Optimal Design of Vibrating Screen Parameters Based on Neural Network
Pages 455 - 459
Abstract
In order to improve the screening efficiency of the vibrating screen, this article takes the material particles as the research object, uses the orthogonal experiment method to design multiple sets of tests, and uses the discrete element method (DEM) to determine the amplitude, frequency and inclination of the vibrating screen. The kinematic parameters that affect the screening efficiency are analyzed, and the change law of the screening efficiency with the three parameters is obtained. Multivariate nonlinear fitting was performed on the orthogonal test results, and the neural network was used to find the parameter values corresponding to the best screening efficiency on the basis of the fitting function. The result indicated that the best parameters found were consistent with the simulation results.
References
[1]
Zhang Kang, Geng Fei. The development trend of coal screening equipment [J]. Mining Machinery, 2010, 11(24): 11--12.
[2]
JAFARIA, SALJOOGHINEZHADV, Emloying DEM to study the impact of different parameterson the screening effciency and mesh wear [J]. Powder Technology, 2016, 297(11):126--129.
[3]
CLEARYP W, SINNOTT M D, MORRISONRD. Separation performance of double deckbananscreens-part2: quantitative predictions[J]. Minerals Engineering, 2009, 22(14):123--128
[4]
CLEARYP W, SAWLEY M L.DEM modelling of industrial granularflows:3D casestudies and the effect of particle shape on hopper discharge[J]. Applied Mathmatical Modelling, 2002, 26(2):89--95.
[5]
Akbar Jafari, Nezhad, Vahid S Nezhad. Employing DEM to study the impact of different parameters on the screening efficiency and mesh wear [J]. Powder Technology, 2016, 297:126--143.
[6]
Gary W Delaney, Paul W Cleary, Marko Hilden, et al. Testing the validity of the spherical DEM model in simulating real granular screening processes[J]. Chemical Engineering Science, 2012, 68(1): 215--226.
[7]
Li Hongchang, Li Yaoming, Tang Zhong, etc. Numerical simulation and analysis of vibrating screening based on EDEM[J]. Journal of Agricultural Engineering, 2011, 27(5): 117--121.
[8]
Wang Lijun, Zhang Chuangen, Ding Zhenjun. Optimization of the structure of the cleaning sieve of the corn harvester[J]. Journal of Agricultural Machinery, 2016, 47(9): 108--114.
[9]
Wang Lijun, Zhang Chuangen, Ding Zhenjun. Optimization of the structure of the cleaning sieve of the corn harvester[J]. Journal of Agricultural Machinery, 2016, 47(9): 108--114.
[10]
Zhao Lala, Liu Chusheng, Yan Junxia, etc. Three-dimensional discrete element method simulation of particle flow on vibrating screen[J]. Journal of China University of Mining and Technology, 2010, 39(3): 414--419.
[11]
Zeng Yilun, Ning Youjun. Dynamic simulation analysis of screening process and effect of linear vibrating screen[J]. Mechanical Design and Research, 2020, 36(02): 163--168.
[12]
Chen Bing, Yan Jiwei, Yin Zhongjun, Sun Zhihui, Xiao Youpeng. Multiparameter optimization of high frequency vibrating screen based on DEM[J]. Journal of Engineering Science, 2021, 43(06): 852--861.
Index Terms
- Optimal Design of Vibrating Screen Parameters Based on Neural Network
Recommendations
Some Considerations on the Parameters Selection of DEM Simulation for Tumbling Ball Mills
ICIE '10: Proceedings of the 2010 WASE International Conference on Information Engineering - Volume 03Linear-spring dashpot model is one of the major contact models applied to the DEM (discrete element method) simulation of the tumbling ball mills. The model parameters such as stiffness, damping coefficient, coefficient of restitution and coefficient of ...
An optimal tumor marker group-coupled artificial neural network for diagnosis of lung cancer
Background: Epidemiological statistics has shown that there are approximately 1.2 million new cases of lung cancer diagnosed every year and the death rate of these patients is 17.8%. Earlier diagnosis is key to promote the five-year survival rate of ...
Monitoring method of rice seeds mass in vibrating tray for vacuum-panel precision seeder
Monitoring method of seeds mass in a vibrating tray was presented.Rice seeds were modelled using triaxial ellipsoidal particles.Impact behaviour of seeds action on the tray was DEM simulated.Differential force sensors were adopted and signal processing ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
October 2021
1723 pages
ISBN:9781450384322
DOI:10.1145/3501409
Copyright © 2021 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 31 December 2021
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
EITCE 2021
EITCE 2021: 2021 5th International Conference on Electronic Information Technology and Computer Engineering
October 22 - 24, 2021
Xiamen, China
Acceptance Rates
EITCE '21 Paper Acceptance Rate 294 of 531 submissions, 55%;
Overall Acceptance Rate 508 of 972 submissions, 52%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 26Total Downloads
- Downloads (Last 12 months)5
- Downloads (Last 6 weeks)2
Reflects downloads up to 11 Dec 2024
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in