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Wyniki wyszukiwania dla: POLYPHASE MACHINE - INDUCTION MACHINE - MULTISCALAR MODEL - OBSERVER - CONTROL SYSTEM
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MACHINE VISION AND APPLICATIONS
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Quantum Machine Intelligence
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublikacjaOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Designing acoustic scattering elements using machine learning methods
PublikacjaIn the process of the design and correction of room acoustic properties, it is often necessary to select the appropriate type of acoustic treatment devices and make decisions regarding their size, geometry, and location of the devices inside the room under the treatment process. The goal of this doctoral dissertation is to develop and validate a mathematical model that allows predicting the effects of the application of the scattering...
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Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublikacjaThe acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...
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Hybrid Processing by Turning and Burnishing of Machine Components
PublikacjaThe paper presents a method of hybrid manufacturing process of long 5 shafts and deep holes by simultaneous turning and burnishing method. The tech- 6 nological results of the research focus on the influence of the basic technological 7 parameters of this process on the surface roughness of piston rods of hydraulic 8 cylinders. Research results are presented in the graphs as well as mathematical 9 formula. Set of samples were made...
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Decisional DNA (DDNA) Based Machine Monitoring and Total Productive Maintenance in Industry 4.0 Framework
PublikacjaThe entire manufacturing spectrum is transforming with the advent of Industry 4.0. The features of Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA) were utilized for developing Virtual Engineering Objects (VEO), Virtual Engineering Process (VEP) and Virtual Engineering Factory (VEF), which in turn facilitate the creation of smart factories. In this study, DDNA based Machine Monitoring for Total Maintenance...
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Load effect impact on the exploitation of concrete machine foundations used in the gas and oil industry
PublikacjaMachine foundations is a critical topic in the gas and oil industry, which design and exploitation require extensive technical knowledge. Machine foundations are the constructions which are intended for mounting on it a specific type of machine. The foundation has to transfer dynamic and static load from machine to the ground. The primary difference between machine foundations and building foundations is that the machine foundations...
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Support Vector Machine Applied to Road Traffic Event Classification
PublikacjaThe aim of this paper is to present results of road traffic event signal recognition. First, several types of systems for road traffic monitoring, including Intelligent Transport System (ITS) are shortly described. Then, assumptions of creating a database of vehicle signals recorded in different weather and road conditions are outlined. Registered signals were edited as single vehicle pass by. Using the Matlab-based application...
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Krzysztof Jan Kaliński prof. dr hab. inż.
OsobyUkończył studia magisterskie na Wydziale Mechanicznym Technologicznym (MT) PG (1980, dyplom z wyróżnieniem). Stopień doktora otrzymał na Wydziale Budowy Maszyn PG (1988, praca wyróżniona), stopień doktora habilitowanego na Wydziale Mechanicznym (WM) PG (2002, praca wyróżniona), a tytuł profesora nauk technicznych – w 2013 r. Od 2015 r. jest profesorem zwyczajnym, a od 2019 r. - profesorem. Obszar jego badań naukowych obejmuje:...
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Wykorzystanie modelu silnika indukcyjnego klatkowego do prądowej diagnostyki jego łożysk. Application of induction machine model for current diagnostics of bearings
PublikacjaW pracy podano widmo prądu stojana dla silnika normalnego oraz wprawianego w drgania o nastawianej częstotliwości. Drgania korpusu wirnika skutkują uginaniem się wirnika, co symuluje bicie wirnika od uszkodzenia łożysk. Podano też model matematyczny silnika, dopuszczający niecentryczność wirnika. Podano widmo prądu stojana przy pracy z wibracjami wirnika odwzorowującymi w pewnym przybliżeniu wibracje od uszkodzonych łożysk.
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Control System Design for Dynamic Positioning using Vectorial Backstepping
PublikacjaThe problem of synthesis a dynamic positioning system for low frequency model of surface vessel was considered in this paper. The recursive vectorial backstepping control design was used to keep a fixed position and heading in presence of wave disturbances. The passive observer was introduced to smooth the measurements and to estimate the velocities needed for the control algorithm. The computer simulation results were given to...
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Control System Design - 2022
Kursy Online3 sem (II st.) AiR
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Control System Design - 2023
Kursy Online3 sem (II st.) AiR
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Control System Design - 2024
Kursy Online3 sem (II st.) AiR
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Agricultural products' storage control system
PublikacjaThe paper discusses the idea and the design of a remote control system for storage management of agricultural products which temperature may rise as the result of biological processes during the storage. An actual potatoes storehouse is discussed as an application for the proposed automation system. Because of existing buildings and infrastructure at the farm, wireless data transfer system has been proposed for communication between...
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Model of aeration system at biological wastewater treatment plant for control design purposes
PublikacjaThe wastewater treatment plant (WWTP) is a dynamic, very complex system, in which the most important control parameter is the dissolved oxygen (DO) con-centration. The air is supplied to biological WWTP by the aeration system. Aera-tion is an important and expensive activity in WWTP. The aeration of sewage ful-fils a twofold role. Firstly, oxygen is provided as the main component for biolog-ical processes. Secondly, it supports...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublikacjaCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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SSFR Test of Synchronous Machine for Different Saturation Levels using Finite-Element Method
PublikacjaIn this paper the StandStill Frequency Response characteristics (SSFR) of saturated synchronous generator (SG) have been calculated using Finite Element Method (FEM) analysis. In order to validate proposed approach for unsaturated conditions FEM simulation from Flux2D software has been compared with the measurements performed on the 10 kVA, 4- poles synchronous machine ELMOR GCe64a of salient rotor construction, equipped with a...
