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Forecasting Breakdowns of Electric Motors of a Sugar Factory Using Machine Learning Methods

Forecasting Breakdowns of Electric Motors of a Sugar Factory...

引用

Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Nataliia Zaiets Nataliia Lutska Lidiia Vlasenko Andrii Zhyltsov dept. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine dept. of Automation and Computer Technologies of Control Systems National University of Food Technologies Kyiv Ukraine dept. of Software Engineering and Cyber Security State University of Trade and Economics Kyiv Ukraine dept. of electromagnetic systems The Institute of Electrodynamics of the National Academy of Sciences of Ukraine Kyiv Ukraine

the paper demonstrates the process of developing mathematical models for identifying breakdowns of electric motors using machine learning methods. The authors have developed three mathematical models for identifying breakdowns of electric drives with a power of 55 kW, 1500 rpm on the example of sugar production: model for quadratic discriminant analysis; binary classification decision tree; feed-forward neural network model. The best structures and parameters of the models were determined by machine learning methods. The performance of the models on the training and test sets was more than 96% by F-score. It was proposed to use all three models independently for diagnosing breakdowns of electric drives, while the decision maker makes the final decision on the replacement or repair of electrical equipment. This approach is justified and effective because of the diversity of models. The developed models, except for assessing the state of the engine, can also be used for simulation modelling, forecasting, and serve as information support for process operators in organizing equipment maintenance. The availability of real-time information about the state of equipment in production will allow timely repair or replacement of equipment, thereby reducing the risks of stopping production and increasing the resource efficiency of technological processes.

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Simulation Model of Hydraulic Feed System with Differential Cylinder 5

Simulation Model of Hydraulic Feed System with Differential ...

引用

5th International Conference on control systems, Mathematical Modeling, automation and Energy Efficiency, SUMMA 2023

作者： Sandler, Ilya L Ivanov, Dmitriy V Terekhin, Michail A Kolpashchikov, Sergey A Vossin, Alexey V Portnov, Artem V Samara State University of Railway Transport Dept. Digital Technologies Samara Russia Samara State Technical University Dept. Automation and Control in Technical Systems Samara Russia National Research University Dept. Information Systems Security Samara Samara Russia FSBEI HE SamSMU MOH Russia Higher School of Medical Engineering Institute of Innovative Development Samara Russia FSBEI HE SamSMU MOH Russia Institute of Innovative Development Samara Russia

ISBN: (纸本)9798350309126

The paper presents a simulation model of a hydraulic feed system with a differential cylinder, which allows you to explore the system and visually examine its operation. During the simulation, transient processes were obtained at various points of the hydraulic control system. The simulation results show the adequate operation of the system under study. The work is of interest to researchers and engineers in the field of building automatic hydraulic drive control systems. Also, the results obtained can be used for educational purposes. © 2023 IEEE.

关键词： Machine tools

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Intelligent Operational Decision Support System for Sugar Factory Resource Efficiency

Intelligent Operational Decision Support System for Sugar Fa...

引用

International Conference on Modern Electrical and Energy systems (MEES)

作者： Nataliia Lutska Nataliia Zaiets Lidiia Vlasenko Stefan Junge Dept. of Automation and Computer Technologies of Control Systems National University of Food Technologies Kyiv Ukraine Dept. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Dept. of Software Engineering and Cyber Security State University of Trade and Economics Kyiv Ukraine Dept. of Packaging Technology Berlin University of Applied Sciences Berlin Germany

With the economic crisis that is looming over the world due to changes in the energy sector and a reduction in the supply of certain types of products, energy and resource efficiency issues are becoming more relevant for the food industry. Also important is the preservation of the environment and the implementation of Cleaner Production trends. Most enterprises follow the concept of Industry 4.0 and increase efficiency through the implementation of intelligent methods, in particular machine learning. The paper proposes a neural network model of sugar production. The model makes it possible to predict the main estimates of resource efficiency used to correct the technological modes of production by the operator-technologist. The structure of the operational decision support system has been developed and is used by personnel to model and predict changes in resource efficiency estimates and KPIs calculated on their basis. Its feature is the integration of methods for achieving resource efficiency, improving environmental performance and ensuring KPIs. To do this, at the initial stage, an analysis of the main flows that affect resource efficiency and an assessment of their importance was carried out. Ensuring Production Performance is confirmed by the simulation and the adequacy of the created neural network accuracy of more than 95%.

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Synthesis of Model Predictive control for an Electrohydraulic Servo System Using Orthonormal Functions

Synthesis of Model Predictive Control for an Electrohydrauli...

