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Search results for: a posteriori error estimator
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublicationThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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Image Classification Based on Video Segments
PublicationIn the dissertation a new method for improving the quality of classifications of images in video streams has been proposed and analyzed. In multiple fields concerning such a classification, the proposed algorithms focus on the analysis of single frames. This class of algorithms has been named OFA (One Frame Analyzed).In the dissertation, small segments of the video are considered and each image is analyzed in the context of its...
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Redundantly Actuated 3RRR Parallel Planar Manipulator - Numerical Analyses of its Dynamics Sensitivity on Modifications of its Platform’s Inertia Parameters
PublicationIn the paper, numerical analyses, as well as dynamics of a complex mechanism, are presented. Two objectives are crucial for the paper: inverse dynamic model is needed (dedicated to be use in the model predictive controller); an identification method is searched (some trajectory parameters are controlled, when specific trajectory is tracked under an open-loop model-based control), as selected parameters must be identified for the...
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Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
PublicationIn this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...
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The study on the appearance of deformation defects in the yacht lamination process using an AI algorithm and expert knowledge
PublicationThis article describes the application of the A-priori algorithm for defining the rule-based relationships between individual defects caused during the lamination process, affecting the deformation defect of the yacht shell. The data from 542 yachts were collected and evaluated. For the proper development of the algorithm, a technological process of the yacht lamination supported by expert decisions was described. The laminating...
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Selected aspects of two-phase flow studies using different visualization techniques in minichannels
PublicationThe subject of the study is to present the possibility of the use of visualization techniques in the researches on two-phase flows, carried out by the authors for many years. These works included as follows: heat transfer during the flow boiling, boiling crises and condensation in flow. The issue of the heat transfer intensification during the flow boiling through the channels of small diameters was analyzed. All this work focused...
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A Proposed Soft Computing Model for Ultimate Strength Estimation of FRP-Confined Concrete Cylinders
PublicationIn this paper, the feed-forward backpropagation neural network (FFBPNN) is used to propose a new formulation for predicting the compressive strength of fiber-reinforced polymer (FRP)-confined concrete cylinders. A set of experimental data has been considered in the analysis. The data include information about the dimensions of the concrete cylinders (diameter, length) and the total thickness of FRP layers, unconfined ultimate concrete...
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A Highly Sensitive Planar Microwave Sensor for Detecting Direction and Angle of Rotation
PublicationThis article presents a technique based on a modified complementary split-ring resonator (CSRR) to detect angular displacement and direction of rotation with high resolution and sensitivity over a wide dynamic range. The proposed microwave planar sensor takes advantage of the asymmetry of the sensor geometry and measures the angle of rotation in terms of the change in the relative phase of the reflection coefficients. The sensor...
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Discrete identification of continuous non-linear and non-stationary dynamical systems that is insensitive to noise correlation and measurement outliers
PublicationThe paper uses specific parameter estimation methods to identify the coefficients of continuous-time models represented by linear and non-linear ordinary differential equations. The necessary approximation of such systems in discrete time in the form of utility models is achieved by the use of properly tuned `integrating filters' of the FIR type. The resulting discrete-time descriptions retain the original continuous parameterization...
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Monte Carlo simulations of the fracture resistance degradation of asphalt concrete subjected to environmental factors
PublicationThe paper presents the results of laboratory tests of SCB (semi-circular beam) samples of asphalt concrete, subjected to the destructive effect of water and frost as well as the aging processes. The determined values of material parameters show significant dispersions, which makes the design of mixtures difficult. Statistical analysis of the test results supplemented by computer simulations made with the use of the proprietary...
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Effective Equations for the Optimum Seismic Gap Preventing Earthquake-Induced Pounding between Adjacent Buildings Founded on Different Soil Types
PublicationThe best approach to avoid collisions between adjacent structures during earthquakes is to provide sufficient spacing between them. However, the existing formulas for calculating the optimum seismic gap preventing pounding were found to provide inaccurate results upon the consideration of different soil types. The aim of this paper is to propose new equations for the evaluation of the sufficient in-between separation gap for buildings...
