Search results for: SINGLE MACHINE
-
Improved RSS-Based DoA Estimation Accuracy in Low-Profile ESPAR Antenna Using SVM Approach
PublicationIn this paper, we have shown how the overall performance of direction-of-arrival (DoA) estimation using lowprofile electronically steerable parasitic array radiator (ESPAR) antenna, which has been proposed for Internet of Things (IoT) applications, can significantly be improved when support vector machine (SVM) approach is applied. Because the SVM-based DoA estimation method used herein relies solely on received signal strength...
-
Reducing common mode voltage and bearing currents in quasi - resonant DC - link inverter
PublicationIn the paper, a concept of separation of an inverter-fed induction motor drive from its mains supply by two transistor switches inserted in the dc-link circuit is reexamined based on the proposed parallel quasi-resonant dc-link inverter (PQRDCLI). The objective of the paper is to show an advantage of the proposed topology in limiting high frequency common mode voltage and bearing currents. In the laboratory setup, an induction...
-
Crack propoagation in MgO-PSZ ceramic materials
PublicationThe properties of ceramic materials such as elevated hardness, high temperature capability, low coefficient of thermal expansion are of interest for rolling element materials. Widely used ceramic materials in engineering applications are silicon nitride, zirconia and alumina. The paper presents an experimental study of the fatigue life of MgO-PSZ ceramic material in lubricated contact with defined types of cracks. A ceramic angular...
-
RAPORT - EKSPERTYZA Z POMIARÓW DRGAŃ LINII WAŁÓW NA JEDNOSTCE ORP „DĄBIE”
PublicationEkspertyza diagnostyczna dotycząca stanu technicznego dwóch linii transmisji mocy (linii wałów) opracowana na podstawie przeprowadzonych pomiarów drgań w 26 punktach pomiarowych, przy jednoczesnej pracy silników napędowych L i PB (wspólnej pracy linii wałów obu burt), w II zakresach ustalonego obciążenia „pół-naprzód” i „cała-naprzód”. Pomiary prędkości i przyspieszeń drgań generowanych przez węzły konstrukcyjne okrętowego układu...
-
Half-Order Modeling of Saturated Synchronous Machine
PublicationNoninteger order systems are used to model diffusion in conductive parts of electrical machines as they lead to more compact and knowledge models but also to improve their precision. In this paper a linear half-order impedance model of a ferromagnetic sheet deduced from the diffusion of magnetic field is briefly introduced. Then, from physical considerations and finite elements simulation, the nonlinear half-order impedance model...
-
„Eulerian – Eulerian” versus ,,Eulerian –Lagrangean” models of condensation
PublicationLiquid phase in the flowing vapor through stages of the steam turbine is the cause of a lot of failures. Nowadays, due to work of steam turbines at partial load, process of homogeneous and heterogeneous condensation still is current. The formation of drops of condensate under conditions other than nominal operation of turbine is a process still unknown. Engineers and designers involved in the development of power station machines...
-
Histogram of Oriented Gradients with Cell Average Brightness for Human Detection
PublicationA modification of the descriptor in a human detector using Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM) is presented. The proposed modification requires inserting the values of average cell brightness resulting in the increase of the descriptor length from 3780 to 3908 values, but it is easy to compute and instantly gives ≈ 25% improvement of the miss rate at 10‒4 False Positives Per Window (FPPW). The...
-
MCSA with Normalized Triple Covariance as a bearings diagnostic indicator in an induction motor
PublicationStatistics of bearing failures in induction motors indicate, that they constitute more than 40% of IM damage, therefore bearing diagnosis is very important. Vibration methods for bearing diagnostics have one major disadvantage - they require the availability of the machine for sensors installation. This is the reason for seeking new methods based on motor supply current analysis. Diagnosis of induction motors, conducted remotely...
-
Optimal spindle speed determination for vibration reduction during ball-end milling of flexible details
PublicationIn the paper a method of optimal spindle speed determination for vibration reduction during ball-end milling of flexible details is proposed. In order to reduce vibration level, an original procedure of the spindle speed optimisation, based on the Liao–Young criterion, is suggested. As the result, an optimal, constant spindle speed value is determined. For this purpose, on-stationary computational model of machining process is...