引用

Communications, Information, Electronic and Energy systems (CIEES), International Conference on

作者： Georgi Mihalev Stanimir Yordanov Krasimir Ormandzhiev Hristina Stoycheva Todor Todorov Dept. of Automation Information and Control Systems Technical University of Gabrovo Gabrovo Bulgaria Dept. of Power Engineering Technical University of Gabrovo Gabrovo Bulgaria Dept. of Comunication Technique and Technologies Technical University of Gabrovo Gabrovo Bulgaria

ISBN: (数字)9798350352863

ISBN: (纸本)9798350352870

The paper presents the implementation of a Continuous-Time Model Predictive control (CMPC) regulator for controlling an electrohydraulic servo system. The control object is a test bench consisting of three modules and a PC-based data acquisition and control system. The system is modeled in state-space form, accounting for parametric uncertainties. The synthesis of the model predictive controller is performed by approximating the control signal using Laguerre orthonormal functions. The article includes mathematical formulas and relationships that illustrate the modeling approach. Simulations and robust analysis of the closed-loop system are conducted. Through a real-time control system, experimental data and graphs are obtained, demonstrating the performance and optimality of the synthesized control strategy.

关键词： Analytical models Uncertainty Mathematical models Stability analysis Robustness Electrohydraulics Closed loop systems Servomotors Voltage control Predictive control

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An Algorithm Restricting Motion into Curve-Like Forbidden Regions

An Algorithm Restricting Motion into Curve-Like Forbidden Re...

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International Conference on control, Mechatronics and automation (ICCMA)

作者： Emre YAZICI Nusrettin GULEC Control & Automation Eng. Dept. Istanbul Technical University NISO Software Technologies Istanbul & Izmir Turkey Defense Systems Technologies ASELSAN Inc. Ankara Turkey

In robotic systems, there are often parts of the workspace where motion may cause damage to surrounding environment or the system itself. For such systems, forbidden regions are defined and motion into these are restricted by special algorithms. It is essential to keep these regions at optimal size and shape in order to ensure maximum operational capability whilst avoiding any risks of damage. In this paper, a hierarchical algorithm tackling these problems for two-axis gimballed systems and motion forbidden regions defined by second order curves is proposed. The method also supports safe operation in case of multiple dynamic forbidden regions in real-time. The proposed algorithm is verified through simulations and experiments conducted on an actual surveillance system.

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Analysis of Energy Potential of Micro Wind Turbines at Three Locations in the Central-Eastern Part of the Bulgarian Danube River Region

Analysis of Energy Potential of Micro Wind Turbines at Three...

引用

Communications, Information, Electronic and Energy systems (CIEES), International Conference on

作者： Nikolay Valov Katerina Gabrovska-Evstatieva Ivaylo Stoyanov Tsvetelina Kaneva Seher Kadirova Boris Evstatiev Nicolay Mihailov Dept. of Automation and Electronics University of Ruse "Angel Kanchev" Ruse Bulgaria Dept. of Computer Science University of Ruse "Angel Kanchev" Ruse Bulgaria Dept. of Electrical Power Engineering University of Ruse "Angel Kanchev" Ruse Bulgaria Dept. of Computer Systems and Technologies University of Ruse "Angel Kanchev" Ruse Bulgaria

ISBN: (数字)9798350352863

ISBN: (纸本)9798350352870

The share of renewable energy sources in the energy mix worldwide is gradually increasing. And even though they all have a highly variable nature, they can be forecasted statistically. The wind energy potential was investigated in this article in the Bulgarian Danube region, located between Ruse and Silistra. Two years of meteorological data, including the wind speed at 10 m height and the ambient temperature was used to estimate the average wind energy for each month of the year at three geographic locations – Ruse, Staro Selo (near Tutrakan), and Calarasi, Romania (near Silistra). The results showed that Staro Selo has the highest energy potential, reaching up to 0.75 kWh/day/m 2 in February, followed by Calarasi with 0.38 kWh/day/m 2 . The city of Ruse showed the lowest wind potential with the highest average monthly value reaching only 0.0027 kWh/day/m 2 . The obtained results showed that the regions around Tutrakan and Silistra are appropriate for the application of micro wind turbines.

关键词： Hands Temperature distribution Renewable energy sources Wind energy Wind speed Urban areas Wind turbines Rivers Wind forecasting Investment

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Modeling the Productivity of a Sugar Factory using Machine Learning Methods

Modeling the Productivity of a Sugar Factory using Machine L...

引用

International computer Sciences and Information technologies (CSIT)

作者： Nataliia Lutska Lidiia Vlasenko Nataliia Zaiets Vitaliy Lysenko dept. of Automation and Computer Technologies of Control Systems National University of Food Technologies Kyiv Ukraine dept. of Software Engineering and Cyber Security State University of Trade and Economics Kyiv Ukraine dept. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine

ISBN: (纸本)9798350334326

Relevant today is the digitalization of industrial enterprises, which is an evolutionary continuation of the introduction of MES/MOM. At the same time, an important role is played by the construction of mathematical models for various purposes, which are the main component of the Digital Twin development. Digital Twin provides a new philosophy for conducting enterprise production processes based on these models, which is aimed at improving the efficiency of both individual sectors and the enterprise as a whole. To increase the profit of the enterprise, it is necessary to ensure the planned productivity of technological processes, the final indicator of which is the yield of sugar. Taking into account that a significant number of material flows operate at the enterprise, only production flows with which the operator-technologist works are singled out in the work. The selected flows, based on expert assessments, were assigned weighted values of the impact on the overall performance of the sugar production. This made it possible to build a mathematical model that predicts the yield of sugar from input flows. The structure and parameters of this model are determined by machine learning methods. This is a feed-forward neural network MLP 7-23-23-1, which provides forecast accuracy with an error of less than 1%. The model can be used to model, correct, and predict the process conditions of an enterprise, which will increase the overall productivity of the sugar factory.

