Impulse Waveforms Research Articles

Naprezanja izolacije elektroenergetske opreme pri nestandardnim talasnim oblicima prenapona

During its operation, electrical equipment is constantly exposed to overvoltages of various waveforms, such as lightning discharges, switching operations, faults, etc. Therefore, adequate selection of overvoltage protection and equipment insulation withstand voltages are key factors in increasing system reliability. In general, insulation coordination is carried out by analyzing the insulation behavior for standard impulse and switching overvoltage waveforms. However, overvoltages that occur in operating conditions can significantly deviate from the standard waveforms of insulation withstand voltages, in terms of the front time, the duration of the wave, the existence of highfrequency components as result of reflections in the facility and other factors. This paper presents possible methods of assessing the behavior of equipment insulation for real voltage waves to which the insulation is exposed during exploitation and which deviate from standard waveforms, by analysis in the frequency domain. As there are different components in the overvoltage signal at different frequencies, which a different energy, the main goal of this paper is to analyze the insulation characteristics of a specific transformer from the point of view of the energy spectral density of the voltage wave that occurs at its terminals when an atmospheric discharge occurs. The analysis is based on the determination of the safety margin on the entire frequency spectrum of the overvoltage wave, that is, on the calculation of the so-called FDSF (Frequency Domain Severity Factor). The calculation results show that although the overvoltage amplitude is lower than the withstand voltage of the transformer insulation with an appropriate safety margin (the condition of the classic approach to insulation coordination is satisfied), the spectrum analysis of the voltage wave in the frequency domain shows that the insulation may still be compromised.

Influence of repetitive impulse waveform on surface discharge characteristics and insulation life for polyimide film

Influence of repetitive impulse waveform on surface discharge characteristics and insulation life for polyimide film

Partial discharge measurement and analysis under lightning impulse superimposed DC voltage in SF6 gas

The presence of lightning impulses (LIs) on the DC waveform can seriously influence the insulation performance of a GIL system. The waveshape can be a superposition of the DC and impulse waveform. In this study, the behaviour of partial discharge (PD) on an epoxy surface is investigated under DC and LI superimposed voltage in SF6. The lightning impulses with different polarities are superimposed on the epoxy surface under both positive and negative DC voltages, respectively. Positive lightning impulses are superimposed on a negative DC voltage with a 90% of the partial discharge inception voltage (PDIV) magnitude. The number and amplitude of the PDs are used to evaluate the insulation performance. The experimental results show that the LI with a different polarity applied to DC can excite the PDs on the epoxy surface. The excitation effect of positive LI superimposed on negative DC is more significant. According to the impulse amplitude and PD characteristics, the influence of superimposed LI on PD excitation can be divided into three stages. As the superimposed LI increases, the amplitude of the excited PD increases gradually, while the PD number first increases and then decreases. This study is expected to provide reference for manufacture and protection of power equipment.

Modeling of high frequency high voltage of waveforms on life of enamel insulation

<p>In recent years it has been observed that insulation failure in electrical motors is caused by adjustable speed drives fed by power electronic converters. These converters produce impulse waveforms having a high slew rate generated by the high switching frequency of IGBTs. This paper focuses on high switching frequency stress in low voltage electrical motors for adjustable speeds. To examine the motor winding insulation under such stress twisted-pair samples were developed from enameled wires. A single-coated polyester of enamel with a thickness of 40 microns is used for this work. High-frequencies, high voltages of Square, and Square-rising, Square-spike waveforms of 10-30 kHz are used here. The test results show that the insulation fails earlier for the Square waveform compared to the Square-spike and Square-rising waveforms. In a nutshell, there is an analysis of PD formation in the insulation system at a higher switching frequency is analyzed. Electric field distributions between twisted pairs with various air gaps of the insulation system stressed by the Square and Square-rising waveforms up to 30 kHz are modeled using COMSOL software.</p>

