This article is focused on considerations based on experimental studies concerning changes of selected parameters of identical compact fluorescent lamps (CFLs) intended for use in buildings during their operation. The studies constituted a long-term experiment whose goal was an evaluation of selected operating parameters of the CFLs in terms of meeting the requirements set out in the specified regulations as well as the issue of marking the lamps with the energy efficiency class. The measurements were performed with the authors’ experimental setup consisting of original equipment designed and made especially for the purpose of the measurements. The studies covered registration of the luminous flux as well as selected electrical parameters such as active power, current and the power factor during the so-called “start-up time” and operation time equal to 100 h, 500 h, 1000 h, 2000 h, etc. with a 1000 h step. The studies were finished with the moment of natural burnout of the CFLs tested. The results showed that the biggest drawback of CFLs is lack of preservation of the required time to reach 60% of the stabilized luminous flux just after short time of lamp operation. Similarly when assessing the conformity of the parameters declared by the manufacturer that have been verified, it can be stated that they are true only at the initial stage of lamp operation.

The article presents an application of Prony’s method with some known components in the analysis of electric power quality. Modifications of the Prony algorithm broaden the scope of method application. Modification of the filter of known components enables more accurate analysis of the parameters of unknown components and components with known or assumed frequencies. This article presents a comparison of the results of analyses conducted with the proposed algorithm for simulated and real signals and the results obtained by means of a commercial electric power quality testing device, operating in class A and using the Fourier transform. The proposed method enables to estimate the levels of the harmonic components, the frequency of the fundamental signal and real parameters of the interharmonic components, which are grouped and averaged in the contemporary monitoring equipment. Knowledge of the individual parameters of the interharmonics has considerable diagnostic importance while removing causes of incorrect operation affecting sensitive equipment in some electric power systems. Additionally, the algorithm is capable of analyzing exponentially damped components and finds its application in analysis of disturbances, for example, transient oscillations.

This paper presents an example of practical use of Prony's method for monitoring of power waveform fundamental harmonic fluctuations, which is required for the analysis of window synchronizations in frequency analyses in power monitoring systems. The example presented offers verification of the authors' theoretical considerations published earlier in articles about Prony's method and its opportunities for practical use for real life signals. The investigations shown are based on the least squares Prony's method, which, in connection with digital filtrations, enables estimations of fundamental frequency at the rate of even tens of times per one fundamental harmonic period.

The article presents a new modification of the the least squares Prony method. The so-called variable-frequency Prony method can be a useful tool for estimating parameters of sinusoidal components, which, in the analyzed signal, are characterized by time-dependent frequencies. The authors propose use of the presented method for testing the quality of electric energy. It allows observation of phenomena which, when using traditional methods, are averaged in the analysis window. The proposed modification of least squares Prony method is based on introduction and specific selection of a frequency matrix. This matrix represents frequencies of estimated components and their variability in time.

This article presents a way of analyzing the transfer function of electronic signal amplifiers. It also describes the possibility of using signal precorrection which improves the parasitic harmonics in the THD (Total Harmonic Distortion) of the amplified signal by correcting linearity of the tested amplifier’s transfer function. The proposed method of analyzing and presenting the transfer function allows to diagnose the causes of generating parasitic harmonics, what makes it a useful tool when designing low distortion amplifier systems, such as e.g. amplifiers in measurement systems. The presented THD correction can be used in e.g. amplifier systems that cooperate with arbitrary generators.

This paper presents a new modification of the least-squares Prony’s method with reduced sampling, which allows for a significant reduction in the number of the analysed signal samples collected per unit time. The specific combination of non-uniform sampling with Prony’s method enables sampling of the analysed signals at virtually any average frequency, regardless of the Nyquist frequency, maintaining high accuracy in parameter estimation of sinusoidal signal components. This property allows using the method in measuring devices, such as for electric power quality testing equipped with low power signal processors, which in turn contributes to reducing complexity of these devices. This paper presents research on a method for selecting a sampling frequency and an analysis window length for the presented method, which provide maximum estimation accuracy for Prony’s model component parameters. This paper presents simulation tests performed in terms of the proposed method application for analysis of harmonics and interharmonics in electric power signals. Furthermore, the paper provides sensitivity analysis of the method, in terms of common interferences occurring in the actual measurement systems.

Photovoltaic panels have a non-linear current-voltage characteristics to produce the maximum power at only one point called the maximum power point. In the case of the uniform illumination a single solar panel shows only one maximum power, which is also the global maximum power point. In the case an irregularly illuminated photovoltaic panel many local maxima on the power-voltage curve can be observed and only one of them is the global maximum. The proposed algorithm detects whether a solar panel is in the uniform insolation conditions. Then an appropriate strategy of tracking the maximum power point is taken using a decision algorithm. The proposed method is simulated in the environment created by the authors, which allows to stimulate photovoltaic panels in real conditions of lighting, temperature and shading.