关键词： Productivity Biological system modeling Machine learning Predictive models Mathematical models Sugar industry Production facilities

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Digital Map Generation Workflow Demonstrated on ZalaZONE Automotive Proving Ground Elements 36

Digital Map Generation Workflow Demonstrated on ZalaZONE Aut...

引用

36th IEEE/IFIP Network Operations and Management Symposium, NOMS 2023

作者： Somogyi, Árpád Tettamanti, Tamás Varga, Pál Szalay, Zsolt Baranyai, Dániel Lovas, Tamás Budapest University of Technology and Economics Fac. of Civil Engineering Dept. of Photogrammetry and Geoinformatics Budapest Hungary Institute for Computer Science and Control The Eötvös Loránd Research Network Systems and Control Laboratory Budapest Hungary Budapest University of Technology and Economics Fac. of Electrical Engineering and Informatics Dept. of Telecommunications and Media Informatics Budapest Hungary Budapest University of Technology and Economics Fac. of Transportation Eng. and Vehicle Eng. Dept. of Automotive Technologies Budapest Hungary

ISBN: (纸本)9781665477161

One major goal of digital twin technology applied in the Architecture, Engineering, and Construction (AEC) Industry is the mapping of roads and road environments with their associated information. Such digital twins can support cost-effective testing, simulations, and the production of mapping backgrounds for automated vehicles and generally for Cooperative, Connected and Automated Mobility (CCAM) developments. The efficient workflow that leads from data acquisition to finished products depends on a number of requirements and knowledge sets. The main contribution of the paper is a general methodology of creating HD-map from point cloud and image data set. Accordingly, the most widely used survey techniques are presented and the requirements for the objects to be derived are summarized. The paper then outlines a general implementation procedure as an expert knowledge through a real-life example, where the results obtained for the ZalaZONE Automotive Proving Ground are demonstrated. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Live Demo: E2P-Events to Polarization Reconstruction from PDAVIS Events

Live Demo: E2P-Events to Polarization Reconstruction from PD...

引用

2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Delbruck, Tobi Wang, Zuowen Mei, Haiyang Haessig, Germain Joubert, Damien Haque, Justin Chen, Yingkai Milde, Moritz B. Gruev, Viktor Univ. of Zurich and ETH Zurich Sensors Group Institute of Neuroinformatics Switzerland Center for Vision Automation & Control High-Performance Vision Systems AIT Austrian Institute of Technology Vienna Austria Western Sydney University Intl. Centre for Neuromorphic Systems The MARCS Institute Sydney Australia University of Illinois at Urbana-Champaign Dept. of Electrical and Computer Engineering UrbanaIL United States

This demonstration shows live operation of of PDAVIS polarization event camera reconstruction by the E2P DNN reported in the main CVPR conference paper Deep Polarization Reconstruction with PDAVIS Events (paper 9149 [... 详细信息

ISBN: (纸本)9798350302493

关键词： Polarization

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Identification and control of a Linear Time-Periodic Test Bench Using Harmonic Transfer Functions and LQR controllers

Identification and Control of a Linear Time-Periodic Test Be...

引用

International Conference on control, Decision and Information technologies (CoDIT)

作者： Basak Sert Bahadir Catalbas Ismail Uyanik Dept. of Electrical and Electronics Engineering Hacettepe University Ankara Turkey Defence Systems Technologies Division Aselsan Inc. Ankara Turkey Dept. of Control and Automation Engineering Yildiz Technical University İstanbul Turkey

The increased need for accurately modeling the input-output characteristics of linear time-periodic (LTP) systems necessitates novel identification and control algorithms as well as new test benches for their experimental validation. This paper introduces a simple-to-build test bench for the identification and control of LTP systems. We mechanically coupled the shafts of two DC motors and fed back the angular velocity to the second motor with a time-periodic modulation. This allowed us to imitate a time-periodic load for the first DC motor, thereby yielding an experimental LTP plant. We used Matlab/Simulink target hardware support to implement the entire software in Simulink, which greatly simplifies input design, data collection, and analysis as compared to embedded programming. We used constant-frequency sinusoidal signals for the data collection on the experimental test bench. Subsequently, we estimated the harmonic transfer functions and identified the parameters of a state-space model of the proposed LTP system. We then designed a time-periodic controller in order to regulate the output of the LTP system. We designed a reference-tracking controller along with a Linear Quadratic Integrator (LQI) to improve the system performance. We validated our results through experiments on the physical LTP system plant.

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