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Assessing the attractiveness of human face based on machine learning
PublicationThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
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A New Approach of Solidification Analysis in Modular Latent Thermal Energy Storage Unit Based on Image Processing
PublicationThe solidification process of RT18HC in a cylindrical shell and tube storage unit has been studied using a new methodology based on image processing. The main idea of the algorithm is to label the region of solidification and use statistical functions to calculate the dimensions of the solidification front over time. Said analysis includes two methods. The first method is to measure the solid fraction changes during solidification....
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Application of Feed Forward Neural Networks for Modeling of Heat Transfer Coefficient During Flow Condensation for Low and High Values of Saturation Temperatur
PublicationMost of the literature models for condensation heat transfer prediction are based on specific experimental parameters and are not general in nature for applications to fluids and non-experimental thermodynamic conditions. Nearly all correlations are created to predict data in normal HVAC conditions below 40°C. High temperature heat pumps operate at much higher parameters. This paper aims to create a general model for the calculation...
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CZYNNIKI DECYDUJĄCE O PRZYDATNOŚCI KOMPUTEROWEGO MODELU PRZEPŁYWÓW W SIECI WODOCIĄGOWEJ
PublicationW pracy poddano analizie wielozadaniowy proces tworzenia komputerowego modelu przepływów. W efekcie zidentyfikowano szereg czynników ograniczających obszar stosowania modelu w praktyce inżynierskiej. W zakresie pozyskiwania danych strukturalnych i operacyjnych wskazano potencjalne źródła błędów, które przyczyniają się do zmniejszenia dokładności odwzorowania stanu rzeczywistego. Specjalną rangę nadano specyfikacji czynników związanych...
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Long-term hindcast simulation of water temperature and salinity in the Baltic Sea
Open Research DataThe dataset contains the results of numerical modelling of water temperature and salinity over a period of 50 years (1958-2007) in the Baltic Sea. A long-term hindcast simulation was performed using a three-dimensional hydrodynamic model PM3D (Kowalewski and Kowalewska-Kalkowska, 2017), a new version of the M3D model (Kowalewski, 1997). The hydrodynamic...
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Risk assessment for tram traffic on tramway bridges
PublicationMiejski transport szynowy wielu miastach stanowi istotny element systemu transportowego i jest przestrzennie rozwijającym się systemem zapewniającym mieszkańcom codzienną obsługę transportową. Bezpieczeństwo pasażerów transportu szynowego i użytkowników dróg jest jednym z najważniejszych czynników, który należy uwzględnić w trakcie projektowania infrastruktury oraz w ocenie operacyjnej systemu miejskiego transportu tramwajowego....
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Determination of Odor Air Quality Index (OAQII) Using Gas Sensor Matrix
PublicationThis article presents a new way to determine odor nuisance based on the proposed odor air quality index (OAQII), using an instrumental method. This indicator relates the most important odor features, such as intensity, hedonic tone and odor concentration. The research was conducted at the compost screening yard of the municipal treatment plant in Central Poland, on which a self-constructed gas sensor array was placed. It consisted...
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublicationNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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The Application of Satellite Image Analysis in Oil Spill Detection
PublicationIn recent years, there has been an increasing use of satellite sensors to detect and track oil spills. The satellite bands, namely visible, short, medium infrared, and microwave radar bands, are used for this purpose. The use of satellite images is extremely valuable for oil spill analysis. With satellite images, we can identify the source of leakage and assess the extent of potential damage. However, it is not yet clear how to...
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Low-Cost and Highly-Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
PublicationThe awareness and practical benefits of behavioral modeling methods have been steadily growing in the antenna engineering community over the last decade or so. Undoubtedly, the most important advantage thereof is a possibility of a dramatic reduction of computational expenses associated with computer-aided design procedures, especially those relying on full-wave electromagnetic (EM) simulations. In particular, the employment of...
