Intelligent Decision Framework for Booster Fan Optimization in Underground Coal Mines: Hybrid Spherical Fuzzy-Cloud Model Approach Enhancing Ventilation Safety and Operational Efficiency
Optimizing mine fan operations in underground coal mines is important for ensuring proper ventilation, enhancing safety, and improving operational efficiency. A single main ventilation fan is insufficient to meet the ventilation demands of the entire mine. Therefore, it is necessary to consider the...
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MDPI AG
2025-04-01
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| Series: | Machines |
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| Online Access: | https://www.mdpi.com/2075-1702/13/5/367 |
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| author | Shibin Yao Jian Zhou Manoj Khandelwal Abiodun Ismail Lawal Chuanqi Li Moshood Onifade Sangki Kwon |
| author_facet | Shibin Yao Jian Zhou Manoj Khandelwal Abiodun Ismail Lawal Chuanqi Li Moshood Onifade Sangki Kwon |
| author_sort | Shibin Yao |
| collection | DOAJ |
| description | Optimizing mine fan operations in underground coal mines is important for ensuring proper ventilation, enhancing safety, and improving operational efficiency. A single main ventilation fan is insufficient to meet the ventilation demands of the entire mine. Therefore, it is necessary to consider the addition of booster fans to ensure effective ventilation. However, the selection of booster fans involves multiple influencing factors, and the complex interrelationships among fans remain unclear, making solution selection and risk assessment more challenging. To address this issue, this study proposes an optimization and risk analysis method for booster fan selection based on an improved analytic hierarchy process. This method leverages spherical fuzzy sets to handle uncertainty in the ventilation parameters and cloud models to facilitate probabilistic decision making. Through this model, the important relationships of the influencing factors for fan selection can be systematically determined, allowing for a rational assessment of the performance scores of candidate solutions. It provides a ranking of the alternatives based on their superiority, along with the risk indicators and optimization potentials of the selected solution. Ultimately, the reliability of the chosen model was verified through comparison and validation. This method not only enhances the scientific and rational basis for booster fan selection, reducing the complexity of the selection process, but also provides theoretical support for the optimization of coal mine ventilation systems. This study demonstrates the model’s effectiveness at improving ventilation safety and cost efficiency, making it a valuable tool for modern underground mining operations. |
| format | Article |
| id | doaj-art-23e77d4aa3984eb7a355400e3e474b99 |
| institution | DOAJ |
| issn | 2075-1702 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj-art-23e77d4aa3984eb7a355400e3e474b992025-08-20T03:14:43ZengMDPI AGMachines2075-17022025-04-0113536710.3390/machines13050367Intelligent Decision Framework for Booster Fan Optimization in Underground Coal Mines: Hybrid Spherical Fuzzy-Cloud Model Approach Enhancing Ventilation Safety and Operational EfficiencyShibin Yao0Jian Zhou1Manoj Khandelwal2Abiodun Ismail Lawal3Chuanqi Li4Moshood Onifade5Sangki Kwon6School of Resources and Safety Engineering, Central South University, Changsha 410083, ChinaSchool of Resources and Safety Engineering, Central South University, Changsha 410083, ChinaInstitute of Innovation, Science and Sustainability, Federation University Australia, Ballarat, VIC 3350, AustraliaDepartment of Mining Engineering, Federal University of Technology, Akure 340252, NigeriaSchool of Resources and Safety Engineering, Central South University, Changsha 410083, ChinaInstitute of Innovation, Science and Sustainability, Federation University Australia, Ballarat, VIC 3350, AustraliaDepartment of Energy Resources Engineering, Inha University, Yong-Hyun Dong, Nam Ku, Incheon 22212, Republic of KoreaOptimizing mine fan operations in underground coal mines is important for ensuring proper ventilation, enhancing safety, and improving operational efficiency. A single main ventilation fan is insufficient to meet the ventilation demands of the entire mine. Therefore, it is necessary to consider the addition of booster fans to ensure effective ventilation. However, the selection of booster fans involves multiple influencing factors, and the complex interrelationships among fans remain unclear, making solution selection and risk assessment more challenging. To address this issue, this study proposes an optimization and risk analysis method for booster fan selection based on an improved analytic hierarchy process. This method leverages spherical fuzzy sets to handle uncertainty in the ventilation parameters and cloud models to facilitate probabilistic decision making. Through this model, the important relationships of the influencing factors for fan selection can be systematically determined, allowing for a rational assessment of the performance scores of candidate solutions. It provides a ranking of the alternatives based on their superiority, along with the risk indicators and optimization potentials of the selected solution. Ultimately, the reliability of the chosen model was verified through comparison and validation. This method not only enhances the scientific and rational basis for booster fan selection, reducing the complexity of the selection process, but also provides theoretical support for the optimization of coal mine ventilation systems. This study demonstrates the model’s effectiveness at improving ventilation safety and cost efficiency, making it a valuable tool for modern underground mining operations.https://www.mdpi.com/2075-1702/13/5/367complex spherical fuzzy theorycloud model theoryimproved analytic hierarchy processbooster fansolution optimization |
| spellingShingle | Shibin Yao Jian Zhou Manoj Khandelwal Abiodun Ismail Lawal Chuanqi Li Moshood Onifade Sangki Kwon Intelligent Decision Framework for Booster Fan Optimization in Underground Coal Mines: Hybrid Spherical Fuzzy-Cloud Model Approach Enhancing Ventilation Safety and Operational Efficiency Machines complex spherical fuzzy theory cloud model theory improved analytic hierarchy process booster fan solution optimization |
| title | Intelligent Decision Framework for Booster Fan Optimization in Underground Coal Mines: Hybrid Spherical Fuzzy-Cloud Model Approach Enhancing Ventilation Safety and Operational Efficiency |
| title_full | Intelligent Decision Framework for Booster Fan Optimization in Underground Coal Mines: Hybrid Spherical Fuzzy-Cloud Model Approach Enhancing Ventilation Safety and Operational Efficiency |
| title_fullStr | Intelligent Decision Framework for Booster Fan Optimization in Underground Coal Mines: Hybrid Spherical Fuzzy-Cloud Model Approach Enhancing Ventilation Safety and Operational Efficiency |
| title_full_unstemmed | Intelligent Decision Framework for Booster Fan Optimization in Underground Coal Mines: Hybrid Spherical Fuzzy-Cloud Model Approach Enhancing Ventilation Safety and Operational Efficiency |
| title_short | Intelligent Decision Framework for Booster Fan Optimization in Underground Coal Mines: Hybrid Spherical Fuzzy-Cloud Model Approach Enhancing Ventilation Safety and Operational Efficiency |
| title_sort | intelligent decision framework for booster fan optimization in underground coal mines hybrid spherical fuzzy cloud model approach enhancing ventilation safety and operational efficiency |
| topic | complex spherical fuzzy theory cloud model theory improved analytic hierarchy process booster fan solution optimization |
| url | https://www.mdpi.com/2075-1702/13/5/367 |
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