-
Development of a Control System for an Autonomous Seaplane
PublicationSelf-driving vehicles, also branded as driverless vehicles, autonomous vehicles, or robotic vehicles, are transport systems that can operate with a reduced human impact or even with any human input at all. The content of the present paper is limited to three types of potential applications: Unmanned Surface Vehicles (USVs), Autonomous Underwater Vehicles (AUVs) and Unmanned Aerial Vehicles (UAV). We set our particular focus on...
-
Induction motor bearings diagnostic indicators based on MCSA and normalized triple covariance
PublicationInduction motors are one of the most widely used electrical machines. Statistics of bearing failures of induction motors indicate, that they constitute more than 40% of induction motor damage. Therefore, bearing diagnosis is so important for trouble-free work of induction motors. The most common methods of bearing diagnosis are based on vibration signal analysis. The main disadvantage of those methods is the need for physical access...
-
Engineering education for smart grid systems in the quasi-industrial environment of the LINTE^2 laboratory
PublicationSmart grid systems are revolutionising the electric power sector, integrating advanced technologies to enhance efficiency, reliability and sustainability. It is important for higher education to equip the prospective smart grid professional with the competencies enabling them to navigate through the related complexities and drive innovation. To achieve this, interdisciplinary education programmes are necessary, addressing inter...
-
Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublicationWe proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...
-
Wireless Body Area Network for Preventing Self-Inoculation Transmission of Respiratory Viral Diseases
PublicationThis paper proposes an idea of Wireless Body Area Networks (WBANs) based on Bluetooth Low-Energy (BLE) standards to recognize and alarm a gesture of touching the face, and in effect, to prevent self-inoculation of respiratory viral diseases, such as COVID-19 or influenza A, B, or C. The proposed network comprises wireless modules placed in bracelets and a necklace. It relies on the received signal strength indicator (RSSI) measurements...
-
TF-IDF weighted bag-of-words preprocessed text documents from Simple English Wikipedia
Open Research DataThe SimpleWiki2K-scores dataset contains TF-IDF weighted bag-of-words preprocessed text documents (raw strings are not available) [feature matrix] and their multi-label assignments [label-matrix]. Label scores for each document are also provided for an enhanced multi-label KNN [1] and LEML [2] classifiers. The aim of the dataset is to establish a benchmark...
-
Noise sources in Raman spectroscopy of biological objects
PublicationWe present an overview of noise sources deteriorating the quality of the recorded biological Raman spectra and the ability to determine the specimen composition. The acquired Raman spectra exhibit intense additive noise components or drifts because of low intensity of the scattered light. Therefore we have to apply expensive or bulky measurement setups to limit their inherent noise or to apply additional signal processing to reduce...
-
Influence of rhamnolipids and ionic cross-linking conditions on the mechanical properties of alginate hydrogels as a model bacterial biofilm
PublicationThe literature indicates the existence of a relationship between rhamnolipids and bacterial biofilm, as well as the ability of selected bacteria to produce rhamnolipids and alginate. However, the influence of biosurfactant molecules on the mechanical properties of biofilms are still not fully understood. The aim of this research is to determine the effect of rhamnolipids concentration, CaCl2 concentration, and ionic cross-linking...
-
EXPERIMENTAL AND NUMERICAL INVESTIGATION ON SPECIMEN GEOMETRY EFFECT ON THE CTOD VALUE FOR VL-E36 SHIPBUILDING STEEL
PublicationThere are special cases in the marine industry, where additional material tests, such as the fracture toughness test, must be performed. Additional fracture toughness tests, such as CTOD (Crack Tip Opening Displacement), are typically performed on three-point bend specimens. The dimension that defines all the specimen dimensions is the thickness of the material to be tested. It is recommended by classification societies (e.g. DNVGL)...
-
Planning optimised multi-tasking operations under the capability for parallel machining
PublicationThe advent of advanced multi-tasking machines (MTMs) in the metalworking industry has provided the opportunity for more efficient parallel machining as compared to traditional sequential processing. It entailed the need for developing appropriate reasoning schemes for efficient process planning to take advantage of machining capabilities inherent in these machines. This paper addresses an adequate methodical approach for a non-linear...
