Karim NESSAIB and Abdelaziz LAKEHAL (2022) CONVEYOR BELT FAULTS DIAGNOSIS USING BAYESIAN NETWORK. The 4th International Conference on Electromechanical Engineering (ICEE2022) , Skikda University
Scientific Publications
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Abstract
Nowadays, belt conveyors play a vital role in industry and specifically in mines, their availability poses a challenge to maintenance professionals. This study proposes a Bayesian network-based conveyor belt diagnostic method. The developed method has been applied to the conveyor belt of the Ouenza mine. First, the belt conveyor was divided into three main subsystems, and then the a priori probability for each cause was defined. The results obtained show that the majority of faults that influence the operation of the conveyor belt are caused by the transport system. Therefore, to improve the availability of the conveyor belt system, the decision-making for intervention should be done at the first level.
Information
| Item Type | Conference |
|---|---|
| Divisions |
» Laboratory of Research on Electromechanical and Dependability » Faculty of Science and Technology |
| ePrint ID | 3745 |
| Date Deposited | 2022-12-21 |
| Further Information | Google Scholar |
| URI | https://univ-soukahras.dz/en/publication/article/3745 |
BibTex
@inproceedings{uniusa3745,
title={CONVEYOR BELT FAULTS DIAGNOSIS USING BAYESIAN NETWORK},
author={Karim NESSAIB and Abdelaziz LAKEHAL},
year={2022},
booktitle={The 4th International Conference on Electromechanical Engineering (ICEE2022)}
}
title={CONVEYOR BELT FAULTS DIAGNOSIS USING BAYESIAN NETWORK},
author={Karim NESSAIB and Abdelaziz LAKEHAL},
year={2022},
booktitle={The 4th International Conference on Electromechanical Engineering (ICEE2022)}
}