Implementation of artificial neural network to achieve speed control and power saving of a belt conveyor system
DOI:
https://doi.org/10.15587/1729-4061.2021.224137Keywords:
Conveyor Belt System, Speed Control, Power Saving, Artificial Neural Network (ANN)Abstract
According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN).
A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through the conveyor belt motion. An optimal speed controlling mechanism of the conveyor belt is presented by detecting smartly the parts' number and weights using the vision sensor, where the latter will give sufficient visualization about the system. Then image processing will deliver the important data to ANN, which will optimally decide the best conveyor belt speed. This decided speed will achieve the aim of power saving in belt motion. The proposed controlling system will optimally switch the speed of the conveyor belt system to ON, OFF and idle status in order to minimize the consumption of energy in the conveyor belt.
As the conveyor belt is fully loaded it moves at its maximum speed. But if the conveyor is partially loaded, the speed will be adjusted accordingly by the ANN. If no loading existed, the conveyor will be stopped. By this way, a very significant energy amount in addition to cost will be saved. The developed conveyor belt system will modernize industrial manufacturing lines, besides reducing energy consumption and cost and increasing the conveyor belts lifetime
References
- Halepoto, I. A., Shaikh, M. Z., Chowdhry, B. S., Uqaili, M. u hammad A. (2016). Design and Implementation of Intelligent Energy Efficient Conveyor System Model Based on Variable Speed Drive Control and Physical Modeling. International Journal of Control and Automation, 9 (6), 379–388. doi: https://doi.org/10.14257/ijca.2016.9.6.36
- Zhang, S., Xia, X. (2010). Optimal control of operation efficiency of belt conveyor systems. Applied Energy, 87 (6), 1929–1937. doi: https://doi.org/10.1016/j.apenergy.2010.01.006
- Zhang, S., Xia, X. (2009). A new energy calculation model of belt conveyor. AFRICON 2009. doi: https://doi.org/10.1109/afrcon.2009.5308257
- Reicks, A. V. (2008). Belt conveyor idler roll behaviours. Bulk material handling by conveyor belt. Colorado: SME, 35–40. Available at: http://www.overlandconveyor.cn/uploadfile/pdf/8-belt-idler-roll-behavior[1].pdf
- Mushiri, T., Mbohwa, C. (2016). Design of a Power Saving Industrial Conveyor System. Proceedings of the World Congress on Engineering and Computer Science. Vol. 2. San Francisco. Available at: http://iaeng.org/publication/WCECS2016/WCECS2016_pp942-947.pdf
- Middelberg, A., Zhang, J., Xia, X. (2009). An optimal control model for load shifting – With application in the energy management of a colliery. Applied Energy, 86 (7-8), 1266–1273. doi: https://doi.org/10.1016/j.apenergy.2008.09.011
- He, D., Pang, Y., Lodewijks, G. (2016). Determination of Acceleration for Belt Conveyor Speed Control in Transient Operation. International Journal of Engineering and Technology, 8 (3), 206–211. doi: https://doi.org/10.7763/ijet.2016.v8.886
- Yang, C., Liu, J., Li, H., Zhou, L. (2018). Energy Modeling and Parameter Identification of Dual-Motor-Driven Belt Conveyors without Speed Sensors. Energies, 11 (12), 3313. doi: https://doi.org/10.3390/en11123313
- He, D., Liu, X., Zhong, B. (2020). Sustainable belt conveyor operation by active speed control. Measurement, 154, 107458. doi: https://doi.org/10.1016/j.measurement.2019.107458
- Windmann, S., Niggemann, O., Stichweh, H. (2015). Energy efficiency optimization by automatic coordination of motor speeds in conveying systems. 2015 IEEE International Conference on Industrial Technology (ICIT). doi: https://doi.org/10.1109/icit.2015.7125185
- Reznik, L., Dabke, K. P. (2004). Measurement models: application of intelligent methods. Measurement, 35 (1), 47–58. doi: https://doi.org/10.1016/j.measurement.2003.08.020
- Li, X., Yu, H. (2015). The Design and Application of Control System Based on the BP Neural Network. Proceedings of the 3rd International Conference on Mechanical Engineering and Intelligent Systems (ICMEIS 2015). doi: https://doi.org/10.2991/icmeis-15.2015.148
- Abbas, N. H., Saleh, B. J. (2016). Design of a Kinematic Neural Controller for Mobile Robots based on Enhanced Hybrid Firefly-Artificial Bee Colony Algorithm. Al-Khwarizmi Engineering Journal, 12 (1), 45–60. Available at: https://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/283/278
- Faisal, A. A. H., Nassir, Z. S. (2016). Modeling the removal of Cadmium Ions from Aqueous Solutions onto Olive Pips Using Neural Network Technique. Al-Khwarizmi Engineering Journal, 12 (3), 1–9. Available at: https://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/303/298
- Beale, M. H., Hagan, M. T., Demuth, H. B. (2012). Neural Network Toolbox™ User’s Guide. The MathWorks, Inc. Available at: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.699.4831
- Wang, Q., Lu, P. (2019). Research on Application of Artificial Intelligence in Computer Network Technology. International Journal of Pattern Recognition and Artificial Intelligence, 33 (05), 1959015. doi: https://doi.org/10.1142/s0218001419590158
- Ballabio, D., Vasighi, M. (2012). A MATLAB toolbox for Self Organizing Maps and supervised neural network learning strategies. Chemometrics and Intelligent Laboratory Systems, 118, 24–32. doi: https://doi.org/10.1016/j.chemolab.2012.07.005
- He, D. (2017). Energy saving for belt conveyors by speed control. TRAIL Research School. doi: https://doi.org/10.4233/uuid:a315301e-6120-48b2-a07b-cabf81ab3279
- Ji, J., Miao, C., Li, X., Liu, Y. (2021). Speed regulation strategy and algorithm for the variable-belt-speed energy-saving control of a belt conveyor based on the material flow rate. PLOS ONE, 16 (2), e0247279. doi: https://doi.org/10.1371/journal.pone.0247279
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