Convolutional Sparse Coding Using Pathfinder Algorithm-Optimized Orthogonal Matching Pursuit With Asymmetric Gaussian Chirplet Model in Bearing Fault Detection

Sparse representation has been widely used in bearing fault impact detection, which can find the impact that best matches the fault waveform from the pre-defined dictionary and recover the fault impulse waveform. However, the current dictionary of sparse representation and the efficiency of sparse representation algorithm need to be improved. In order to accurately detect the fault impulse in the original signal, a convolutional sparse coding using pathfinder algorithm-optimized orthogonal matching pursuit with asymmetric Gaussian chirplet model (CSC-OAGCM) is proposed in this paper. A new time-frequency atom prototype, AGCM, is used to match the fault impulse waveform. The specific application steps of the proposed algorithm are as follows: Firstly, a convolution dictionary is constructed with atoms generated by AGCM. Subsequently, based on the convolution dictionary, a pathfinder algorithm-optimized orthogonal matching pursuit algorithm is used to solve the sparse representation and optimize the atomic parameters to achieve the best approximation of the original signal. In other words, the proposed method detects the convolutional sparse patterns in the signal. A simulation signal, two sets of mixed signals of experimental data collected from the experimental platform and an axle box vibration signal collected from the actual operating train are used to verify the effectiveness of proposed method. Additionally, the spectral kurtosis and empirical wavelet transform are also used to process these signals, and their processing results are compared with those obtained by the proposed method to demonstrate the superiority of the proposed method.

General Formulas for Lightning Impulse Impedance of Horizontal and Vertical Grounding Electrodes

Voltage drop developed between the grounding electrode under lightning current and distant neutral ground determines the protection efficiency. The peak value of such voltage can be computed from known impulse impedance and current peak value. For the first time, in this letter, general formulas are derived for impulse impedance of horizontal and vertical electrodes valid for any length up to 100 m, soil's resistivity of 30 to 1000 Ωm, and current impulse front time of 0.2 to 10 μs. Waveforms of typical lightning impulses given in IEC standards are used, but it is shown that results are also relevant for other impulse waveforms. Soil ionization effects are taken into account, and the accuracy of the formulas is investigated. New formulas enable an estimate of lightning protection grounding's surge efficiency in a wide range of practical situations.

Effect of wave oscillation on breakdown characteristics of oil-impregnated paper under lightning impulse voltage

Effect of the oscillation on the breakdown characteristics of the oil-impregnated paper under different lightning impulse voltage waves are studied experimentally in this work. IEC60060-3 standard and the waveform requirements of the on-site impulse withstand voltage test are considered, and four lightning impulse waves with different oscillation frequencies and 1.2/50μs standard lightning impulse wave are applied during the experiment. The experimental results show that the breakdown voltage under 1.2/50μs impulse is lower than that under the oscillating impulse. Under the oscillating waves, as the oscillating frequency increases, the number of breakdown points distributed at the peak of the non-first cycle increases, the minimum breakdown time gradually shortens, and the breakdown voltage shows a decreasing trend. The possible breakdown process of paper and the influence mechanism of different waveform parameters are discussed in detail. The explanation could be that changes on the impulse waveform parameters affect the movement, trap and accumulation of the positive charges ionized inside the oil micro-cavity, causing differences in the breakdown results. This study deepens the understanding of the breakdown mechanism of paper from the perspective of the waveform parameters effect and can provide a theoretical reference for the explanation of on-site impulse withstand voltage test results.

