Control of the belt speed at unbalanced loading of the conveyor

Abstract

Purpose. Development of algorithms for controlling the speed of the conveyor belt, based on the distributed model of the transport system, containing partial differential equations methodology. To calculate the parameters of a conveyor line with a variable speed of material motion, an instrument of math ematical physics is used. findings. Comparative analysis of conveyor transport system models is performed. Application of partial differential equations for simulating transport systems of conveyor type, which are complex dynamic distributed systems, is substantiated. A nondimen sional model of a conveyor system in instantaneous approximation with the use of partialderivative equations is presented. A sys tem of characteristic equations is recorded and a solution is developed which defines the value of material flow and material den sity at an arbitrary point of time for the given point of the transportation route. An expression is obtained which defines the value of material delay in the transport system depending on the velocity defect law for conveyor belt movement. Transition period time is determined during which the output material flow is defined by linear density of material disposition along the transportation route. Dependences for the material linear density and material flow for the steady state condition are defined. The performance criterion of control of flow parameters of the conveyor system is recorded and a solution of the problem of optimal control of con veyor belt speed providing the relay control mode with the minimum power consumption for material movement is found. An example of control algorithm development is given. originality. PDEmodels of transport systems of conveyor type and energysaving algorithms for controlling such systems have been improved. Practical value. The proposed method for calculating the parameters of the conveyor line, which is a dynamic distributed sys tem, can be used to design systems for optimal control of flow parameters of transport systems of conveyor type

Analysis of Dynamic Mechanic Belt Stresses of the Magistral Conveyor

“…The characteristics of modern conveyor systems are presented in [5,6] (table 1). The nonstationary value of the incoming rock flow to the entrance of the conveyor section leads to an uneven distribution of material on the conveyor belt along the transportation route [7,8]. This leads to an increase in the specific energy consumption for the transportation of one ton of material [9].…”

Using the asymptotic approximation of the Maxwell element model for the analysis of stress in a conveyor belt

“…The viscoelastic properties of the conveyor belt material, caused by relaxation processes, affect the destruction rate of the conveyor belt [6,7], are closely related to the problem of saving material transport costs. One of the ways to reduce transport costs, which occupy a significant part in the cost of material extraction, is to use a conveyor belt speed control system [8]. Switching speed modes leads to acceleration or deceleration of the conveyor belt, and, accordingly, to the emergence of dynamic stresses in the belt.…”

Control of a Conveyor Based on a Neural Network

“…Modern transport conveyor systems are characterized by relatively large power consumption, intensive material flow, extended in separate sections, high-speed conveyor belts [8]. One of the methods to increase the efficiency of conveyor transport is to increase the uploading of the transport system with material and ensure uniform distribution of material along the transport route [9][10][11]. The operation of the conveyor with a nominal upload is the most cost-effective.…”

“…However, it is often not possible to install a bunker or its capacity is insufficient to ensure effective control. This is one of the reasons for using conveyor belt speed control systems [9][10][11].…”

“…The Logistic-activation function (12) was chosen as the activation function. The neural network is trained in the test sample [38], which was used to train the main model (10), (11).…”