A measurement system for radiated transient electromagnetic interference based on general purpose instruments

This paper presents a measurement system intended to be used to assets the radiated electromagnetic interference (EMI) in both time and frequency domains. In order to keep the measurement setup as accessible and practical as possible, the direct measurements are recorded with a general purpose digital oscilloscope and processed with a commonly available personal computer. The measurement system was validated for radiated emissions testing using well-known, controlled transient and continuous signals emulating typical interferences. The results are in satisfactory agreement with those provided by a conventional EMI receiver for different types of detectors. The proposed approach shows that, currently, it is possible to implement a timesaving, accurate and generally inexpensive time domain measurement system for radiated emissions that is capable to overcome the limitations of the superheterodyne EMI receivers regarding the measurement of discontinuous electromagnetic disturbances and also able to provide additional enhanced features to evaluate and troubleshoot EMI problemsPostprint (published version

Power quality and electromagnetic compatibility: special report, session 2

The scope of Session 2 (S2) has been defined as follows by the Session Advisory Group and the Technical Committee: Power Quality (PQ), with the more general concept of electromagnetic compatibility (EMC) and with some related safety problems in electricity distribution systems. Special focus is put on voltage continuity (supply reliability, problem of outages) and voltage quality (voltage level, flicker, unbalance, harmonics). This session will also look at electromagnetic compatibility (mains frequency to 150 kHz), electromagnetic interferences and electric and magnetic fields issues. Also addressed in this session are electrical safety and immunity concerns (lightning issues, step, touch and transferred voltages). The aim of this special report is to present a synthesis of the present concerns in PQ&EMC, based on all selected papers of session 2 and related papers from other sessions, (152 papers in total). The report is divided in the following 4 blocks: Block 1: Electric and Magnetic Fields, EMC, Earthing systems Block 2: Harmonics Block 3: Voltage Variation Block 4: Power Quality Monitoring Two Round Tables will be organised: - Power quality and EMC in the Future Grid (CIGRE/CIRED WG C4.24, RT 13) - Reliability Benchmarking - why we should do it? What should be done in future? (RT 15

On-line signal analysis of partial discharges in medium-voltage power cables

Partial discharges are symptomatic of many degradation phenomena in power cables and may cause further deterioration of the insulation in many cases. Electrical im- pulses, generated by partial discharges, travel towards the cable ends, and can there be detected using appropriate sensors. Continuous monitoring of the insulation con- dition can be achieved by on-line detection and location of partial discharge (PD) signals. An important aspect of such a diagnostic is the analysis of on-line measure- ments. The research reported in this thesis is aimed at analysis of PD signals from on-line measurements and location of discharge sites. Signal analysis depends on knowledge of both signals and disturbances that are to be expected. To that end, characteristics of PD signals in medium voltage cables are studied in this thesis. The result of this study is a signal model of the propagation path between the discharge site and the sensors. The model accounts for cable sections with di®erent properties, and incorporates the propagation channel load impedances, i.e. the equipment to which a cable is terminated in an on-line situation. The exact propagation properties and load impedances depend on the speci¯c cable connection under test, and are unknown a priori. For this reason, research is conducted on meth- ods that enable experimental characterization of the parameters, by evaluating the response of the cable to applied transients. The presented methods rely on the ex- traction of pulses that are re°ected on impedance transitions within the cable system under test. On-line ¯eld measurements are corrupted by noise and interference, which impede PD signal detection and location. Generally, narrowband interferences resulting from radio broadcasts dominate the measurements, thus prohibiting data-acquisition trig- gered by PD signals. Broadband background noise is present within the entire PD signal bandwidth, and therefore poses a fundamental limit on PD signal analysis. Generally, existing extraction techniques for PD signals only partially exploit a priori knowledge of both signals and interference. In this thesis, matched ¯lters are ap- plied that are derived from the signal model, and are optimally adapted to the signals that can be expected. Besides signal extraction, matched ¯lters provide a means to estimate the PD magnitude and the signal arrival time. Likewise, discharge location methods based on the signal model are proposed, resulting in optimal location esti- mators. Computer simulations illustrate the e®ectiveness of the proposed algorithms and show that the attainable accuracy can be speci¯ed by theoretical bounds. Accurate PD location relies on estimation of the di®erence in arrival times of signals originating from the same discharge. In case of on-line detection, the cable is connected to the grid, and signals are not necessarily re°ected at the cable ends. Therefore signal detection at both sides is generally required for the purpose of dis- charge location. Synchronization of the measurement equipment is achieved using pulses that are injected into the cable connection. Finite-energy disturbances, such as PD signals that originate outside the cable connection under test, frequently occur in on-line situations. Since measurements are synchronously conducted at both cable ends, pulses originating within and outside the cable can be distinguished by examining the di®erence in time of arrival. Moreover, in many situations, the signal direction of arrival can be determined by detecting pulses in two di®erent current paths at a cable termination. This method is applied as an additional technique to discriminate PD signals and disturbances. Based on the results of research, a measurement system is proposed, which enables automated on-line PD detection and location in medium voltage cable connections. The conceptual design is validated by experiments, and the results demonstrate that the practical application is promising

