Abstract
From the view of underground coal mining safety system, it is extremely important to continuous monitoring of coal mines for the prompt detection of fires or related problems inspite of its uncertainty and imprecise characteristics. Therefore, evaluation and inferring the data perfectly to prevent fire related accidental risk in underground coal mining (UMC) system are very necessary. In the present article, we have proposed a novel type-2 fuzzy logic system (T2FLS) for the prediction of fire intensity and its risk assessment for risk reduction in an underground coal mine. Recently, for the observation of underground coal mines, wireless underground sensor network (WUSN) are being concerned frequently. To implement this technique IT2FLS, main functional components are sensor nodes which are installed in coal mines to accumulate different imprecise environmental data like, temperature, relative humidity, different gas concentrations etc. and these are sent to a base station which is connected to the ground observation system through network. In the present context, a WUSN based fire monitoring system is developed using fuzzy logic approach to enhance the consistency in decision making system to improve the risk chances of fire during coal mining. We have taken Mamdani IT2FLS as fuzzy model on coal mine monitoring data to consider real-time decision making (DM). It is predicted from the simulated results that the recommended system is highly acceptable and amenable in the case of fire hazard safety with compared to the wired and off-line monitoring system for UMC. Legitimacy of the suggested model is prepared using statistical analysis and multiple linear regression analysis.
Highlights
The productivity, quality and safety performance of an UMC systems are highly influenced by the environmental states of it
We have proposed a novel type-2 fuzzy logic system (T2FLS) for the prediction of fire intensity and its risk assessment for risk reduction in an underground coal mine
For the observation of underground coal mines, wireless underground sensor network (WUSN) are being concerned frequently. To implement this technique IT2FLS, main functional components are sensor nodes which are installed in coal mines to accumulate different imprecise environmental data like, temperature, relative humidity, different gas concentrations etc. and these are sent to a base station which is connected to the ground observation system through network
Summary
The productivity, quality and safety performance of an UMC systems are highly influenced by the environmental states (uncertain or fuzzy) of it. The major factors that influence the different uncertain environmental conditions of an underground coal mines (UCM) are, airflow, temperature, humidity, dust and gases. These operations are essentially responsible for the generation of various toxic gases like, H2S, CO2, CO, etc. WSN (Akyildiz and Stuntebeck 2006) has developed like a crucial technique in continuous monitoring of an industrial workplace or in an UCM It can be recognized by involving sensor nodes in proper positions of underground mines to gather environmental data and to detect the occurrences of probable risks like fires, explosions, gas leaks or roof failures etc. (6) A robust T2FLC model is developed to evaluate the instant updates of mine fire risk chances from the UCM imprecise data
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