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
Highlights
Belt conveyors become very widely used in handling materials along short and medium conveying distances because their ability to transport is very effective if compared to the other transportation methods [1]
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 Artificial Neural Network (ANN) controller
The aim of this study is to develop the speed controlling of the conveyor belt motor based on the Artificial Neural Network (ANN) in order to minimize the consumption of energy in the conveyor belt system
Summary
Belt conveyors become very widely used in handling materials along short and medium conveying distances because their ability to transport is very effective if compared to the other transportation methods [1]. The handling of materials represents an important sector in the industry, where it consumes a considerable proportion of the overall power supply. In South Africa, for example, material handling consumes 10 % of the overall power supply [2]. It is very significant to enhance the energy efficiency of belt conveyors in order to maximize energy consumption and for sure the cost of energy used in the material handling process. The efficiency of energy could be in four kinds, which are: performance, operation, equipment and technology efficiency Both of operation and equipment efficiencies can be improved in most systems including belt conveyors. The performance efficiency depends on the operation and equipment efficiencies, where the performance efficiency is reflected by many external indicators like the consumption and cost of energy [4]
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