Statistical Failure Characteristics of Air Gap Subjected to Damped Alternating Overvoltages and Its Risk Assessment

This paper examines characteristics of the statistical failure of rod-plane air gap (RPAG) under damped alternating overvoltage (DAOV) as their parameters, including the frequency and the damping factor, are varied. The failure probability is calculated by considering the probability density distribution of overvoltage in power systems, and the results show that the failure probability of insulation under the DAOV is higher than that under double exponential impulse waveforms (DEIW), where this shows the risk of the prevalent insulation design. We then propose a 3D model to predict the characteristics of failure that shows that the probability of failure increases with the frequency and the damping factor. We use a 3D analytical formula to propose a method characterized by a failure graph to search for typical parameters of the area of the waveform that poses a high risk to the insulation. The results of a verification experiment show that the risk of failure of the DAOV in the search area of the waveform is significantly higher than those of other DAOV. Both the proposed 3D prediction model and the search area can help improve the design of the insulation, and can be used to apply statistical methods for insulation coordination in power systems.

Detection of Partial Discharge in Oil Filled-Tank using Acoustic in Audio Frequency

In this paper, the acoustic emission of partial discharge (PD) in oil contained in the tank was detected by using microphone sensor. PD was generated by point-to-flat electrodes under DC high voltage. The given variables were the DC voltage stress, the electrode gap distance, and the location of PD and sensors. The acoustic and high frequency current were recorded along with the increased voltage. The acoustic signal was then transformed using the fast Fourier transform (FFT) to obtain the frequency spectrum. Furthermore, the acoustic waveforms, the acoustic frequency spectrum, and the PD current were analyzed and correlated. The results showed that the PD could be detected by its audio frequency signal. The impulse-shaped acoustic signal was recognized as a transition condition from normal to PD. The acoustic sensor attached to the outer wall of tank (contact type) was more sensitive than sensor that had a distance from the tank (non-contact type). The perfection level of impulse waveform may indicate the PD location in the oil-filled tank. The signal of acoustic and current did also not affect each other.

Experimental Study on the Effect of Lightning Impulse Oscillation Frequency on Pressboard Flashover in Oil

In this work, effect of the oscillation frequency on the oil surface flashover characteristics under lightning impulse voltage is experimentally studied. Four lightning impulse (OLI) waves with different oscillation frequencies and 1.2/50 μs standard lightning impulse (SLI) wave are used in this study. The experiment results show that flashover voltages under OLI are larger than those under SLI and the flashover time lags under OLI are longer than those under SLI. Additionally, the flashover voltage tends to increase and the time lag tends to be shorter as the oscillation frequency increases. According to the experimental results and the discharge theory of liquids, we believe that the waveform oscillation frequency affects both the effective electron generation time lag and the formative time lag. This work provides a reference for the waveform selection of the on-site withstand voltage test and explains the physical mechanism of the oil flashover discharge from the perspective of impulse waveform oscillation.

Hydrophone Spatial Averaging Correction for Acoustic Exposure Measurements From Arrays-Part II: Validation for ARFI and Pulsed Doppler Waveforms.

This article reports the experimental validation of a method for correcting underestimates of peak compressional pressure ( pc) , peak rarefactional pressure ( pr) , and pulse intensity integral (pii) due to hydrophone spatial averaging effects that occur during output measurement of clinical linear and phased arrays. Pressure parameters ( pc , pr , and pii), which are used to compute acoustic exposure safety indexes, such as mechanical index (MI) and thermal index (TI), are often not corrected for spatial averaging because a standardized method for doing so does not exist for linear and phased arrays. In a companion article (Part I), a novel, analytic, inverse-filter method was derived to correct for spatial averaging for linear or nonlinear pressure waves from linear and phased arrays. In the present article (Part II), the inverse filter is validated on measurements of acoustic radiation force impulse (ARFI) and pulsed Doppler waveforms. Empirical formulas are provided to enable researchers to predict and correct hydrophone spatial averaging errors for membrane-hydrophone-based acoustic output measurements. For example, for a 400- [Formula: see text] membrane hydrophone, inverse filtering reduced errors (means ± standard errors for 15 linear array/hydrophone pairs) from about 34% ( pc) , 22% ( pr) , and 45% (pii) down to within 5% for all three parameters. Inverse filtering for spatial averaging effects significantly improves the accuracy of estimates of acoustic pressure parameters for ARFI and pulsed Doppler signals.

