Flickermeter Comparison Test

The paper describes the test of flickerevaluation made by eleven different types of power qualityanalyzers. The standard IEC 61000-4-15Ed.2 (Functionaland design specification of flickermeter) issued on August2010 specifies performance testing. Existing flickermetersfrom different manufacturers may provide different resultswhen processing non-uniform voltage fluctuations. Theflickermeters response to voltage varying signals withenvelope shape typical for sawmill, heat pump, granulatorwas tested. Voltage fluctuation caused by operating of thiselectrical equipment was measured in the real low voltagedistribution network by means of the power qualityanalyzer Topas 1000. One-period records of voltagefluctuation were available for the analysis. These weresimulated on the programmable power voltage sourceHP6834B in the university lab

Use of Regression Analysis to Determine the Model of Lighting Control in Smart Home with Implementation of KNX Technology

To optimize the management of operational and technical functions in the smart home (SH) and for use of effective methods of energy management in SH, it is generally necessary to provide statistics and process relevant data from operational measurement devices. This chapter describes the use of modern methods for statistical data processing using regression analysis techniques. The aim of the analysis is to describe the dependence of single measured values using an appropriate mathematical model that can be efficiently implemented in the control system of SH. This model can be used for the functions of supervision and diagnostics of optimum comfort setting inside the indoor environment of SH. Real experimental measurements of objective parameters of the indoor environment were realized in the selected rooms of unique wooden building in the passive standard. The researched methods were experimentally verified by classifying the behavior of lighting in the SH-selected rooms under specified conditions. The achieved experimental results will be used for the operating and technical functions control in SH for reducing the building operating costs

Parallel Iteration Method for Frequency Estimation Using Trigonometric Decomposition

The parallel iteration method for frequency estimation based on trigonometric decomposition is presented. First, the multi-frequency signal can be expressed in a matrix form based on the trigonometric decomposition, which implies a possibility to solve the nonlinear mapping functions of frequency estimation by a parallel iteration procedure. Then, frequency estimation with the minimized square errors is achieved by using the gradient-descent method in the parallel iteration procedure, which can effectively restrain the interferences from harmonics and noise. Finally, the workflow is shown, and the efficiency of the proposed method was demonstrated through computer simulations and experiments

Nonlinear Adaptive Signal Processing Improves the Diagnostic Quality of Transabdominal Fetal Electrocardiography

The abdominal fetal electrocardiogram (fECG) conveys valuable information that can aid clinicians with the diagnosis and monitoring of a potentially at risk fetus during pregnancy and in childbirth. This chapter primarily focuses on noninvasive (external and indirect) transabdominal fECG monitoring. Even though it is the preferred monitoring method, unlike its classical invasive (internal and direct) counterpart (transvaginal monitoring), it may be contaminated by a variety of undesirable signals that deteriorate its quality and reduce its value in reliable detection of hypoxic conditions in the fetus. A stronger maternal electrocardiogram (the mECG signal) along with technical and biological artifacts constitutes the main interfering signal components that diminish the diagnostic quality of the transabdominal fECG recordings. Currently, transabdominal fECG monitoring relies solely on the determination of the fetus’ pulse or heart rate (FHR) by detecting RR intervals and does not take into account the morphology and duration of the fECG waves (P, QRS, T), intervals, and segments, which collectively convey very useful diagnostic information in adult cardiology. The main reason for the exclusion of these valuable pieces of information in the determination of the fetus’ status from clinical practice is the fact that there are no sufficiently reliable and well-proven techniques for accurate extraction of fECG signals and robust derivation of these informative features. To address this shortcoming in fetal cardiology, we focus on adaptive signal processing methods and pay particular attention to nonlinear approaches that carry great promise in improving the quality of transabdominal fECG monitoring and consequently impacting fetal cardiology in clinical practice. Our investigation and experimental results by using clinical-quality synthetic data generated by our novel fECG signal generator suggest that adaptive neuro-fuzzy inference systems could produce a significant advancement in fetal monitoring during pregnancy and childbirth. The possibility of using a single device to leverage two advanced methods of fetal monitoring, namely noninvasive cardiotocography (CTG) and ST segment analysis (STAN) simultaneously, to detect fetal hypoxic conditions is very promising

