We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Risk Assessment of Unsafe Acts in Coal Mine Gas Explosion Accidents Based on HFACS-GE and Bayesian Networks.
- Authors
Niu, Lixia; Zhao, Jin; Yang, Jinhui
- Abstract
Even in the context of smart mines, unsafe human acts are still an important cause of coal mine gas explosion accidents, but there are few models to analyze unsafe human acts in coal mine gas explosion accidents. This study tries to solve this problem through a risk assessment method of unsafe acts in coal mine gas explosion accidents based on Human Factor Analysis and Classification system (HFACS-GE) and Bayesian networks (BN). After verifying the reliability of HFACS-GE framework, a BN model of risk factors of unsafe acts was established with the Chi-square test and odds ratios analysis. After reasoning analysis, risk paths and key risk factors of unsafe acts were obtained, and preventive measures were granted. Based on the analysis of 100 coal mine gas explosion cases, the maximum probability of five kinds of unsafe acts of employees is 38%. Among the 22 risk factors, the mental state of employees has the greatest influence on the habitual violation of regulations, and the sensitivity value is 12.7%. This study can provide technical assistance for the risk management of unsafe acts in coal mine gas explosions.
- Subjects
COAL gas; GAS explosions; COAL mining; BAYESIAN analysis; COAL mining accidents; ACT Assessment
- Publication
Processes, 2023, Vol 11, Issue 2, p554
- ISSN
2227-9717
- Publication type
Article
- DOI
10.3390/pr11020554