An Empirical Model to Account for Spectral Amplification of Pulse-Like Ground Motion Records

Near-source effects can amplify seismic ground motion, causing large demand to structures and thus their identification and characterization is fundamental for engineering applications. Among the most relevant features, forward-directivity effects may generate near-fault records characterized by a large velocity pulse and unusual response spectral shape amplified in a narrow frequency-band. In this paper, we explore the main statistical features of acceleration and displacement response spectra of a suite of 230 pulse-like signals (impulsive waveforms) contained in the NESS1 (NEar Source Strong-motion) flat-file. These collected pulse-like signals are analyzed in terms of pulse period and pulse azimuthal orientation. We highlight the most relevant differences of the pulse-like spectra compared to the ordinary (i.e., no-pulse) ones, and quantify the contribution of the pulse through a corrective factor of the spectral ordinates. Results show that the proposed empirical factors are able to capture the amplification effect induced by near-fault directivity, and thus they could be usefully included in the framework of probabilistic seismic hazard analysis to adjust ground-motion model (GMM) predictions.

Supplementary comparison EURAMET.EM-S42, comparison of lightning impulse (LI) reference measuring systems

Main textIn 2016 the Consultative Committee for Electricity and Magnetism (CCEM) commissioned a supplementary comparison EURAMET.EM-S42 of Lightning Impulse (LI) measurement systems. This comparison was piloted by RISE (Sweden, formerly SP), and it was supported by VTT MIKES (Finland) and FFII LCOE (Spain). Eleven National Metrology Institutes (NMI) and two Designated Institutes (DI) from four Regional Metrology Organizations, EURAMET, COOMET, APMP and SIM, took part in the comparison.A commercial travelling measuring system (TRMS) for Lightning Impulse (LI) measurement was adopted for the comparison. The TRMS consisted of a 700 kV resistive voltage divider and a transient recorder with computer. The TRMS was calibrated by the pilot lab in November 2016 before start of the comparison, and the first circulation was between five EURAMET NMI/DIs. After an intermediate calibration by the pilot lab in July 2017, the TRMS was circulated between seven NMI/DIs in the other regional organisations. On the return of the TRMS in March 2019 a final calibration was made by the pilot lab.The measured parameters are defined in IEC60060-1. Test voltage value (U t), front time (T 1), time to half value (T 2) and relative overshoot (β') were measured for full impulses; and extreme value (U e) and time to chopping (T c) for front chopped waveform. The test voltage value ranged from -700 kV to 700 kV with two full and one chopped impulse waveform. A set of preferred voltage levels and waveforms was defined. The obtained expanded uncertainties (k = 2) of the comparison reference values (CRV) were: <0.3% for U t, <1.3% for T 1, <1.0% for T 2, <0.4% for β', <0.6% for U e and <1.4% for T c.The transfer reference measuring system of the previous LI comparison (EU-SMT4-CT98-2270), arranged between 1999 and 2002, is linked to this comparison. The link is established by comparing VTT MIKES system used 20 years ago with that used in this comparison.To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/.The final report has been peer-reviewed and approved for publication by the CCEM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Effects of lightning impulse front time on substation grounding system performance

&lt;table width="593" border="1" cellspacing="0" cellpadding="0"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td valign="top" width="387"&gt;&lt;p&gt;The role of the grounding system in the safety of the power system and protection of personnel is obvious during an unexpected short circuit or lightning discharge at the substation. The aim of this work is to analyze the effects of several parameters: lightning impulse front time, soil resistivity and types of grid materials on the grounding system of the Substation. The ground potential rise (GPR), touch voltage and step voltage of a 50 m x 60 m grounding grid buried at a depth of 0.5 m were computed using CDEGS when injected by impulse with different front times. Results show that the shorter the front time of lightning impulse waveform, the higher the value of GPR, touch voltage and step voltage. Meanwhile, when the value of soil resistivity is increased, the value of GPR, touch voltage and step voltage is also increased. Lastly, different types of grid conductor materials give different values of GPR, touch voltage and step voltage. However, it can be said that the differences are too small to be of any significance.&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;