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Scientific research in the Department of Machine Design and Automotive Engineering
PublikacjaShort descriptions of various research subjects taken up at the Department of Machine Design and Automotive Engineering are included in the paper. The subjects cover a wide range of bearing systems and tribology research and the research on tires and road surfaces. A third field of activity is biomedical engineering – with the attempts to improve methods of modelling biological materials in FEM calculations. The Department has...
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Optimization of chip removing system operation in circular sawing machine
PublikacjaThe paper presents the optimization of the wood chips removing system in the sliding table saw. Chips are generated during the cutting of the material. The attention was focused on the upper casing of mentioned system. The methodical experimental studies of the pressure distribution inside the casing during the wood chip removing operation for the selected rotational speed of saw blade with a diameter of 300 mm and 450 mm were...
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Portable computer measurement system of machine tools in wood industry
PublikacjaW pracy przedstawiono przenośny system diagnostyczny przeznaczony do oceny pracy obrabiarek skrawających i urządzeń przemysłu drzewnego. Ocena procesu obróbczego odbywa się na podstawie pomiaru wielkości mechanicznych, takich jak: prędkość obrotowa , przemieszczenia oraz przyspieszenia. Korzystanie z programów komputerowych, w które system jest wyposażony, pozwala użytkownikowi maszyn na przeprowadzanie szczegółowych analiz, dzięki...
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A pilot study to assess manufacturing processes using selected point measures of vibroacoustic signals generated on a multitasking machine
PublikacjaThe article presents the method for the evaluation of selected manufacturing processes using the analysis of vibration and sound signals. This method is based on the use of sensors installed outside the machining zone, allowing to be used quickly and reliably in real production conditions. The article contains a developed measurement methodology based on the specific location of microphones and vibration transducers mounted on...
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublikacjaControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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Simulation Studies of Control Systems for Doubly Fed Induction Generator Supplied by the Current Source Converter
PublikacjaThe control system for a Doubly Fed Induction Generator (DFIG) supplied by a grid-connected Current Source Converter (CSC) is presented in this paper. Nonlinear transformation of DFIG model to the multi-scalar form is proposed. The nonlinear control strategy of active and reactive power of DFIG is realized by feedback linearization. In the proposed control scheme, the DFIG model and CSI parameters are included. Two Proportional-Integral...
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Machine-to-Machine communication and data processing approach in Future Internet applications
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Network lifetime maximization in wireless mesh networks for machine-to-machine communication
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Computer aided machine design
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Machine Design - selected problems
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Machine Design 3, PG_00042104
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Machine Design PG_00059691 2024
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublikacjaA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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Machine-aided detection of SARS-CoV-2 from complete blood count
PublikacjaThe current gold standard for SARS-CoV-2 detection methods lacks the functionality to perform population screening. Complete blood count (CBC) tests are a cost-effective way to reach a wide range of people – e.g. according to the data of the Central Statistical Office of Poland from 2016, there are 3,000 blood diagnostic laboratories in Poland, and 46% of Polish people have at least one CBC test per year. In our work, we show...
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Noise profiling for speech enhancement employing machine learning models
PublikacjaThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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MRAS-Based Switching Linear Feedback Strategy for Sensorless Speed Control of Induction Motor Drives
PublikacjaThis paper presents a newly designed switching linear feedback structure of sliding mode control (SLF-SMC) plugged with an model reference adaptive system (MRAS) based sensorless fieldoriented control (SFOC) for induction motor (IM). Indeed, the performance of the MRAS depends mainly on the operating point and the parametric variation of the IM. Hence, the sliding mode control (SMC) could be considered a good control alternative...
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Concrete mix design using machine learning
PublikacjaDesigning a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...
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Slowly-closing valve behaviour during steam machine accelerated start-up
PublikacjaThe paper discusses the state of stress in a slowly-closing valve during accelerated start-up of a steam turbine. The valve is one of the first components affected by high temperature gradients and is a key element on which the power, efficiency and safety of the steam system depend. The authors calibrated the valve model based on experimental data and then performed extended Thermal-FSI analyses relative to experiment. The issue...
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Fundamentals of Machine Design I
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Fundamental of Machine Design III
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Fundamentals of Machine Design II
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Fundamentals of Machine Design III
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Fundamentals of Machine Design I
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublikacjaBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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Augmented speed control scheme of dual induction motors with mutual flux angle control loop
PublikacjaThis paper proposes an augmented speed control scheme of dual induction motors fed by a five-leg voltage source inverter (VSI) with a common/shared-leg. An additional control loop is proposed here and based on the mutual flux angle – the difference between flux angular positions of the IMs. The main purpose of this research is to minimize the energy losses in the common inverter leg by controlling the mutual flux angle, at equal...
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Neural Networks, Support Vector Machine and Genetic Algorithms for Autonomous Underwater Robot Support
PublikacjaIn this paper, artificial neural networks, a classification technique called support vector machine and meta-heuristics genetic algorithm have been considered for development in autonomous underwater robots. Artificial neural networks have been used for seabed modelling as well as support vector machine has been applied for the obstacles classification to avoid some collision problems. Moreover, genetic algorithm has been applied...