of Mines, Dhanbad 826 004, IN
1 Central Institute of Mining and Fuel Research, Dhanbad 826 015, IN
2 Department of Mining Engineering, Indian School of Mines, Dhanbad 826 004, IN
Source
Current Science, Vol 108, No 3 (2015), Pagination: 422-426Abstract
Coal production using surface miner technology is a well-accepted method today in Indian coal mines contributing a sizeable proportion to the overall production. Production of coal chips of desired size is an important parameter in surface miner performance evaluation in terms of tonnes per hour as well as fulfilment of the need of the consumers. The demand for an average chip size in the range 100-150 mm thermal power plants is growing and this size also fetches a premium price compared to blasted lumpy coal. A field study was conducted at Sonepur Bazari opencast mine, Eastern coalfields (ECL), West Bengal, India for evaluating the cutting operation and performance of a 2200 SM surface miner under varied operational and rock mass conditions. An imaging technique coupled with Fragalyst software was used for grabbing and analysing the sizes of chips produced by surface miner. The wide variation in chip size formation observed in the field was due to the fluctuations in cutting speed and also the presence of joints. This communications reports the study carried out on surface miner to develop a new methodology for characterizing chip size, fixing the optimum machine operating parameters for a desired chip size and also the production potential.Keywords
Surface Miner Technology, Chip Size, Coal Production, Rock Mass.- Hierarchy of Parameters Influencing Cutting Performance of Surface Miner through Artificial Intelligence and Statistical Methods
Abstract Views :208 |
PDF Views:86
Authors
Affiliations
1 CSIR-Central Institute of Mining and Fuel Research, Dhanbad 826 015, IN
2 Department of Mining Engineering, Indian School of Mines, Dhanbad 826 004, IN
1 CSIR-Central Institute of Mining and Fuel Research, Dhanbad 826 015, IN
2 Department of Mining Engineering, Indian School of Mines, Dhanbad 826 004, IN
Source
Current Science, Vol 112, No 06 (2017), Pagination: 1242-1249Abstract
Applicability of a surface miner (SM) must be based on a careful assessment of intact rock and rock mass properties. A detailed literature review was made to identify different parameters influencing the performance of various types of cutting machines deployed in different parts of the world. The critical parameters influencing the production, diesel consumption and pick consumption of SM in Indian coal and limestone mines, were identified through artificial neural network (ANN) technique and screened by correlation coefficient analysis. Parameters that were common in both ANN and correlation analysis were grouped under critical category and others in semi-critical category.Keywords
Artificial Neural Network, Intact Rock, Rock Mass, Surface Miner.References
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