In the diagnosis of many disease entities directly or indirectly related to disorders of respiratory parameters and heart disease, an important support would be to estimate the temporal changes in these parameters (most often respiratory wave (RW) and respiratory rate (RR)) on the basis the results of measurements of other physiological parameters of the patient. Such a possibility exists during ECG examination. The paper presents three methods for estimating RWand RR using ECG signal processing. The three procedures developed are shown: using Savitzky–Golay filtering (S-G), the ECG-Derived Respiration method (EDR) and the Respiratory Sinus Arrhythmia Analysis method (RSA). It must be clearly stated that the proposed methods are not designed to fully diagnose the patient’s respiratory function, but they can be applied to detect some conditions that are difficult to diagnose when performing an ECG, such as sleep-disordered breathing. The obtained results of the analysis were compared with those obtained from a dedicated measurement system developed by the authors. The second part of the paper will show the results of preliminary clinical verification of the developed analysis methods, taking into account the physiological parameters of the patient.

The article presents a water-cooling system for photovoltaic (PV) modules using a two-axis tracking system that tracks the apparent position of the Sun on the celestial sphere. The cooling system consists of 150 adjustable spray nozzles that cool the bottom layer of PV modules. The refrigerant is water taken from a tank with a capacity of 7 m ³. A water recovery system reduces its consumption with efficiency of approximately 90%. The experimental setup consists of a full-size photovoltaic installation made of 10 modules with an output power of 3.5 kWp combined with a tracking system. The article presents an analysis of the cooling system efficiency in various meteorological conditions. Measurements of energy production were performed in the annual cycle using three different types of photovoltaic installations: stationary, two-axis tracking system and two-axis tracking system combined with the cooling system.

The one-dimension frequency analysis based on DFT (Discrete FT) is sufficient in many cases in detecting power disturbances and evaluating power quality (PQ). To illustrate in a more comprehensive manner the character of the signal, time-frequency analyses are performed. The most common known time-frequency representations (TFR) are spectrogram (SPEC) and Gabor Transform (GT). However, the method has a relatively low time-frequency resolution. The other TFR: Discreet Dyadic Wavelet Transform (DDWT), Smoothed Pseudo Wigner-Ville Distribution (SPWVD) and new Gabor-Wigner Transform (GWT) are described in the paper. The main features of the transforms, on the basis of testing signals, are presented.

The paper deals with frequency estimation methods of sine-wave signals for a few signal cycles and consists of two parts. The first part contains a short overview where analytical error formulae for a signal distorted by noise and harmonics are presented. These formulae are compared with other accurate equations presented previously by the authors which are even more accurate below one cycle in the measurement window. The second part contains a comparison of eight estimation methods (ESPRIT, TLS, Prony LS, a newly developed IpDFT method and four other 3-point IpDFT methods) in respect of calculation time and accuracy for an ideal sine-wave signal, signal distorted by AWGN noise and a signal distorted by harmonics. The number of signal cycles is limited from 0.1 to 3 or 5. The results enable to select the most accurate/ fastest estimation method in various measurement conditions. Parametric methods are more accurate but also much slower than IpDFT methods (up to 3000 times for the number of samples equal to 5000). The presented method is more accurate than other IpDFT methods and much faster than parametric methods, which makes it possible to use it as an alternative, especially in real-time applications.

Fast and accurate grid signal frequency estimation is a very important issue in the control of renewable energy systems. Important factors that influence the estimation accuracy include the A/D converter parameters in the inverter control system. This paper presents the influence of the number of A/D converter bits b, the phase shift of the grid signal relative to the time window, the width of the time window relative to the grid signal period (expressed as a cycle in range (CiR) parameter) and the number of N samples obtained in this window with the A/D converter on the developed estimation method results. An increase in the number b by 8 decreases the estimation error by approximately 256 times. The largest estimation error occurs when the signal module maximum is in the time window center (for small values of CiR) or when the signal value is zero in the time window center (for large values of CiR). In practical applications, the dominant component of the frequency estimation error is the error caused by the quantization noise, and its range is from approximately 8×10-10 to 6×10-4.

We introduce numerical methods and algorithms to estimate the main parameters of fractal-like particle aggregates from their optical structure factor (i.e. light scattering diagrams). The first algorithm is based on a direct and simple method, but its applicability is limited to aggregates with large size parameter and intermediate fractal dimension. The second algorithm requires to build calibration curves based on accurate particle agglomeration and particle light scattering models. It allows analyzing the optical structure factor of much smaller aggregates, regardless of their fractal dimension and the size of the single particles. Therefore, this algorithm as well as the introduction of a criterial curve to detect the different scattering regimes, are thought to be powerful tools to perform reliable and reproducible analysis.

Telemedicine is one of the most innovative and promising applications of technology in contemporary medicine. Telemedical systems, a sort of distributed measurement systems, are used for continuous or periodic monitoring of human vital signals in the environment of living. This approach has several advantages in comparison to traditional medical care: e.g. patients experience fewer hospitalizations, emergency room visits, lost time from work, the costs of treatment are reduced, and the quality of life is improved. Currently, chronic respiratory diseases comprise one of the most serious public health problems. Simultaneously patients suffering from these diseases are well suitable for home monitoring. This paper describes the design and technical realization of a telemedical system that has been developed as a platform suitable for monitoring patients with chronic pulmonary diseases and fitted to Polish conditions. The paper focuses on the system's architecture, included medical tests, adopted hardware and software, and preliminary internal evaluation. The performed tests demonstrated good overall performance of the system. At present further work goes on to put it into practice.