Intelligent Prediction of Sieving Efficiency in Vibrating Screens
In order to effectively predict the sieving efficiency of a vibrating screen, experiments to investigate the sieving efficiency were carried out. Relation between sieving efficiency and other working parameters in a vibrating screen such as mesh aperture size, screen length, inclination angle, vibra...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2016/9175417 |
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| _version_ | 1832547153197662208 |
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| author | Bin Zhang Jinke Gong Wenhua Yuan Jun Fu Yi Huang |
| author_facet | Bin Zhang Jinke Gong Wenhua Yuan Jun Fu Yi Huang |
| author_sort | Bin Zhang |
| collection | DOAJ |
| description | In order to effectively predict the sieving efficiency of a vibrating screen, experiments to investigate the sieving efficiency were carried out. Relation between sieving efficiency and other working parameters in a vibrating screen such as mesh aperture size, screen length, inclination angle, vibration amplitude, and vibration frequency was analyzed. Based on the experiments, least square support vector machine (LS-SVM) was established to predict the sieving efficiency, and adaptive genetic algorithm and cross-validation algorithm were used to optimize the parameters in LS-SVM. By the examination of testing points, the prediction performance of least square support vector machine is better than that of the existing formula and neural network, and its average relative error is only 4.2%. |
| format | Article |
| id | doaj-art-704ef50efd63402b8f5e6987678d1b0c |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-704ef50efd63402b8f5e6987678d1b0c2025-02-03T06:45:58ZengWileyShock and Vibration1070-96221875-92032016-01-01201610.1155/2016/91754179175417Intelligent Prediction of Sieving Efficiency in Vibrating ScreensBin Zhang0Jinke Gong1Wenhua Yuan2Jun Fu3Yi Huang4The State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082, ChinaThe State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082, ChinaDepartment of Mechanical and Energy Engineering, Shaoyang University, Shaoyang 422004, ChinaDepartment of Mechanical and Energy Engineering, Shaoyang University, Shaoyang 422004, ChinaThe State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082, ChinaIn order to effectively predict the sieving efficiency of a vibrating screen, experiments to investigate the sieving efficiency were carried out. Relation between sieving efficiency and other working parameters in a vibrating screen such as mesh aperture size, screen length, inclination angle, vibration amplitude, and vibration frequency was analyzed. Based on the experiments, least square support vector machine (LS-SVM) was established to predict the sieving efficiency, and adaptive genetic algorithm and cross-validation algorithm were used to optimize the parameters in LS-SVM. By the examination of testing points, the prediction performance of least square support vector machine is better than that of the existing formula and neural network, and its average relative error is only 4.2%.http://dx.doi.org/10.1155/2016/9175417 |
| spellingShingle | Bin Zhang Jinke Gong Wenhua Yuan Jun Fu Yi Huang Intelligent Prediction of Sieving Efficiency in Vibrating Screens Shock and Vibration |
| title | Intelligent Prediction of Sieving Efficiency in Vibrating Screens |
| title_full | Intelligent Prediction of Sieving Efficiency in Vibrating Screens |
| title_fullStr | Intelligent Prediction of Sieving Efficiency in Vibrating Screens |
| title_full_unstemmed | Intelligent Prediction of Sieving Efficiency in Vibrating Screens |
| title_short | Intelligent Prediction of Sieving Efficiency in Vibrating Screens |
| title_sort | intelligent prediction of sieving efficiency in vibrating screens |
| url | http://dx.doi.org/10.1155/2016/9175417 |
| work_keys_str_mv | AT binzhang intelligentpredictionofsievingefficiencyinvibratingscreens AT jinkegong intelligentpredictionofsievingefficiencyinvibratingscreens AT wenhuayuan intelligentpredictionofsievingefficiencyinvibratingscreens AT junfu intelligentpredictionofsievingefficiencyinvibratingscreens AT yihuang intelligentpredictionofsievingefficiencyinvibratingscreens |