Affiliation:
1. School of Economics and Management China University of Mining and Technology Xuzhou China
2. Safety Science and Emergency Management Research Institute China University of Mining and Technology Xuzhou China
3. Artificial Intelligence Research Institute China University of Mining and Technology Xuzhou China
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.
Funder
National Natural Science Foundation of China
Subject
Management Science and Operations Research,Safety, Risk, Reliability and Quality
Reference32 articles.
1. The National Mine Safety Administration of China 2022.https://www.chinamine‐safety.gov.cn
2. Study on warning criterion of critical separation area for separation type roof accident;Xie JL;J Min Say Eng,2012
3. Analysis of roof collapse mechanism and supporting measures in fault zone of coal roadway;Wang Q;Rock Soil Mech,2012
4. In‐situ observation and numerical analysis of roof movement features of fully‐mechanized sublevel caving face with deep alluvium;Guo XS;J Min Say Eng,2015
5. Logistic regression model for prediction of roof fall risks in bord and pillar workings in coal mines: An approach
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献