Bilal Asad, Toomas Vaimann, Ants Kallaste, Anton Rassõlkin, Anouar Belahcen and M. Naveed Iqbal
In this paper, the harmonic contribution of the broken rotor bar of an induction machine is investigated using an effective combination of the fast Fourier transform (FFT) and a band stop filter. The winding, spatial, grid fed and fault-based harmonics are investigated. Since the fundamental component is the most powerful component as compared to the other frequencies, it decreases the legibility of spectrum, making logarithmic scale inevitable. It also remains a potential threat of burying the fault representative side band frequencies because of its spectral leakage. In this paper, a band stop Chebyshev filter is used to attenuate the fundamental component, which makes the spectrum clearer and easier to understand even on the linear scale. Its good transition band and low passband ripples make it suitable for attenuating the main supply frequency with low impact on the neighbouring side band frequencies. To study the impact of fault on magnetic flux distribution, simulation is done using finite element method with good number of mesh elements and very small step size. The line current is calculated and frequency spectrum is investigated to segregate the spatial and fault frequencies using the proposed technique. The results are further validated by implementing the algorithm on the data measured in the laboratory environment including the grid fed harmonics.
Longwave radiation, as part of the radiation balance, is one of the factors needed to estimate potential evapotranspiration (PET). Since the longwave radiation balance is rarely measured, many computational methods have been designed. In this study, we report on the difference between the observed longwave radiation balance and modelling results obtained using the two main procedures outlined in FAO24 (relying on the measured sunshine duration) and FAO56 (based on the measured solar radiation) manuals. The performance of these equations was evaluated in the April–October period over eight years at the Liz experimental catchment and grass surface in the Bohemian Forest (Czech Republic). The coefficients of both methods, which describe the influence of cloudiness factor and atmospheric emissivity of the air, were calibrated. The Penman-Monteith method was used to calculate the PET. The use of default coefficient values gave errors of 40–100 mm (FAO56) and 0–20 mm (FAO24) for the seasonal PET estimates (the PET was usually overestimated). Parameter calibration decreased the FAO56 error to less than 20 mm per season (FAO24 remained unaffected by the calibration). The FAO56 approach with calibrated coefficients proved to be more suitable for estimation of the longwave radiation balance.
Coir fibre is a non-conventional fibre extracted from the husk of coconut fruit and is abundantly available in tropical countries. Coir yarn is produced in the decentralised cottage industry. Increase in the demand for the coir fibre yarns for value-added applications has forced the coir yarn manufacturers to improve the existing coir spinning machine in different ways. In this study, the working principle of the existing coir spinning machine has been studied from the perspective of further improvements in production rate, yarn quality and spinning performance. Modifications have been made in the existing coir spinning machine in fibre feeding, opening and cleaning. There is improvement in the production rate of up to 20% with significant improvements in the yarn quality and spinning performance.
The shift towards distributed generation and microgrids has renewed the interest in forecasting algorithms and methods, which need to take into account the advances in information, metering and control technologies in order to address the challenges of forecasting problems. Technologies such as machine learning have been proven useful for short-term electricity load forecasting, especially for microgrids, as they can also take into account several types of historical data and can adapt to changes often encountered in small-scale systems and on a short time scale. In this paper, we present a flexible and easily customized modular toolbox, called Divinus, for electricity use profiling and forecasting in microgrids. Divinus may support a variety of machine learning algorithms for forecasting and profiling that can be used independently or combined. For demonstration purposes, we have implemented Self-Organizing Maps for profiling and k-Neighbors for forecasting. The testing of the platform was based on electricity consumption data of the Euripus campus of the National and Kapodistrian University of Athens in Evia, Greece, from January 2010 till March 2018. The tests that have been carried out so far show that the platform can be easily customized and the algorithms examined yield high accuracy and acceptable mean errors for the case of a university campus energy profile.
A 2D hydrodynamic (labeled as CAR) model has been proposed in a rectangular Cartesian coordinate system with two axes within the horizontal plane and one axis along the vertical direction (global coordinates), considering the effects of bed slope on both pressure distribution and bed shear stresses. The CAR model satisfactorily reproduces the analytical solutions of dam-break flow over a steep slope, while the traditional Saint-Venant Equations (labeled as SVE) significantly overestimate the flow velocity. For flood events with long duration and large mean slope, the CAR and the SVE models present distinguishable discrepancies. Therefore, the proposed CAR model is recommended for applications to real floods for its facility of extending from 1D to 2D version and ability to model shallow-water flows on steep slopes.
