Bibliographic Details
| Title: |
Influence Mechanism of Key Operating Parameters in a Novel Wet Cyclone–Ultrasonic Atomization Dust Removal System. |
| Authors: |
Xian, Wenhao, Liu, Yingjie, Xia, Zixuan, Cai, Yongbo, Sun, Zuo, Hu, Penglin, Hu, Shuda, Li, Shihang |
| Source: |
Journal of Environmental Engineering; Sep2026, Vol. 152 Issue 9, p1-12, 12p |
| Subject Terms: |
Dust removal, Atomization, Machine separators, Coal dust, Dust removal equipment |
| Abstract: |
Underground coal mine tunnels suffer from high dust concentrations and significant respirable dust, while traditional dust suppression technologies (ventilation exhaust, coal seam water injection, dry filtration, conventional wet scrubbing) have limitations including low capture efficiency, frequent equipment clogging, high operating costs, and poor adaptability. This paper proposes an innovative wet cyclone–ultrasonic atomization dust removal system integrating ultrasonic atomization with cyclone separation. Single-factor experiments investigated the effects of four key parameters (air pressure, liquid pressure, filter precision, filtration velocity) on the system's pressure drop, total dust, and respirable dust removal efficiency, clarifying their influence mechanisms. A four-factor, three-level orthogonal experiment combined with validation tests determined the parameter influence order and optimal operating conditions. Results show that parameters affect comprehensive performance in the order: filter precision > filtration velocity > air pressure > liquid pressure. The optimal conditions are air pressure 0.5 MPa, liquid pressure 0.2 MPa, filtration velocity 11.45 m/s , filter precision 40 mesh, yielding filter pressure drop of 217.8 Pa, total dust removal efficiency of 98.23%, and respirable dust removal efficiency of 94.46%, balancing low energy consumption and high dust removal efficiency. [ABSTRACT FROM AUTHOR] |
|
Copyright of Journal of Environmental Engineering is the property of American Society of Civil Engineers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Complementary Index |