-
Critical Review on Robust Speed Control Techniques for Permanent Magnet Synchronous Motor (PMSM) Speed Regulation
PublicationThe permanent magnet synchronous motor (PMSM) is a highly efficient energy saving machine. Due to its simple structural characteristics, good heat radiation capability, and high efficiency, PMSMs are gradually replacing AC induction motors in many industrial applications. The PMSM has a nonlinear system and lies on parameters that differ over time with complex high-class dynamics. To achieve the excessive performance operation...
-
Automatic classification and mapping of the seabed using airborne LiDAR bathymetry
PublicationShallow coastal areas are among the most inhabited areas and are valuable for biodiversity, recreation and the economy. Due to climate change and sea level rise, sustainable management of coastal areas involves extensive exploration, monitoring, and protection. Current high-resolution remote sensing methods for monitoring these areas include bathymetric LiDAR. Therefore, this study presents a novel methodological approach to assess...
-
Quantification of ultrafine airborne particulate matter generated by the wear of car brake materials
PublicationThe wear of car brakes is one of the main sources of airborne particulate matter in urban environments. Ultrafine wear particles are of special environmental interest since they can easily penetrate the human body through inhalation and cause various diseases. In the present study, the contribution of ultrafine particles to airborne particulate matter emitted from car brake materials was investigated under different friction conditions....
-
A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone Sensors
PublicationIn recent years, emotion recognition algorithms have achieved high efficiency, allowing the development of various affective and affect-aware applications. This advancement has taken place mainly in the environment of personal computers offering the appropriate hardware and sufficient power to process complex data from video, audio, and other channels. However, the increase in computing and communication capabilities of smartphones,...
-
The Method of Selecting the Interval of Functional Tests Taking into Account Economic Aspects and Legal Requirements
PublicationThe article discusses the problem of choosing the optimal frequency of functional tests, taking into account the reliability and law requirements, but also the impact of business aspects in the company. The subject of functional test interval is well described for purposes of the process industry. Unfortunately, this is not the case for the machinery safety functions with low demand mode. This is followed by a presentation of the...
-
NUMERICAL SIMULATIONS OF HONING PROCESS OF THIN WALL CYLINDER LINERS, WITH CONSTANT AND WITH VARIABLE THICKNESS OF WALL OF HONED PARTS
PublicationNumerical simulations of honing process of thin-wall cylinder liners, with constant and with variable thickness of the wall of honed workpieces can improve and can help to conduct the experimental research of honing process and can improve the honing process. A very valuable research assumption, before performing the numerical analysis of computer simulation of honing process, is the measurement of the real geometry of the honing...
-
A highly-efficient technique for evaluating bond-orientational order parameters
PublicationWe propose a novel, highly-efficient approach for the evaluation of bond-orientational order parameters (BOPs). Our approach exploits the properties of spherical harmonics and Wigner 3jj-symbols to reduce the number of terms in the expressions for BOPs, and employs simultaneous interpolation of normalised associated Legendre polynomials and trigonometric functions to dramatically reduce the total number of arithmetic operations....
-
Thin-walled frames and grids - statics and dynamics
PublicationFrames and grids assembled with thin-walled beams of open cross-section are widely applied in various civil engineering and vehicle or machine structures. Static and dynamic analysis of theses structures may be carried out by means of different models, startingfrom the classical models made of beam elements undergoing the Kirchhoff assumptions to the FE discretization of whole frame into plane elements. The former model is very...
-
Sounding Mechanism of a Flue Organ Pipe—A Multi-Sensor Measurement Approach
PublicationThis work presents an approach that integrates the results of measuring, analyzing, and modeling air flow phenomena driven by pressurized air in a flue organ pipe. The investigation concerns a Bourdon organ pipe. Measurements are performed in an anechoic chamber using the Cartesian robot equipped with a 3D acoustic vector sensor (AVS) that acquires both acoustic pressure and air particle velocity. Also, a high-speed camera is employed...