The detection of defects in yarn-dyed fabric is one of the most difficult problems among the present fabric defect detection methods. The difficulty lies in how to properly separate patterns, textures, and defects in the yarn-dyed fabric. In this paper, a novel automatic detection algorithm is presented based on frequency domain filtering and similarity measurement. First, the separation of the pattern and yarn texture structure of the fabric is achieved by frequency domain filtering technology. Subsequently, segmentation of the periodic units of the pattern is achieved by using distance matching function to measure the fabric pattern. Finally, based on the similarity measurement technology, the pattern’s periodic unit is classified, and thus, automatic detection of the defects in the yarn-dyed fabric is accomplished.
Peter Hlinka, Ingrid Karandušovská and Štefan Mihina
The aim of this paper was to monitor the production and composition of gases from the biowaste landfill in terms of the utilized composting process technology. Processing technology of biowaste in the reference sample V1 was without modification; process optimization technology – material homogenization by overturning and irrigation – was used for the second sample V2. Gas measurements (methane, carbon dioxide, ammonia, nitrous oxide) were conducted during the first and sixth weeks after their establishing. At the same time, samples were taken for laboratory determination of the dry matter content of examined materials, pH and C/N ratio. It has been statistically proved that there was a significantly higher gas production in V2, which was overturned and irrigated, than in V1. The measured CO2 values were 2.5 times higher in V2 in comparison to V1. The mean CH4 production in the stack V1 was 96.35 mg·m−3 and 235.9 mg·m−3 in the stack V2, which is 2.5 times more. Due to overturning and irrigation of composted material in the stack V2, the decomposition of microorganisms was faster, which also affected the amount of released gases.
Klara Kostajnšek, Raša Urbas and Krste Dimitrovski
Knowing the reflection, transmission, and absorption properties of the yarns from which the woven fabric is made, prediction of a fabric’s UV-protective properties is simple. Using the geometrical properties of monofilament yarns and fabrics, which were determined optically, and following the cover factor theory, we have determined the areas of fabrics covered with no yarns, only one yarn, and two yarns. From a special selected set of high-module polyethylene terephthalate (PET) monofilament materials (e.g., fabrics), we have elaborated a method for determining the reflection, transmission, and absorption of yarns. By first defining the differently covered areas of fabrics, we were able to use them in a mathematical model for calculating and predicting the UV-protective properties of the fabrics. The calculated and measured values of the UV-protective properties of the selected test fabrics were highly correlated, with a correlation coefficient >0.98.
This research addresses some personalization aspects of education in electrical engineering. Its goal is to help students and educators evaluate the complexity of the disciplines they have chosen for studying and optimize the order of the learned courses and topics. A new instrument, namely, an educational thesaurus, is presented and its assembling procedure is shown. The offered educational thesauri implemented in the labs and integrated in the exercises have become smart platforms suitable for design and management of the students’ individual knowledge domains. The ontology-based Web manuals in Electronics and Power Electronics for the Bachelor study cycle have been introduced. An example of ontology graph to be applied within the Master study cycle has been developed and explained in the paper. According to the authors’ investigation, the decrease of stress caused by the new educational environment and achievement of success in learning were observed thanks to the individual knowledge domain organization proposed in this study.
Łukasz Frącczak, Domagała Rafał, Zgórniak Piotr and Małgorzata Matusiak
Seersucker woven fabrics are increasingly used in the textile industry. Unfortunately, their popularity is limited due to the lack of standards and parameterization of their structure. Thus, the designer of the finished product (clothing, bedding, or decorative items) has problems with ordering a fabric with a specific structure and properties. In this context, it is necessary to parameterize them. This paper presents a method for measuring the surface geometry of seersucker woven fabrics using laser techniques. The surface geometry of the seersucker woven fabric was determined using adapted roughness parameters, such as Wz, Ra, and Rz, as well as by using a hypsometric map.