Safety and Health at Work Vol. 11 Issue 3 2020
Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine (Original Article)
Dublin Core
Title
Safety and Health at Work Vol. 11 Issue 3 2020
Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine (Original Article)
Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine (Original Article)
Subject
fire intensity, fuzzy logic model, mine fire prediction, spontaneous combustion
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, O2, N2, 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.
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, O2, N2, 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.
Creator
Esmatullah Danish, Mustafa Onder
Publisher
Elsevier Korea LLC
Date
September 2020
Contributor
Sri Wahyuni
Format
PDF
Language
English
Type
Text
Coverage
Safety and Health at Work Vol. 11 Issue 3 2020
Files
Citation
Esmatullah Danish, Mustafa Onder, “Safety and Health at Work Vol. 11 Issue 3 2020
Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine (Original Article),” Repository Horizon University Indonesia, accessed December 22, 2024, https://repository.horizon.ac.id/items/show/2007.
Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine (Original Article),” Repository Horizon University Indonesia, accessed December 22, 2024, https://repository.horizon.ac.id/items/show/2007.