Search results for: MACHINE CONTROL
-
Monitoring of the circular saw vibrations with machine vision system.
PublicationPraca przedstawia metodologię wyznaczania drgań obracających się pił tarczowych z wykorzystaniem technik wizyjnych. Na podstawie otrzymanych wyników można wyznaczyc prędkości krytyczne piły oraz podac obszary prędkości zalecanych (najmniejsze wartości drgań poprzecznych piły).
-
Synthesis of irregular motion mechanisms for production machine drives
Publication -
Microgrinding of flat surfaces on single-disk lapping machine
PublicationW pracy przedstawiono wyniki badań mikroszlifowania z kinematyką docierania w układzie jednotarczowym z wykorzystaniem nowego narzędzia wykonanego z pastylek ściernych z ziarnem diamentowym (D3/2) i spoiwem żywicznym. Zakres pracy obejmował przeprowadzenie badań eksperymentalnych i modelowych związanych z analizą promienia krzywizny rys obróbkowych.
-
Microgrinding of flat surfaces on single-disc lapping machine
PublicationW pracy przedstawiono możliwości zastosowania specjalnych narzędzi do mikroszlifowania na docierarce jednotarczowej. Jedno z zastosowanych narzędzi posiada warstwę ścierniwa diamentowego (D64) nałożoną metodą galwaniczną. Drugie przetestowane narzędzie zbudowane zostało z diamentowych pastylek ściernych (D3/2). Przedstawiono analizę kinematyczną i wyniki ubytku materiałowego oraz osiągnięte parametry chropowatości.
-
Machine Learning Modelling and Feature Engineering in Seismology Experiment
Publication -
Hybrid excited electric machine with axial flux bridges
Publication -
Stacking-Based Integrated Machine Learning with Data Reduction
Publication -
Data Reduction Algorithm for Machine Learning and Data Mining
Publication -
Machine learning system for estimating the rhythmic salience of sounds.
PublicationW artykule przedstawiono badania dotyczące wyszukiwania danych rytmicznych w muzyce. W pracy przedstawiono postać funkcji rankingujacej poszczególnych dźwięków frazy muzycznej. Opracowano metodę tworzenia wszystkich możliwych hierarchicznych struktur rytmicznych, zwanych hipotezami rytmicznymi. Otrzymane hipotezy są następnie porządkowane w kolejności malejącej wartości funkcji rankingującej, aby ustalić, która ze znalezionych...
-
Geometric working volume of a satellite positive displacement machine
PublicationThis article describes a method for determining the geometric working volume of satellite positive displacement machines (pump and motor). The working mechanism of these machines is satellite mechanism consisting of two non-circular gears (rotor and curvature) and circular gears (satellites). Two variants of the satellite mechanism are presented. In the first mechanism, the rolling line of the rotor is a sinusoid "wrapped" around...
-
Finishing of Ceramics in a Single-Disk Lapping Machine Configuration
PublicationPrzedstawiono metodę obróbki ceramiki technicznej na zmodifikowanej docierarce jednotarczowej z niezależnym napędem pierścienia prowadzącego. Omówiono przebieg obróbki z wykorzystaniem nowych narzędzi i zastosowaniem ziarna wiązanego.
-
The use of machine learning for face regions detection in thermograms
PublicationThe aim of this study is to analyse the methods of detecting characteristic points of the face in thermographic images. As part of the implementation an extensive analysis of scientific publications covering similar issues both for the analysis of images made in visible light and thermographic images was carried out. On the basis of this analysis, 3 models were selected and then they were implemented and tested on the basis of...
-
MACHINE LEARNING SYSTEM FOR AUTOMATED BLOOD SMEAR ANALYSIS
PublicationIn this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones - the healthy blood cells (erythrocytes) and the pathologic (echinocytes). The separated blood cells are analyzed in terms of their most important features by the eigenfaces method. The features are the...
-
MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublicationAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
-
INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
PublicationThe Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters...
-
A Universal Gains Selection Method for Speed Observers of Induction Machine
PublicationProperties of state observers depend on proper gains selection. Each method of state estimation may require the implementation of specific techniques of finding those gains. The aim of this study is to propose a universal method of automatic gains selection and perform its verification on an induction machine speed observer. The method utilizes a genetic algorithm with fitness function which is directly based on the impulse response...
-
MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publication—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...
-
Noise profiling for speech enhancement employing machine learning models
PublicationThis 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...
-
Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
-
Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublicationLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
-
Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
-
Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublicationThe 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...
-
Testing of Technical Fabrics under Fast Camera Control
PublicationThe dynamic development of measurement and recording techniques has been changing the way one conceives material strength. In this study, two different methods of evaluating the strength of fabrics are compared. The first is the typical and commonly used technique based on the use of a testing machine. The second method uses the so-called “fast camera” to monitor the entire process of the destruction of a fabric sample and analyse...
-
Calculation of self and mutual inductances of the switched reluctance machine mathematical model.
PublicationA mathematical model of the switched reluctance machine (SRM) in a drive system obtained using Lagrange's energy method and a method of calculation of self and mutual inductances of the SRM are presented in the paper. The self and mutual inductances are elements of Lagrange's function in generalised coordinates and have been calculated using the finite element method (FEM). Selected calculation results for the particular machine...
-
Predictions of cervical cancer identification by photonic method combined with machine learning
PublicationCervical 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...
-
Dangerous sound event recognition using Support Vector Machine classifiers
PublicationA method of recognizing events connected to danger based on their acoustic representation through Support Vector Machine classification is presented. The method proposed is particularly useful in an automatic surveillance system. The set of 28 parameters used in the classifier consists of dedicated parameters and MPEG-7 features. Methods for parameter calculation are presented, as well as a design of SVM model used for classification....