Statistical analysis in electromagnetic compatibility

Power electronic (PE) converters are electronic devices designed to process electrical power, transforming the input voltage into an output voltage with desired characteristics. Their main function, which is power conversion, is enabled through the usage of switching devices, such as transistors. Due to the rapid development of the Smart Grid (SG) power devices are more often used alongside or close to communication systems, in particular serial communication devices. The operation of the power converters might induce electromagnetic interference (EMI) and bring about malfunction of these communication devices, which poses a challenge in achieving electromagnetic compatibility (EMC) of the system. The range of switching frequencies used in modern power converters corresponds to the conducted EMI range (9 kHz { 30 MHz), and the impact of conducted EMI is highly influenced by the presence of parasitic elements, values of which exhibit uncertain behaviour due to environmental conditions, geometrical layouts of the circuits, and manufacturing tolerances of the circuit elements.This thesis presents a statistical approach to identify EMI issues that might occur due to the coexistence of power converters and serial communication systems and proposes the use of stochastic simulation, surrogate modelling, and statistical analysis to compare methodologies for EMI reduction, identify the most in uential parasitic elements and enable optimization of PE circuits.Firstly, it presents two mathematical models for analysing EMI induced by PE converters when the switching function is realized with Random Modulation (RanM) and Deterministic Modulation (DetM) techniques, along with a novel averaging scheme to facilitate their comparison, thereby overcoming the existing limitations of the models and enhancing its ability to directly calculate the probability of communication error. Contrary to expectations posed by many researchers, the research found that RanM does not improve EMC compliance in the context of PE converter's impact on serial communication devices, with RanM and DetM demonstrating similar influences on average. Additionally, the thesis determined that a Polynomial Chaos (PC)-based surrogate model outperforms Support Vector Machines (SVM) in modelling complex PE converters as judged by prediction error and stability against Monte Carlo simulations. Finally, it presents a methodology using Sobol' indices derived from the PC model to identify and optimize the most sensitive parasitic elements in PE converters, aiming to mitigate the influence of EMI on communication error probability.This thesis provides the EMC engineers and system integrators methods to validate their approaches for achieving EMC compliance. Accompanying the thesis is an open source toolbox `UQSpice' that allows to use the methods presented in this thesis for performing PC-based simulations and sensitivity analysis using an LTSpice circuit simulation software

UTILIZATION OF MACHINE LEARNING TO OPTIMIZE RADIO-FREQUENCY INTERFERENCE IDENTIFICATION FOR U.S. NAVAL COMMUNICATIONS

The proliferation of electronic devices emitting radio waves has led to Radio Frequency (RF) spectrum congestion. This poses a significant threat to Department of Defense (DOD) environments, especially naval communications heavily reliant on satellite systems, which are susceptible to electromagnetic interference. The lack of sufficient interference identification and characterization capabilities further compounds the operational risks faced by naval units. This thesis investigates the utilization of machine learning (ML) techniques for interference detection in RF transmissions. With their advanced data analysis and pattern-recognition capabilities, ML algorithms can enhance interference detection and mitigation. Two architectures, a basic autoencoder and Long Short-Term Memory (LSTM) autoencoder, were evaluated for their ability to identify anomalous RF data within a dataset. The research methodology involved generating RF data with varying Additive White Gaussian Noise (AWGN) levels in a basic transmission pathway. The ML models were trained using normal RF data and evaluated on their ability to detect and classify signals with and without interference. The results demonstrate that both the basic autoencoder and LSTM autoencoder models could effectively identify interference. The LSTM autoencoders achieved a success rate of about 99%, indicating their potential use as a solution to the capabilities gap for interference identification.Approved for public release. Distribution is unlimited.Lieutenant, United States Nav

RF and Microwave Measurements

open1noBasic theory and techniques are concentrated mostly in the first four chapters, where definitions, formulas and references are collected aiming at giving a thorough overview of the most relevant topics: circuit theory, material properties, transmission lines, signal analysis and spectral analysis, including random processes, probability and statistics. The central chapters 5, 6 and 7 deals with three important elements of setups and experiments: cables, printed circuit boards and connectors. The influence on the overall measurement, their modeling and characterization are discussed, keeping an eye on applicable standards. The last four chapters cover advanced aspects of scattering parameters, differential lines and mixed modes, and the use and performance of spectrum analyzer and vector network analyzer.openA. MariscottiMariscotti, A