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Forecasting Spontaneous Heating Susceptibility of Indian Coals Using Neuro Fuzzy System

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Abstract

Coal mine fires due to spontaneous heating have been a great concern both for the industry and researchers worldwide. They start in a very small scale and gradually expand in size resulting in environmental, safety and economic concerns. Most of these fires could be averted if suitable preventive measures are taken. Since the spontaneous heating potential of all types of coals are not the same, its accurate forecasting is essential to plan efficient preventive measures, production schedule and storage capabilities of a mine. This study presents a neuro-fuzzy approach for forecasting the auto-oxidation of coals based on laboratory test results on fifty cone coal samples collected from different coalfields of India. Using the constituents of proximate analysis as input parameters, crossing point temperature (CPT) is predicted using adaptive neuro-fuzzy inference system (ANFIS) model. Gaussian membership function has been adopted for describing the input variables. The results indicate that ANFIS model can predict CPT values with reasonable accuracy.

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Acknowledgments

The authors are thankful to the Director of National Institute of Technology, Rourkela for his permission to publish this paper. The views expressed are of the authors and not necessarily of the organisations to which they belong. The authors are also thankful to the anonymous reviewers for their suggestions, which have helped in improving the technical content of the paper.

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  1. Department of Mining Engineering, National Institute of Technology, Rourkela, 769 008, India

    H. B. Sahu

  2. Department of Mechanical Engineering, National Institute of Technology, Rourkela, 769 008, India

    S. S. Mahapatra

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  1. H. B. Sahu
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  2. S. S. Mahapatra
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Correspondence to H. B. Sahu.

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Sahu, H.B., Mahapatra, S.S. Forecasting Spontaneous Heating Susceptibility of Indian Coals Using Neuro Fuzzy System. Geotech Geol Eng 31, 683–697 (2013). https://doi.org/10.1007/s10706-013-9618-6

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