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Performance and Emission Modelling and Simulation of Marine Diesel Engines using Publicly Available Engine Data
PublicationTo analyse the behaviour of marine diesel engines in unsteady states for different purposes, for example to determine the fuel consumption or emissions level, to adjust the control strategy, to manage the maintenance, etc., a goal-based mathematical model that can be easily implemented for simulation is necessary. Such a model usually requires a wide range of operating data, measured on a test stand. This is a time-consuming process...
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Problemy zarządzania bezpieczeństwem obiektu przemysłowego podwyższonego ryzyka
PublicationW rozdziale przedstawiono wybrane zagadnienia dotyczące zarządzania bezpieczeństwem w zautomatyzowanym złożonym obiekcie podwyższonego ryzyka. Pokazano, że ryzyko strat można istotnie ograniczyć stosując odpowiednie rozwiązania techniczne w postaci warstwowego systemu zabezpieczeń, który obejmuje podstawowy system sterowania procesem, człowieka-operatora i system automatyki zabezpieczeniowej. Podkreślono znaczenie właściwego zaprojektowania...
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Derivation of motor mean phase currents in PMSM drives operating with low switching-to-fundamental frequency ratio
PublicationPulse width modulation (PWM) of inverter output voltage causes the waveforms of motor phase cur-rents to consist of distinctive ripples. In order to provide suitable feedback for the motor current con-trollers, the mean value must be extracted from the currents’ waveforms in every PWM cycle. A com-mon solution to derive the mean phase currents is to sample their value at the midpoint of a symmetrical PWM cycle. Using an assumption...
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Entanglement of genuinely entangled subspaces and states: Exact, approximate, and numerical results
PublicationGenuinely entangled subspaces (GESs) are those subspaces of multipartite Hilbert spaces that consist only of genuinely multiparty entangled pure states. They are natural generalizations of the well-known notion of completely entangled subspaces, which by definition are void of fully product vectors. Entangled subspaces are an important tool of quantum information theory as they directly lead to constructions of entangled states,...
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Impact of digital signal processing on FOC current feedback in high-speed PMSM drive
PublicationIn applications where size and weight of the electric motor are among major design concerns, Permanent Magnet Synchronous Motors (PMSMs) with wide operational speed-range are commonly preferred. Due to limited inverter switching frequency, high-speed operation of a drive results in a low ratio between the switching frequency and the fundamental frequency of motor voltage. Such operating conditions have been recently identified...
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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublicationThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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Finding deformation of the straight rail track by GNSS measurements
PublicationW 2009 roku na Politechnice Gdańskiej i Akademii Marynarki Wojennej w Gdyni zostały przeprowadzone, po raz pierwszy, ciągłe pomiary satelitarne toru kolejowego z wykorzystaniem względnej metody fazowej na bazie polskiej Aktywnej Sieci Geodezyjnej ASG-EUPOS i serwisu czasu rzeczywistego RTK (GPRS) - NAVGEO. Przeprowadzona analiza wykazała silny związek między lokalizacją odbiornika GNSS i dokładnością wyznaczania pozycji, wpływ...
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Real-time simulation in non real-time environment
PublicationSimulation in real-time is a very useful tool because of didactical and practical benefits. Very important benefit of real-time simulation is a fact that operator’s decision can be taken into account in the same time scale as the real system would work. This enables construction of simulators, and opportunity to test control algorithms in Hardware in The Loop scheme using target industrial equipment. Professional real-time environments...
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A Compact Basis for Reliable Fast Frequency Sweep via the Reduced-Basis Method
PublicationA reliable reduced-order model (ROM) for fast frequency sweep in time-harmonic Maxwell’s equations by means of the reduced-basis method is detailed. Taking frequency as a parameter, the electromagnetic field in microwave circuits does not arbitrarily vary as frequency changes, but evolves on a very low-dimensional manifold. Approximating this low-dimensional manifold by a low dimension subspace, namely, reduced-basis space, gives...
