Abstract
One of major threat to underground coal mines and miner's life is a fire hazard. It is important to foresee conditions leading to the fire hazard by proper interpretation of the data from underground coal mine air monitoring stations. The article describes new method for analyzing measured data. The method applies a fuzzy logic and its inference mechanisms to improve reliability in decision making process. The analysis utilizes measured data from information related to changes in composition of gases in underground mine and uncertainty of monitoring sensors. The method was tested in fire simulating setting utilizing underground measurement equipment. Fuzzy models of fire hazard conditions where design with help of LabVIEW. The correlation between model structure and interpretation of the result is presented.
| Original language | English |
|---|---|
| Pages (from-to) | 345-351 |
| Number of pages | 7 |
| Journal | Journal of Intelligent and Fuzzy Systems |
| Volume | 26 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2014 |
Keywords
- Exogenous fire assessment
- Expert systems
- Fire hazard detection
- Fuzzy logic
- Gas measurements
- Knowledge based systems
- Underground fire
ASJC Scopus subject areas
- Statistics and Probability
- General Engineering
- Artificial Intelligence
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