-
Model-Based Adaptive Machine Learning Approach in Concrete Mix Design
PublicationConcrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...
-
Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublicationA 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...
-
Core loss resistance impact on sensorless speed control of an induction motor using hybrid adaptive sliding mode observer
PublicationInduction motors (IMs) experience power losses when a portion of the input power is converted to heat instead of driving the load. The combined effect of copper losses, core losses, and mechanical losses results in IM power losses. Unfortunately, the core losses in the motor, which have a considerable impact on its energy efficiency, are not taken into account by the generally employed dynamic model in the majority of the studies. Due...
-
Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublicationIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
-
Digital Interaction and Machine Intelligence. Proceedings of MIDI’2021 – 9th Machine Intelligence and Digital Interaction Conference, December 9-10, 2021, Warsaw, Poland
Publication -
Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublicationThe continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...
-
Modeling of generator performance of BLDC machine using mathematica software
PublicationW artykule porównano trzy modele maszyny bezszczotkowej prądu stałego z magnesami trwałymi(BLDC) w przypadku pracy prądnicowej. Najprostszy model qd0 sprowadzono do dwóch osi prostopadłychzwiązanych z wirnikiem [3]. Zakłada on sinusoidalny rozkład pola w szczelinie. Model opisany wosiach naturalnych wyprowadzono w oparciu o formalizm Lagrnage'a [4] i moŜe uwzględniać dowolnyrozkład pola wzbudzonego przez magnesy trwałe. Model pośredni...
-
Hybrid-Excited Permanent Magnet-Assisted Synchronous Reluctance Machine
Publication -
Performance Evaluation of an Axial Flux Machine with a Hybrid Excitation Design
Publication -
An approach to machine classification based on stacked generalization and instance selection
Publication -
Clamping precision of a cilcular saw blade on a spindle of a sawing machine
PublicationW pracy przedstawiono analizę dokładności mocowania piły tarczowej na wrzecionie pilarki, w której uwzgledniono jedynie tolerancje wykonania układu wrzeciona pilarki i piły tarczowej.
-
Portable computer measurement system of machine tools in wood industry
PublicationW 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...
-
The methods of fretting wear prevention in machine elements : chapter 9
PublicationOpisano skutki procesu frettingu w elementach maszyn i warunki ich wystąpienia. Przedstawiono przegląd metod zapobiegania zużyciu frettingowemu i jego ograniczania. Opisano laboratoryjne badania zużywania frettingowego wybranych skojarzeń w warunkach umożliwiających ograniczanie zużycia.
-
The Influence of Abrasive Machine on Temperature During One Side Lapping
PublicationPrzedstawiono wyniki badań temperatury układu wykonawczego docierarki jednotarczowej. Analizowano temperaturę trzech pierścieni prowadzących separatory przy wykorzystaniu kamery termograficznej V-20 II firmy VIGO System S.A.
-
Playback detection using machine learning with spectrogram features approach
PublicationThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
-
Optimization of chip removing system operation in circular sawing machine
PublicationThe 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...
-
The methodology of design of satellite working mechanism of positive displacement machine
PublicationIn this paper is described a methodology of design of satellite mechanism consisting of two noncircular gears (externally toothed rotor and internally toothed curvature) and circular gears (satellites). In the presented methodology is assumed that the rotor pitch line is known, and the curvature pitch line is necessary to designate. The presented methodology applies to mechanisms for which the number of the curvature humps is at...
-
LOW PLACTICITY BURNISHING PROCESSES. Fundaments, tools and machine tools
PublicationW obszernej monografii (530 stron) autor przedstawił w sposób kompleksowy zagadnienia związane z wykończeniową metodą obróbki części maszyn przez powierzchniową obróbkę plastyczną-nagniataniem. Jest to pierwsza książka w języku angielskim poświęcona tej bezwiórowej i ekologicznej metodzie obróbki. W wielu przypadkach w technologii różnorodnych części maszyn i innych urządzeń, nagniatanie może zastąpić operację szlifowania. Ma to...
-
2D Mathematical Model of the Commutator Sliding Contact of an Electrical Machine
PublicationW artykule przedstawiono model matematyczny 2D komutatorowego zestyku ślizgowego z wieloma stopniami swobody. W modelu uwzględniono zmienne wymuszenia działające na szczotkę. Wymuszenia te są wynikiem falistości wirującego komutatora. Szczotka została zamodelowana jako system wielu mas, elementów sprężystych i tłumików rozłożonych w kierunku stycznym i promieniowym. Zamodelowano wszystkie oddziaływania lepkosprężyste pomiędzy komutatorem...
-
Sensorless Disturbance Detection for Five Phase Induction Motor with Third Harmonic Injection
PublicationThe paper presents a sensorless disturbance detection procedure that was done on a five phase induction motor with third harmonic injection. A test bench was developed where a three phase machine serves as disturbance generator of different frequencies. The control of the machines is based on multi scalar variables that ensures an independent control of the motor EMF and the rotor flux. For disturbance identification a speed observer...
-
Possibility of Fault Detection in Sensorless Electric Drives
PublicationThe work presents a fault detection method for an induction motor drive system with inverter output filter. This approach make use of a load torque state observer, which complete structure is presented along with the used control structure. Moreover, the demonstrated drive system operates without rotor speed measurement in conjunction with the multiscalar control. The verification of the demonstrated idea was performed on an experimental...
-
Modeling lignin extraction with ionic liquids using machine learning approach
PublicationLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
-
A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublicationTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
-
Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...