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Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine
BACKGROUND: Spontaneous combustion of coal is one of the factors which causes direct or indirect gas and dust explosion, mine fire, the release of toxic gases, loss of reserve, and loss of miners' life. To avoid these incidents, the prediction of spontaneous combustion is essential. The safety...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Occupational Safety and Health Research Institute
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7502667/ https://www.ncbi.nlm.nih.gov/pubmed/32995058 http://dx.doi.org/10.1016/j.shaw.2020.06.005 |
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author | Danish, Esmatullah Onder, Mustafa |
author_facet | Danish, Esmatullah Onder, Mustafa |
author_sort | Danish, Esmatullah |
collection | PubMed |
description | BACKGROUND: Spontaneous combustion of coal is one of the factors which causes direct or indirect gas and dust explosion, mine fire, the release of toxic gases, loss of reserve, and loss of miners' life. To avoid these incidents, the prediction of spontaneous combustion is essential. The safety of miner's in the mining field can be assured if the prediction of a coal fire is carried out at an early stage. METHOD: Adularya Underground Coal Mine which is fully mechanized with longwall mining method was selected as a case study area. The data collected for 2017, by sensors from ten gas monitoring stations were used for the simulation and prediction of a coal fire. In this study, the fuzzy logic model is used because of the uncertainties, nonlinearity, and imprecise variables in the data. For coal fire prediction, CO, O(2), N(2), and temperature were used as input variables whereas fire intensity was considered as the output variable.The simulation of the model is carried out using the Mamdani inference system and run by the Fuzzy Logic Toolbox in MATLAB. RESULTS: The results showed that the fuzzy logic system is more reliable in predicting fire intensity with respect to uncertainties and nonlinearities of the data. It also indicates that the 1409 and 610/2B gas station points have a greater chance of causing spontaneous combustion and therefore require a precautional measure. CONCLUSION: The fuzzy logic model shows higher probability in predicting fire intensity with the simultaneous application of many variables compared with Graham's index. |
format | Online Article Text |
id | pubmed-7502667 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Occupational Safety and Health Research Institute |
record_format | MEDLINE/PubMed |
spelling | pubmed-75026672020-09-28 Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine Danish, Esmatullah Onder, Mustafa Saf Health Work Original Article BACKGROUND: Spontaneous combustion of coal is one of the factors which causes direct or indirect gas and dust explosion, mine fire, the release of toxic gases, loss of reserve, and loss of miners' life. To avoid these incidents, the prediction of spontaneous combustion is essential. The safety of miner's in the mining field can be assured if the prediction of a coal fire is carried out at an early stage. METHOD: Adularya Underground Coal Mine which is fully mechanized with longwall mining method was selected as a case study area. The data collected for 2017, by sensors from ten gas monitoring stations were used for the simulation and prediction of a coal fire. In this study, the fuzzy logic model is used because of the uncertainties, nonlinearity, and imprecise variables in the data. For coal fire prediction, CO, O(2), N(2), and temperature were used as input variables whereas fire intensity was considered as the output variable.The simulation of the model is carried out using the Mamdani inference system and run by the Fuzzy Logic Toolbox in MATLAB. RESULTS: The results showed that the fuzzy logic system is more reliable in predicting fire intensity with respect to uncertainties and nonlinearities of the data. It also indicates that the 1409 and 610/2B gas station points have a greater chance of causing spontaneous combustion and therefore require a precautional measure. CONCLUSION: The fuzzy logic model shows higher probability in predicting fire intensity with the simultaneous application of many variables compared with Graham's index. Occupational Safety and Health Research Institute 2020-09 2020-06-26 /pmc/articles/PMC7502667/ /pubmed/32995058 http://dx.doi.org/10.1016/j.shaw.2020.06.005 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original Article Danish, Esmatullah Onder, Mustafa Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine |
title | Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine |
title_full | Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine |
title_fullStr | Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine |
title_full_unstemmed | Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine |
title_short | Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine |
title_sort | application of fuzzy logic for predicting of mine fire in underground coal mine |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7502667/ https://www.ncbi.nlm.nih.gov/pubmed/32995058 http://dx.doi.org/10.1016/j.shaw.2020.06.005 |
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