Issue |
Mechanics & Industry
Volume 24, 2023
|
|
---|---|---|
Article Number | 10 | |
Number of page(s) | 16 | |
DOI | https://doi.org/10.1051/meca/2023009 | |
Published online | 17 April 2023 |
Regular Article
Reliability evaluation of electromechanical braking system of mine hoist based on fault tree analysis and Bayesian network
1
Anhui Key Laboratory of Mine Intelligent Equipment and Technology, Anhui University of Science and Technology, Huainan 232001, China
2
State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines, Anhui University of Science and Technology, Huainan 232001, China
3
School of Mechanical Engineering, Anhui University of Science and Technology, Huainan 232001, China
* e-mail: hwjin@mail.ustc.edu.cn
Received:
31
August
2022
Accepted:
3
March
2023
Electromechanical braking system is the key way to improve the braking response ability of mine hoist. At present, the reliability research of electromechanical braking system is less. In order to further analyze and improve the reliability of electro-mechanical braking system, this paper adopts the reliability analysis method of electro-mechanical braking system based on fault tree and Bayesian network. Firstly, the fault tree of the electro-mechanical braking system is established, and then the fault tree is transformed into a Bayesian network, and the posterior probability, probability importance and key importance of each root node are inversely deduced. The diagnosis results show that the ball screw is the weakest link of the electro-mechanical braking system. Then the static simulation and fatigue life simulation of the ball screw are carried out for optimization, and the optimal model of the ball screw is determined. Finally, the electro-mechanical brake installed with the optimized ball screw is tested and analyzed. After the reliable performance test of the electro-mechanical brake, it is finally determined that the braking effect of the optimized electro-mechanical brake is stable.
Key words: Mine hoist / electromechanical brake / fault tree / Bayesian network / reliability analysis
© H. Jin et al., published by EDP Sciences 2023
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