Abstract
AbstractIn the context that coal remains the main energy source of China now, the safety of coal mine production is still worth our attention. For the factors influencing the roof accident of coal mine roadway have great complexity and uncertainty, a new risk prediction method of coal mine roof accidents integrating T‐S fuzzy fault tree and Bayesian network (BN) is proposed. The constructed method determines the BN and the conditional probability tables according to the established T‐S fuzzy fault tree. The fault state and fuzzy fault rate of root nodes are described according to the fuzzy number. And the forward inference of Bayesian is used to calculate the probability of the accidents on the roadway roof based on the fault probability of the root nodes and actual fault probability during construction respectively, to realize the risk prediction of roof accidents. Finally, practical data are used to verify the new fusion risk evaluation method by taking two mines as cases. The results show that the influencing factors calculated by the new fusion risk prediction method are completely consistent with the actual situation, confirming the effectiveness and reliability of this method, which providing new ideas for the research about the risk prediction of coal mine roof accidents.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.