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Computationally efficient two-objective optimization of compact microwave couplers through corrected domain patching
PublicationFinding an acceptable compromise between various objectives is a necessity in the design of contemporary microwave components and circuits. A primary reason is that most objectives are at least partially conflicting. For compact microwave structures, the design trade-offs are normally related to the circuit size and its electrical performance. In order to obtain comprehensive information about the best possible trade-offs, multi-objective...
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Determinants of trade balance in Polish and Czech manufacturing sectors
PublicationResearch background: A strong industrial base is essential for achieving long-term sustainable economic growth and export competitiveness. In that sense, manufacturing remains a significant contributor to exports in the CEE countries. However, its role and its influence vary between CEE economies and change over time. Purpose of the article: The main objective of this paper is to compare the determinants of the international competitiveness,...
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Multi-region fuzzy logic controller with local PID controllers for U-tube steam generator in nuclear power plant
PublicationIn the paper, analysis of multi-region fuzzy logic controller with local PID controllers for steam generator of pressurized water reactor (PWR) working in wide range of thermal power changes is presented. The U-tube steam generator has a nonlinear dynamics depending on thermal power transferred from coolant of the primary loop of the PWR plant. Control of water level in the steam generator conducted by a traditional PID controller...
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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublicationIn this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model has been used. The task is to predict simultaneously and independent of each characteristic parameters of a buried object of several radii at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable...
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublicationSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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A Simple Neural Network for Collision Detection of Collaborative Robots
PublicationDue to the epidemic threat, more and more companies decide to automate their production lines. Given the lack of adequate security or space, in most cases, such companies cannot use classic production robots. The solution to this problem is the use of collaborative robots (cobots). However, the required equipment (force sensors) or alternative methods of detecting a threat to humans are usually quite expensive. The article presents...
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Optimization-Based High-Frequency Circuit Miniaturization through Implicit and Explicit Constraint Handling: Recent Advances
PublicationMiniaturization trends in high-frequency electronics have led to accommodation challenges in the integration of the corresponding components. Size reduction thereof has become a practical necessity. At the same time, the increasing performance demands imposed on electronic systems remain in conflict with component miniaturization. On the practical side, the challenges related to handling design constraints are aggravated by the...
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Application of a Gas Sensor Array to Effectiveness Monitoring of Air Contaminated with Toluene Vapors Absorption Process
PublicationThis article demonstrates the application of a gas sensor array to monitor the effectiveness of the absorption process of air stream purification from odorous compounds (toluene vapors). A self-constructed matrix consisting of five commercially available gas sensors was used. Multiple linear regression (MLR) was selected as the statistical technique used to calibrate the matrice. Gas chromatography coupled with a flame ionization...
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A Comparative Study of Fuzzy SMC with Adaptive Fuzzy PID for Sensorless Speed Control of Six-Phase Induction Motor
PublicationMulti-phase motors have recently replaced three-phase induction motors in a variety of applications due to the numerous benefits they provide, and the absence of speed sensors promotes induction motors with variable speed drives. Sensorless speed control minimizes unnecessary speed encoder cost, reduces maintenance, and improves the motor drive’s reliability. The performance comparison of the fuzzy sliding mode controller (FSMC)...
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Multiple Cues-Based Robust Visual Object Tracking Method
PublicationVisual object tracking is still considered a challenging task in computer vision research society. The object of interest undergoes significant appearance changes because of illumination variation, deformation, motion blur, background clutter, and occlusion. Kernelized correlation filter- (KCF) based tracking schemes have shown good performance in recent years. The accuracy and robustness of these trackers can be further enhanced...
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A Comparative Study of Fuzzy SMC with Adaptive Fuzzy PID for Sensorless Speed Control of Six-Phase Induction Motor
PublicationMulti-phase motors have recently replaced three-phase induction motors in a variety of applications due to the numerous benefits they provide, and the absence of speed sensors promotes induction motors with variable speed drives. Sensorless speed control minimizes unnecessary speed encoder cost, reduces maintenance, and improves the motor drive’s reliability. The performance comparison of the fuzzy sliding mode controller (FSMC)...
