Volume 69 (2018): Issue 2 (March 2018)

This paper describes an image encryption algorithm which utilizes chaotic logistic map. Values generated by this map are used in two steps of algorithm which shuffles image pixels and then changes their intensities. Design of the encryption scheme considers possibility of various attacks, such as statistical, differential or phase space reconstruction attacks. Robustness against last mentioned type of attacks is introduced by selective skipping of values generated by the map. This skipping depends on key entered by user. The paper also verifies properties of proposed algorithm by common measures and by set of statistical tests that examine randomness of computed encrypted images. Results are compared with other approaches and they are also briefly discussed.

Total internal reflection of plane waves is a well-known phenomenon. Some new aspects of the numerical treatment of the total internal reflection phenomena, concerning the beam-wave, are discussed.

The paper presents a new original robust PID design method for non-minimum phase plants to achieve closed-loop performance prescribed by the process technologist in terms of settling time and maximum overshoot, respectively. The proposed design procedure has two steps: first, the uncertain system is identified using external harmonic excitation signal with frequency, second, the controller of the nominal system is designed for specified gain margin. A couple of parameters is obtained from the time domain performance specification using quadratic regression curves, the so-called performance Bparabolas so, as to simultaneously satisfy robust closed-loop stability conditions. The main benefits of the proposed method are universal applicability for systems with both fast and slow dominant dynamics as well as performance specification using time domain criteria. The proposed PID design method has been verified on a set of benchmark systems.

Configuration of distribution system can be changed manually or automatically, by changing the status of the respective switching elements, with the aim of reducing power losses, increase system reliability, or improving the power quality. When changing the status of switching equipment it is necessary to satisfy the requirement for the radial and connected structure of the distribution network. Using the single criteria optimization it is possible to improve one of the characteristics of the distribution network, on the other hand by using multicriteria optimization it is possible to find a network configuration that enhances multiple distribution system characteristics at the same time. In this paper, a modification of the multi-criteria Gray Wolf optimization algorithm is proposed in order to create an efficient algorithm that can be implemented in the management functions of smart grid concept of modern distribution systems. The proposed reconfiguration algorithm was tested on standard symmetrical IEEE 33 test distribution network.

Two basic tasks are covered in this paper. The first one consists in the design and practical testing of a new method for voice de-identification that changes the apparent age and/or gender of a speaker by multi-segmental frequency scale transformation combined with prosody modification. The second task is aimed at verification of applicability of a classifier based on Gaussian mixture models (GMM) to detect the original Czech and Slovak speakers after applied voice deidentification. The performed experiments confirm functionality of the developed gender and age conversion for all selected types of de-identification which can be objectively evaluated by the GMM-based open-set classifier. The original speaker detection accuracy was compared also for sentences uttered by German and English speakers showing language independence of the proposed method.

Thanks to non-pollution and sustainability of wind energy, it has become the main source of power generation in the new era worldwide. However, the inherent random fluctuation and intermittency of wind power have negative effects on the safe and stable operation of power system and the quality of power. The key solving this problem is to improve the accuracy of wind speed prediction. In the paper, considering the forecasting accuracy is affected by many factors, we propose that, Principal Component Analysis (PCA) is combined with Independent Component Analysis (ICA) to process the sample, which can weaken the mutual interference between the various factors, extract accurately independent component reflected the characteristics of wind farm and achieve the purpose of improving the accuracy of wind speed prediction. At the same time, the adaptive and self-learning ability of neural network is more suitable for wind speed sequence prediction. The prediction results demonstrate that compared with the traditional neural network predicting model (RBF, BP, Elman), this model makes full use of the information provided by varieties of relevant factors, weakens the volatility of wind speed sequence and significantly enhances the short-term wind speed forecasting accuracy. The research work in the paper can help wind farm reasonably arrange the power dispatching plan, reduce the power operation cost and effectively boost the large-scale development and utilization of renewable energy.

The paper presents idea and practical implementation of a medium voltage synchronous drive with a voltage source inverter in the stator circuit and a microprocessor controlled unit for excitation supply. Construction of both devices was presented, and methods of their cooperation were described. Selected start-up methods of large power synchronous motors were presented. Exemplary realization was discussed. Measurement results of the direct full-voltage start-up and frequency start-up of a real 1.25 MW 6 kV fan drive system were compared and discussed.

This paper discusses the influence of the Particle Size Distribution (PSD) of the nanocrystalline Fe-based granular-soft-magnetic material on the final magnetic properties of a Magnetic Powder Core (MPC). Here we show how PSD impacts the final magnetic properties. Mixing fine and coarse particles, with a dominance of coarse particles, significantly influences the magnetic permeability increase of the core. Better magnetic features are noted for MPCs constructed with certain mass ratio of fine and coarse particles due to improvement in the magnetic path in the cores. This allows to offer new induction components to industry.

A surrogate technique based on Gaussian Process (GP) is used for predicting quality of laser in case of laser welding process that may be supported by induction preheating. FEM-based solution of the problem is computationally expensive because it combines computation of 3D coupled nonlinear electromagnetic and temperature fields. The quality of laser welds is quantified with weld depth, which depends on a number of input parameters. The paper deals with two of them —thickness of the welded steel sheet and power of the laser beam. First, selected FEM simulations allow finding data describing the dependency between the two input parameters and weld depth. These data allow creating a surrogate model that is able to predict weld depth at any point close to the points where the results are known. The principal goal is to essentially save the computational time. The surrogate model also allows estimating prediction plausibility and running the full FEM calculation in cases where the prediction is not sufficiently accurate. The methodology is illustrated with a typical example whose results are discussed.

The fabrication procedure and characterization of low-cost electrodes for capacitive level sensors realized on a flexible substrate are presented in this paper. The aim was to prepare conductive electrodes by printing of silver and PEDOT:PSS pastes on coated PET foil. Individual interdigital capacitors and a system with embedded microcontroller readout were designed for a comparative study. Individual capacitors in the form of interdigital electrodes (IDT) were designed with different finger width/spacing dimensions from 300/300 μm to 800/800 μm, a finger length 10 mm and 15 mm and an overall length of 100 mm. A demonstrator device featuring an integrated microcontroller, sensing and reference capacitive sensors and a resistive temperature sensor was realized to proof a practical utilization. The microcontroller is used to calculate capacitances of IDT electrodes in terms of charging time proportional to the fluid level. The design with reference capacitor can be directly applied to different fluids with a wide range of conductivities and dielectric constants without recalibration. The printed structures were thermally laminated with covering PET foil. The sensitivity of the fabricated devices was characterized in liquids with different relative permittivity and conductivity (water and oil). The highest measured sensitivity was 0.7 pF/mm and 0.08 pF/mm for water and oil respectively, with resolution down to 0.1 mm.

In this work, a quaternion-valued model is proposed in lieu of the Clarke’s α, β transformation to convert three-phase quantities to a hypercomplex single-phase signal. The concatenated signal can be used for harmonic distortion detection in three-phase power systems. In particular, the proposed model maps all the harmonic frequencies into frequencies in the quaternion domain, while the Clarke’s transformation-based methods will fail to detect the zero sequence voltages. Based on the quaternion-valued model, the Fourier transform, the minimum variance distortionless response (MVDR) algorithm and the multiple signal classification (MUSIC) algorithm are presented as examples to detect harmonic distortion. Simulations are provided to demonstrate the potentials of this new modeling method.

This paper presents a non-traditional way of determining an unknown constant encountered in the expression for magnetic vector potential due to an elemental dipole antenna.