Time-Domain Analysis of Retarded Partial Element Equivalent Circuit Models Using Numerical Inversion of Laplace Transform

Full-wave time-domain computational electromagnetic (CEM) solvers, which are integral equation (IE)-based, may suffer from what is called “late-time instability” problems. This unstable behavior occurs for CEM solvers for very fast rise-time input signals. A multitude of techniques has been devised by researchers over the years to solve the problem. In this article, we pursue an approach for the stable solution of full-wave partial element equivalent circuit (PEEC) models for fast-rising input waveforms. In particular, step and impulse response will be considered that are the most challenging from a stability point of view. For the solver part, a conventional full-wave PEEC code is used that requires one to use retarded partial elements. Unfortunately, a PEEC, as well as impedance Z-(method of moment) solvers using suitable numerical time-stepping methods have stability problems, especially for fast rising impulse or step inputs. An important step forward is achieved in this work by providing a larger class of stable solutions well above the stability achieved for time-stepping methods in the last 50 years. The time-domain stability is achieved by replacing the stepping integration methods with a numerical inversion of Laplace transform (NILT) technique. The NILT transform starts out by applying it to a frequency-domain PEEC solution. The surprising result is that the NILT-based method has a variable time-dependent bandwidth that is advantageous for the full-wave IE solution stability. In this article, we give several examples that show that a PEEC-NILT solution provides accurate and stable results for impulse, step- and piece-wise linear input waveforms.

On Site Oscillating Lightning Impulse Test and Insulation Diagnose for Power Transformers

This letter proposed a new lightning impulse test method for power transformers based on oscillating lightning impulse(OLI) waveform. The OLI has high generation efficiency and is easy to generate for field test. Partial discharge detection and transfer function analysis are used to evaluate the transformer insulation condition during the impulse test. The OLI waveform for transformer test satisfied with the requirements of the standard is obtained by altering the value of resistance and inductance in the circuit. The experiment was carried out on a transformer scale model to prove the validity of the proposed method. The results show that the current pulse method and the UHF method detect the PDs simultaneously as the insulation defect is excited at high voltage. Meanwhile, the transfer function changes due to the discharge in winding. It provides a new test and insulation diagnose method with application prospects for transformer lightning impulse test on site.

Identifying Different Classes of Seismic Noise Signals Using Unsupervised Learning

AbstractProper classification of nontectonic seismic signals is critical for detecting microearthquakes and developing an improved understanding of ongoing weak ground motions. We use unsupervised machine learning to label five classes of nonstationary seismic noise common in continuous waveforms. Temporal and spectral features describing the data are clustered to identify separable types of emergent and impulsive waveforms. The trained clustering model is used to classify every 1 s of continuous seismic records from a dense seismic array with 10–30 m station spacing. We show that dominate noise signals can be highly localized and vary on length scales of hundreds of meters. The methodology demonstrates the complexity of weak ground motions and improves the standard of analyzing seismic waveforms with a low signal‐to‐noise ratio. Application of this technique will improve the ability to detect genuine microseismic events in noisy environments where seismic sensors record earthquake‐like signals originating from nontectonic sources.

An Algorithm for Circuit Parameter Identification in Lightning Impulse Voltage Generation for Low-Inductance Loads

