Model of a Composite Magistral Conveyor Line

Pihnastyi, Oleh; Khodusov, Valery

doi:10.1109/saic.2018.8516739

Cited by 14 publications

(7 citation statements)

References 6 publications

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“…In this case, a separate model is built for each separate section. Combining sections into a common system leads to a system of equations [29,30]. In the event that a separate section does not include an accumulating bunker, the number of equations of the system is equal to the number of sections.…”

Section: Literature Reviewmentioning

confidence: 99%

Neural model of conveyor type transport system

Pihnastyi¹,

Khodusov²

2020

Computer Modeling and Intelligent Systems

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In this paper, a model of a transport conveyor system using a neural network is demonstrated. The analysis of the main parameters of modern conveyor systems is presented. The main models of the conveyor section, which are used for the design of control systems for flow parameters, are considered. The necessity of using neural networks in the design of conveyor transport control systems is substantiated. A review of conveyor models using a neural network is performed. The conditions of applicability of models using neural networks to describe conveyor systems are determined. A comparative analysis of the analytical model of the conveyor section and the model using the neural network is performed. The technique of forming a set of test data for the process of training a neural network is presented. The foundation for the formation of test data for learning neural network is an analytical model of the conveyor section. Using an analytical model allowed us to form a set of test data for transient dynamic modes of functioning of the transport system. The transport system is presented in the form of a directed graph without cycles. Analysis of the model using a neural network showed a high-quality relationship between the output flow for different conveyor sections of the transport system.

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Section: Literature Reviewmentioning

confidence: 99%

Neural model of conveyor type transport system

Pihnastyi¹,

Khodusov²

2020

Computer Modeling and Intelligent Systems

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“…This class of models is of particular importance for the design of control systems for a transport conveyor consisting of hundreds of sections. In the absence of experimental data for training a neural network in modeling a transport system, an analytical model can be used [16,32,33]. In this regard, in this work, we will pay attention to the construction of an optimal control system for the flow parameters of the assembly line using the neural network.…”

Section: Literature Reviewmentioning

confidence: 99%

Control of a Conveyor Based on a Neural Network

Pihnastyi

Kozhevnikov

2020

SSRN Journal

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“…Especially, it cannot estimate the wood humidity. The study [3,4] presented a distributed model of the transport conveyor which material moves along at the same speed to obtain the equations in closed form. Based on this model, the time delay between the arrival of the material at the inlet of the conveyor line and its outlet from the conveyor is calculated.…”

Section: Introductionmentioning

confidence: 99%

Application of Computer-Aided to Improve Industrial Productivity in Cement Factories by using a Novel Design of Quantitative Conveyor

Tran¹,

Quang²

2019

IJACSA

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To deal with the industrial evolution 4.0, many cement enterprises must be enhanced the productive ability. In this paper, the novel design of quantitative conveyor is introduced to improve the industrial productivity. Firstly, the test hardware platform is setup based on customer's requirement. Then, the analysis and control of mechanical platform for quantitative conveyor is investigated. From the experimental results, the operation of conveyor is stable and precise to ensure the output products for cement factories.

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Model of a Composite Magistral Conveyor Line

Cited by 14 publications

References 6 publications

Neural model of conveyor type transport system

Neural model of conveyor type transport system

Control of a Conveyor Based on a Neural Network

Application of Computer-Aided to Improve Industrial Productivity in Cement Factories by using a Novel Design of Quantitative Conveyor

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