-
Active Learning on Ensemble Machine-Learning Model to Retrofit Buildings Under Seismic Mainshock-Aftershock Sequence
PublicationThis research presents an efficient computational method for retrofitting of buildings by employing an active learning-based ensemble machine learning (AL-Ensemble ML) approach developed in OpenSees, Python and MATLAB. The results of the study shows that the AL-Ensemble ML model provides the most accurate estimations of interstory drift (ID) and residual interstory drift (RID) for steel structures using a dataset of 2-, to 9-story...
-
Finger Vein Presentation Attack Detection Method Using a Hybridized Gray-Level Co-Occurrence Matrix Feature with Light-Gradient Boosting Machine Model
PublicationPresentation Attack Detection (PAD) is crucial in biometric finger vein recognition. The susceptibility of these systems to forged finger vein images is a significant challenge. Existing approaches to mitigate presentation attacks have computational complexity limitations and limited data availability. This study proposed a novel method for identifying presentation attacks in finger vein biometric systems. We have used optimal...
-
Crack monitoring in concrete beams under bending using ultrasonic waves and coda wave interferometry: the effect of excitation frequency on coda
PublicationConcrete is one of the most widely used construction materials in the world. In recent years, various non-destructive testing (NDT) and structural health monitoring (SHM) techniques have been investigated to improve the safety and control of the current condition of concrete structures. This study focuses on micro-crack monitoring in concrete beams. The experimental analysis was carried out on concrete elements subjected to three-point...
-
Path-based methods on categorical structures for conceptual representation of wikipedia articles
PublicationMachine learning algorithms applied to text categorization mostly employ the Bag of Words (BoW) representation to describe the content of the documents. This method has been successfully used in many applications, but it is known to have several limitations. One way of improving text representation is usage of Wikipedia as the lexical knowledge base – an approach that has already shown promising results in many research studies....
-
Society 4.0: Issues, Challenges, Approaches, and Enabling Technologies
PublicationThis guest edition of Cybernetics and Systems is a broadening continuation of our last year edition titled “Intelligence Augmentation and Amplification: Approaches, Tools, and Case Studies”. This time we cover research perspective extending towards what is known as Society 4.0. Bob de Vit brought the concept of Society 4.0 to life in his book “Society 4.0 – resolving eight key issues to build a citizens society”. From the Systems...
-
Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublicationIn recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for...
-
Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublicationThis article introduces an innovative method for achieving low-cost and reliable multi-objective optimization (MO) of microwave passive circuits. The technique capitalizes on the attributes of surrogate models, specifically artificial neural networks (ANNs), and multi-resolution electromagnetic (EM) analysis. We integrate the search process into a machine learning (ML) framework, where each iteration produces multiple infill points...
-
Data on LEGO sets release dates and worldwide retail prices combined with aftermarket transaction prices in Poland between June 2018 and June 2023
PublicationThe dataset contains LEGO bricks sets item count and pricing history for AI-based set pricing prediction. The data spans the timeframe from June 2018 to June 2023. The data was obtained from three sources: Brickset.com (LEGO sets retail prices, release dates, and IDs), Lego.com official web page (ID number of each set that was released by Lego, its retail prices, the current status of the set) and promoklocki.pl web page (the retail...
-
Will NILM Technology Replace Multi-Meter Telemetry Systems for Monitoring Electricity Consumption?
PublicationThe estimation of electric power utilization, its baseload, and its heating, light, ventilation, and air-conditioning (HVAC) power component, which represents a very large portion of electricity usage in commercial facilities, are important for energy consumption controls and planning. Non-intrusive load monitoring (NILM) is the analytical method used to monitor the energy and disaggregate total electrical usage into appliance-related...
-
Accounting for the distributions of input quantities in the procedure for the measurement uncertainty evaluation when calibrating the goniometer
PublicationThe discords concerning the measurement uncertainty evaluation in the Guide to the Expressing of Uncertainty in Measurement (GUM) and its Supplement 1 are considered. To overcome these discords, the authors of the paper propose to use the kurtosis method and the law of the propagation of the expanded uncertainty. Using the example of the goniometer calibration, the features of accounting for the distribution laws of input quantities...