This paper presents an effective technique based on an artificial neural network algorithm utilized for circuit parameter identification in lightning impulse generation for low inductance loads such as low voltage windings of a power transformer, a large distribution transformer and an air core reactor. The limitation of the combination between Glaninger’s circuit and the circuit parameter selection from Feser’s suggestions in term of producing an impulse waveform to be compliant with standard requirements when working with a low inductance load is discussed. In Feser’s approach, the circuit parameters of the generation circuit need to be further adjusted to obtain the waveform compliant with the standard requirement. In this process, trial and error approaches based on test engineers’ experience are employed in the circuit parameter selection. To avoid the unintentional damage from electrical field stress during the voltage waveform adjustment process, circuit simulators, such as Pspice and EMTP/ATP, are very useful to examine the generated voltage waveform before the experiments on the test object are carried out. In this paper, a system parameter identification based on an artificial neural network algorithm is applied to determine the appropriate circuit parameters in the test circuit. This impulse voltage generation with the selected circuit parameters was verified by simulations and an experiment. It was found that the generation circuit gives satisfactory impulse voltage waveforms in accordance with the standard requirement for the maximum charging capacitance of 10 µF and the load inductance from 400 µH to 4 mH. From the simulation and experimental results of all cases, the approach proposed in this paper is useful for test engineers in selection of appropriate circuit components for impulse voltage tests with low inductance loads instead of employing conventional trial and error in circuit component selection.

Impact of impulse voltage frequency on the partial discharge characteristic of electric vehicles motor insulation

The urgent need for electric vehicles is the leading research to safer operation of electric motors on high frequency impulsive voltages. For low voltage electric vehicles partial discharge (PD) inception voltage tests under impulse voltage waveforms are desired. However, measuring PD using repetitive impulse waveforms is critical in selecting generators with appropriate parameters to increase PD detection sensitivity. Here, we report on PD characteristics for such kind of voltage waveforms, demonstrated with the high frequency and thermal impact on different types of motor insulation models. The increasing frequency of impulsive voltages tends to result in PD activities with low magnitude and short delay times. In this case, some PD pulses are missed because the PD and disturbance pulses produced by power electronic devices will likely overlap. Therefore, these parameters are carefully considered to evaluate the insulation performance of EV motors.

Myocardial infarction evaluation from stopping time decision toward interoperable algorithmic states in reinforcement learning

BackgroundThe Elliot wave principle commonly characterizes the impulsive and corrective wave trends for both financial market trends and electrocardiograms. The impulsive wave trends of electrocardiograms can annotate several wave components of heart-beats including pathological heartbeat waveforms. The stopping time inquires which ordinal element satisfies the assumed mathematical condition within a numerical set. The proposed work constitutes several algorithmic states in reinforcement learning from the stopping time decision, which determines the impulsive wave trends. Each proposed algorithmic state is applicable to any relevant algorithmic state in reinforcement learning with fully numerical explanations. Because commercial electrocardiographs still misinterpret myocardial infarctions from extraordinary electrocardiograms, a novel algorithm needs to be developed to evaluate myocardial infarctions. Moreover, differential diagnosis for right ventricle infarction is required to contraindicate a medication such as nitroglycerin.MethodsThe proposed work implements the stopping time theory to impulsive wave trend distribution. The searching process of the stopping time theory is equivalent to the actions toward algorithmic states in reinforcement learning. The state value from each algorithmic state represents the numerically deterministic annotated results from the impulsive wave trend distribution. The shape of the impulsive waveform is evaluated from the interoperable algorithmic states via least-first-power approximation and approximate entropy. The annotated electrocardiograms from the impulsive wave trend distribution utilize a structure of neural networks to approximate the isoelectric baseline amplitude value of the electrocardiograms, and detect the conditions of myocardial infarction. The annotated results from the impulsive wave trend distribution consist of another reinforcement learning environment for the evaluation of impulsive waveform direction.ResultsThe accuracy to discern myocardial infarction was found to be 99.2754% for the data from the comma-separated value format files, and 99.3579% for those containing representative beats. The clinical dataset included 276 electrocardiograms from the comma-separated value files and 623 representative beats.ConclusionsOur study aims to support clinical interpretation on 12-channel electrocardiograms. The proposed work is suitable for a differential diagnosis under infarction in the right ventricle to avoid contraindicated medication during emergency. An impulsive waveform that is affected by myocardial infarction or the electrical direction of electrocardiography is represented as an inverse waveform.