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System for automatic singing voice recognition
PublicationW artykule przedstawiono system automatycznego rozpoznawania jakości i typu głosu śpiewaczego. Przedstawiono bazę danych oraz zaimplementowane parametry. Algorytmem decyzyjnym jest algorytm sztucznych sieci neuronowych. Wytrenowany system decyzyjny osiąga skuteczność ok. 90% w obydwu kategoriach rozpoznawania. Dodatkowo wykazano przy pomocy metod statystycznych, że wyniki działania systemu automatycznej oceny jakości technicznej...
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FFT analysis of temperature modulated semiconductor gas sensor response for the prediction of ammonia concentration under humidity interference
PublicationThe increasing environmental contamination forces the need to design reliable devices for detecting of the volatile compounds present in the air. For this purpose semiconductor gas sensors, which have been widely used for years, are often utilized. Although they have many advantages such as low price and quite long life time, they still lack of long term stability and selectivity. Namely, environmental conditions have significant...
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In silico modelling for predicting the cationic hydrophobicity and cytotoxicity of ionic liquids towards the Leukemia rat cell line, Vibrio fischeri and Scenedesmus vacuolatus based on molecular interaction potentials of ions
PublicationIn this study we present prediction models for estimating in silico the cationic hydrophobicity and the cytotoxicity (log [1/EC50]) of ionic liquids (ILs) towards the Leukemia rat cell line (IPC-81), the marine bacterium Vibrio fischeri and the limnic green algae Scenedesmus vacuolatus using linear free energy relationship (LFER) descriptors computed by COSMO calculations. The LFER descriptors used for the prediction model (i.e....
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Estimation of the Regenerative Braking Process Efficiency in Electric Vehicles
PublicationIn electric and hybrid vehicles, it is possible to recover energy from the braking process and reuse it to drive the vehicle using the batteries installed on-board. In the conditions of city traffic, the energy dissipated in the braking process constitutes a very large share of the total resistance to vehicle motion. Efficient use of the energy from the braking process enables a significant reduction of fuel and electricity consumption...
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User Authentication by Eye Movement Features Employing SVM and XGBoost Classifiers
PublicationDevices capable of tracking the user’s gaze have become significantly more affordable over the past few years, thus broadening their application, including in-home and office computers and various customer service equipment. Although such devices have comparatively low operating frequencies and limited resolution, they are sufficient to supplement or replace classic input interfaces, such as the keyboard and mouse. The biometric...
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Analiza właściwości rozszerzonego obserwatora prędkości maszyny indukcyjnej
PublicationRozszerzony obserwator prędkości został zaproponowany przez prof. Krzemińskiego i jest oparty na rozszerzonym modelu maszyny indukcyjnej, gdzie wprowadzona został nowa zmienna ζ. Jest to nowe podejście do estymacji zmiennych stanu maszyny indukcyjnej i nie wszystkie problemy zostały do tej pory rozwiązane. Zaproponowano wykorzystanie algorytmów ewolucyjnych do doboru wzmocnień obserwatora. W celu redukcji nakładów obliczeniowych...
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G2DC-PL+: a gridded 2 km daily climate dataset for the union of the Polish territory and the Vistula and Odra basins
PublicationG2DC-PL+, a gridded 2 km daily climate dataset for the union of the Polish territory and the Vistula and Odra basins, is an update and extension of the CHASE-PL Forcing Data – Gridded Daily Precipitation and Temperature Dataset – 5 km (CPLFD-GDPT5). The latter was the first publicly available, high-resolution climate forcing dataset in Poland, used for a range of purposes including hydrological modelling and bias correction of...
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Iterative Global Sensitivity Analysis Algorithm with Neural Network Surrogate Modeling
PublicationGlobal sensitivity analysis (GSA) is a method to quantify the effect of the input parameters on outputs of physics-based systems. Performing GSA can be challenging due to the combined effect of the high computational cost of each individual physics-based model, a large number of input parameters, and the need to perform repetitive model evaluations. To reduce this cost, neural networks (NNs) are used to replace the expensive physics-based...