Machine Learning and Computer Vision Techniques in Bee Monitoring Applications

Machine learning and computer vision are dynamically growing fields, which have proven to be able to solve very complex tasks. They could also be used for the monitoring of the honeybee colonies and for the inspection of their health state, which could identify potentially dangerous states before the situation is critical, or to better plan periodic bee colony inspections and therefore save significant costs. In this paper, we present an overview of the state-of-the-art computer vision and machine learning applications used for bee monitoring. We also demonstrate the potential of those methods as an example of an automated bee counter algorithm. The paper is aimed at veterinary and apidology professionals and experts, who might not be familiar with machine learning to introduce to them its possibilities, therefore each family of applications is opened by a brief theoretical introduction and motivation related to its base method. We hope that this paper will inspire other scientists to use the machine learning techniques for other applications in bee monitoring

PRECISION CHECK OF ENERGY METERS UNDER NONSINUSOIDAL CONDITIONS

ABSTRAC

Evaluation of Power Quality in Off-Grid Power System

The energy independence, reliability and safety of energy distribution system operation as well as use of renewable resources have been hot research topics in recent years. This research leads to the development of active distribution grids with specific requirements. The Power Quality problems can arise when using renewable sources in active distribution grids. Problems are caused by decreased short-circuit power of local renewable sources, stochastic supply of electric energy from renewable sources and operating the active distribution grid in off-grid regime without connection to the external distribution system. In case of these conditions, the mutual interference between sources and loads is relevant and parameters of quality of electric energy can be exceeded. The results from analysis of quality of electric energy in the particular active distribution grid (off-grid power system) are introduced in this paper

Analysis of EMC Factors on Electronic Devices Using PLS-SEM Method: A Case Study in Vietnam

Electronic equipment is indispensable in the industrial 4.0 era. Electromagnetic Compatibility issues with electronic devices are increasingly concerning. The phenomenon of electromagnetic field compatibility is getting higher and higher. The operating quality of electronic equipment is more and more adversely affected, such as by the phenomenon of hesitation in operation for the operating structures, the generation of fire and explosion of electrical equipment, the loss of information, and many other negative effects. This paper discusses the relationship between Electromagnetic Compatibility (EMC) scoring, Electromagnetic Interference (EMI) scoring, and Electromagnetic Susceptibility (EMS) scoring with the performance quality of electronic devices (QUA). We perform reviews on regulatory institutions governing Electromagnetic Compatibility on electronic devices. To evaluate the proposed Electromagnetic Compatibility structure and its relationship to electronic devices, we proposed to use the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. The research results of the model show that the electronic device layout conditions and the lack of systematic conditions have a negative impact on the operating quality of the electronic equipment, while the conditions on equipment techniques, scientific and technological resources have positive and significant impacts

Harmonics Signal Feature Extraction Techniques: A Review

Harmonic estimation is essential for mitigating or suppressing harmonic distortions in power systems. The most important idea is that spectrum analysis, waveform estimation, harmonic source classification, source location, the determination of harmonic source contributions, data clustering, and filter-based harmonic elimination capacity are also considered. The feature extraction method is a fundamental component of the optimization that improves the effectiveness of the Harmonic Mitigation method. In this study, techniques to extract fundamental frequencies and harmonics in the frequency domain, the time domain, and the spatial domain include 67 literature reviews and an overall assessment. The combinations of signal processing with artificial intelligence (AI) techniques are also reviewed and evaluated in this study. The benefit of the feature extraction methods is that the analysis extracts the powerful basic information of the feedback signals from the sensors with the most redundancy, ensuring the highest efficiency for the next sampling process of algorithms. This study provides an overview of the fundamental frequency and harmonic extraction methods of recent years, an analysis, and a presentation of their advantages and limitations