Кафедра "Інтернет речей"
Постійне посилання колекціїhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/5398
Увага! Поповнення колекції кафедри "Інтернет речей" – призупинено.
Від вересня 2022 року кафедри "Інтернет речей" та "Мультимедійних інформаційних технологій і систем" об’єднані у кафедру "Мультимедійні та інтернет технології і системи".
Первісна назва кафедри – "Розподілені інформаційні системи і хмарні технології".
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Документ On constructing a random values generator of the input material flow for transport conveyor models based on neural network(Видавничий дім "Гельветика", 2024) Pihnastyi, O. M.; Sobol, MaksymThis study examines a method for constructing a generator of random values of the input material flow to form a training data set for highly efficient transport conveyor models based on a neural network. A comparative analysis of the experimental, approximated and generated realizations for the input material flow of the conveyor type transport system is presented.Документ Predictive analysis of the interval material flow rates in transport conveyors based on experimental data(2024) Pihnastyi, O. M.; Sobol, Maksym; Burduk, AnnaThis study examines a method for constructing a generator of random values of the input flow of material to form a training data set in highly efficient transport conveyor models based on a neural network. Dimensionless parameters are introduced that make it possible to represent the model of the input material flow of a transport conveyor in a dimensionless form. Coordinate functions are determined to approximate the experimental realization of the input material flow. A canonical decomposition of the experimental realization of the input material flow in terms of coordinate functions based on the use of fixed intervals is presented. For the selected canonical decomposition of the experimental realization of the input material flow, a theoretical correlation function is determined. It is shown that as the number of intervals increases, the correlation function of the experimental realization tends to the theoretical correlation function. The stages of constructing a random value generator for the input material flow are presented in detail. A comparative analysis of the experimental, approximated and generated realization for the input material flow is presented and estimates of the statistical characteristics of the realizations of the input material flow are given. The correlation functions constructed for the experimental, approximated and generated realizations of the input material flow are analyzed. An estimate is given of the length of the time interval required to carry out experimental changes in the input material flow.Документ Analysis of the input material flow of the transport conveyor(Національний гірничий університет, 2023) Pihnastyi, O. M.; Sobol, MaksymPurpose. To develop a method for analyzing the material flw entering the input of a conveyor section, based on the decomposition of the input material flw into a deterministic material flw and a stochastic material flw. Methodology. The analysis of experimental data characterizing the input material flw was performed using the methods of the canonical Fourier representation of a random process. Findings. A method for representing a stochastic material flw as a combination of a deterministic process and a stationary random process with ergodic properties is proposed. Originality. The originality of the obtained results lies in the fact that, for the fist time, a method of analysis based on the decomposition of the input material flw for a conveyor section has been proposed, which, unlike the existing methods of input flw typing for the mining industry, will allow us to independently perform deterministic flw typing and stochastic material flw typing in transport conveyors. The proposed approach makes it possible to highlight special characteristics separately for deterministic and stochastic material flws. This will make it possible to use the obtained regularities to increase the accuracy of the conveyor model and will accordingly increase the quality of the belt speed control systems and the flw of material coming from the input bunker. The obtained results are of particular importance due to the fact that the characteristics of the deterministic material flw are directly related to the technical or technological factors of material extraction. Practical value. The obtained results allow determining statistically stable regularities for the incoming flw, which makes it possible, based on these regularities from the set of available control algorithms, to choose the optimal control algorithm for the parameters of the operating conveyor section. This allows reducing the enterprise’s energy costs of the transportation of material. The proposed method can be successfully applied to build random number generators simulating the sequence of values of the input flw of material. The developed generators can be used both for validating existing belt speed control systems and creating new control systems based on neural networks. This opens perspectives for the design of effctive systems for controlling the flw parameters of transport system, based on the transport conveyor model, which takes into account the stochastic nature of the incoming material flw.Документ The Input Material Flow Model of the Transport Conveyor(Institute of Electrical and Electronics Engineers, Inc., 2022) Pihnastyi, O. M.; Sobol, MaksymThis paper discusses the problem of forming a data set for training a neural network used to build a model of a multi-section conveyor. The analysis of the models, which are used by designing the flow parameters control system of the transport system, is given. The conditions of applying a neural network in the transport conveyer model are justified and determined. Methods for generating a data set for training a neural network are discussed. As the main approach, the use of production data obtained from functioning transport conveyors is considered. Statistically processed data can be used to build generators of stochastic processes that model the incoming material flow for the transport system. The development of these generators to form the input flow of the material of the transport system opens up the possibility of analyzing and monitoring conveyor models in various modes of its configuration. A statistical analysis of the incoming material flow of the transport system was carried out and its number characteristics were determined. The correlation function characterizing the input flow of material for the transport system is considered. The introduction of dimensionless parameters to describe the input material flow made it possible to scale the results of work for a wide class of conveyor-type transport systems.