-
Slowly-closing valve behaviour during steam machine accelerated start-up
PublicationThe 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...
-
Acoustic emission signals in concrete beams under 3-point bending (polyolefin and steel fibre concrete)
Open Research DataThe DataSet contains the results of the mechanical behaviour of concrete beams with dimensions 40 x 40 x 160 cm3 under the 3-point bending. All specimens were manufactured based on the same concrete mixture composed of cement CEM I 42.5R (380 kg/m3), water (165 kg/m3), aggregate 0/2 mm (648 kg/m3), aggregate 2/8 mm (426 kg/m3), aggregate 8/16 mm (754...
-
Acoustic emission signals in concrete beams under 3-point bending (plain concrete, steel fibre reinforced concrete, steel bar reinforced concrete)
Open Research DataThe DataSet contains the results of the mechanical behaviour of concrete beams with dimensions 40 x 40 x 160 cm3under the 3-point bending. Two concrete mixes, both based on the same design, were produced in the test programme. Mixture #1 was the plain concrete (PC), consisting of cement CEM I 42.5R (380 kg/m3), water (165 kg/m3), aggregate 0/2 mm (648...
-
Future Skills and Education in a Computerized World
PublicationAs computerization of Western economies has advanced, the supply of the demand for routine cognitive tasks and routine manual tasks has fallen. Computerization has increased labour input of nonroutine cognitive tasks which has favourized high educated workers. Similarly, there is clear evidence of an increase in demand for high skilled workforce which originates from poor machine performance of nonroutine...
-
Effect of selective laser treatment on initiation of fatigue crack in the main part of an undercarriage drag strut
PublicationThis paper presents the results of material characterization and a fatigue test conducted for a laser-re-melted drag strut used in an aircraft landing gear. The drag strut was re-melted with a CO2 laser beam. Eight re-melted paths were made in the form of spiral lines along the axis of the drag strut. Next, the drag strut was subjected to variable loads on a testing machine simulating loads occurring when an aircraft lands. The...
-
Technical Engine for Democratization of Modeling, Simulations, and Predictions
PublicationComputational science and engineering play a critical role in advancing both research and daily-life challenges across almost every discipline. As a society, we apply search engines, social media, and se- lected aspects of engineering to improve personal and professional growth. Recently, leveraging such aspects as behavioral model analysis, simulation, big data extraction, and human computation is gain- ing momentum. The nexus...
-
Comparison of Surface Quality and Tool-Life of Glulam Window Elements after Planing
PublicationThe quality of the surface of wooden elements, that have been planed, has a crucial importance in the whole production process, since the obtained effects affect the quality of wooden surface after fi nishing (painting). The occurrence of defects is usually the reason for qualifying a workpiece as scrap or for requiring additional work. This paper presents the selected results of research of the effect of the cutting tool wear...
-
Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublicationFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
-
Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants
PublicationThe use of metal halide perovskites in photocatalytic processes has been attempted because of their unique optical properties. In this work, for the first time, Pb-free Bi-based perovskites of the Cs3Bi2X9 type (X = Cl, Br, I, Cl/Br, Cl/I, Br/I) were synthesized and subjected to comprehensive morphological, structural, and surface analyses, and photocatalytic properties in the phenol degradation reaction were examined. Furthermore,...
-
Metal–Organic Frameworks (MOFs) for Cancer Therapy
PublicationMOFs exhibit inherent extraordinary features for diverse applications ranging from catalysis, storage, and optics to chemosensory and biomedical science and technology. Several procedures including solvothermal, hydrothermal, mechanochemical, electrochemical, and ultrasound techniques have been used to synthesize MOFs with tailored features. A continued attempt has also been directed towards functionalizing MOFs via “post-synthetic...
-
Properties of Old Concrete Built in the Former Leipziger Palace
PublicationThis research aims to determine the mechanical, chemical, and physical properties of old concrete used in the former Leipziger Palace in Wrocław, Poland. The cylindrical specimens were taken from the basement concrete walls using a concrete core borehole diamond drill machine. The determination of the durability and strength of old concrete was based on specified chosen properties of the old concrete obtained through the following...
-
Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublicationForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...