Showing papers on "Partial discharge published in 2022"

Multispectral Optical Partial Discharge Detection, Recognition, and Assessment

Abstract: In this article, a hypersensitive multispectral partial discharge (PD) optical sensor array was developed, by which the optical pulses in seven independent bands can be acquired simultaneously. By using this sensor array, the multispectral pulses for three typical PDs in gas insulated system were obtained experimentally and analyzed with phase-based (phase-resolved) and nonphase-based (spectral-ratio-based) multispectral characteristics, respectively. It indicates that the multispectral characteristics produced by a specific discharge defect provide unique spectral signatures in discharge mode as well as stage evolution. Based on the intrinsic relationship between the discharge feature and optical emission spectrum, we adopted the classification algorithms and spectral-ratio-reserved multispectral characteristics to implement pattern recognition as well as assessment on the three typical PDs, which obtained the hit ratios exceeding 91%. In principle, such detection approach also supports the phase-independent PD diagnosis especially for dc power equipment.

AC Breakdown Voltage and Partial Discharge Activity in Synthetic Ester-Based Fullerene and Graphene Nanofluids

Abstract: This paper deals with the study of the AC breakdown voltage (BDV) and partial discharges (PDs) activity of synthetic ester-based nanofluids (NF) with two kinds of carbonic nanoparticles (NPs), namely graphene (Gr) and fullerene (C₆₀); the synthetic ester (SE) being Midel 7131. The BDV measurement was achieved at various concentrations of NPs and different electrodes gap distances, while the partial discharges activity was studied only at the optimal concentration that gave the best improvements of BDV. First, a detailed improved procedure for preparing our NFs is presented. Then, the zeta potential measurements are performed on these NFs, and their stability is checked. After the preparation and characterization of samples, the BDVs and PDs parameters are measured according to IEC 60156 (modified gap distance) and IEC 60270 standards, respectively. Finally, conformity of the experimental data with Normal and Weibull distributions is examined, and the BDV at cumulative probabilities of 1% and 50% are then deduced. It is shown that BDV outcomes for all studied liquids obey both Normal and Weibull distributions, and the BDVs at cumulative probabilities of 1% and 50% are improved. Moreover, adding Gr and C₆₀ nanoparticles at different concentrations enhances the BDV values for investigated electrode gaps (0.1 to 2.0mm). The best improvement is obtained with a concentration of 0.4 g/L for 0.5mm and 0.7mm electrode gap with fullerene and Graphene nanoparticles, respectively. For a 2mm gap distance, the best improvements are of about 12.67% and 16.64% with 0.4g/L of C₆₀ and 0.3 g/L of Gr, respectively. It is also shown that the addition of C₆₀ significantly reduces the activity of partial discharges compared to pure SE, while the addition of Gr destroys the partial discharges resistance of pure SE.

Design of an Effective Antenna for Partial Discharge Detection in Insulation Systems of Inverter-fed Motors

Abstract: Partial discharge (PD) measurements under repetitive impulse voltages are critical for the qualification of inverter-fed motor insulation systems. Severe electromagnetic interference due to high frequency switching from power electronic devices can cause the traditional PD detection techniques of sinusoidal voltage unfeasible. This article presents the design of an Archimedes spiral antenna that can work effectively for PD detection under fast rise time repetitive impulse voltages. The antenna structure is optimized by a media superstrate with a high dielectric constant over the radiant surface. Through the optimized design, both the gains of the antenna in the 0.5–1.5 GHz frequency range and the signal-to-noise ratio for PD detection are increased substantially. Modeling and experimental results prove that the gain of the antenna can reach 2.5 dB in the frequency range of 500–900 MHz and become higher than 7.0 dB in the frequency range of 900–2.0 GHz, with a voltage standing–wave ratio smaller than 1.4. This seems to be a significant achievement for PD detection under fast rise time impulse voltages.

Insulation and Switching Performance Optimization for Partial-Discharge-Free Laminated Busbar in More-Electric Aircraft Applications

Abstract: This article proposes an insulation design strategy of laminated busbar to avoid partial discharge (PD) in more-electric aircraft (MEA) applications. During high-altitude operation, the converters for MEA are exposed to low air pressure, making partial discharge being triggered easier. But blindly increasing the insulation results in excessive parasitic inductance and degraded switching performance, which lead to serve losses and electromagnetic interference (EMI) problems during high-frequency switching operations. This article targets this issue and conducts a systematic study for laminated busbars in these high-density converters for MEA application. Moreover, it proposes a model-based codesign strategy to simultaneously optimize the busbar's stray inductance control and insulation layer design. To verify the design strategy, a busbar for a three-level (3L) 450-kVA converter is designed, fabricated, and evaluated. The measured minimum partial-discharge inception voltage is 43% higher than the rated voltage at 0.2 atm. Moreover, busbar stray inductance of 12.0 nH is achieved, which is lower than published literature for 3L converters. The low-inductance busbar can fully exploit the advantage of SiC-mosfet, helping it reduce switching loss by 66.7% at 1 kV 350 A with minimum voltage overshoots.

Design and Implementation of Ultra-Wide Band Antenna for Partial Discharge Detection in High Voltage Power Equipment

Abstract: Partial discharges (PD) are the most common and harmful threat to the health of electrical insulation of high voltage (HV) and high field (HF) equipment. The occurrence of PD activity in HV and MV equipment is at the same time a cause and a sign of insulation degradation that may eventually result in the breakdown of the HV power equipment. For the safe and reliable operation of HV power equipment, continuous PD monitoring needs to be conducted conveniently to prevent any unplanned power outages and damage to electrical power equipment. The ultra-high frequency (UHF) PD measurement method has been widely used as an effective technique to detect PD activity on HV power equipment due to its non-invasive principle. To enable PD detection accuracy, there is still a need for more sensitive PD sensors that can assist the UHF PD monitoring system by suppressing ambient background noise and low-frequency electromagnetic interferences from telecommunication such as GSM signals. To tackle the sensitivity issues, this article presents a new design of ultra-wideband (UWB) microstrip patch antenna that is capable of effective suppression of low-frequency interference signals. The proposed antenna, designed, simulated, and optimized using the CST Microwave Studio software, has a bandwidth of 3.3GHz, below -10dB, in the operating frequency range of 1.2GHz-4.5GHz. The prototype of this antenna, printed on an FR4 substrate of a thickness of 1.6mm and a dielectric constant of 4.4, featuring a compact size of 100mm $\times100$ mm $\times1.6$ mm, was implemented to detect PD through laboratory experiments. This paper shows that the designed UWB antenna has high sensitivity, good noise rejection and it is, therefore, a promising candidate sensor for PD detection on HV equipment.

Breakdown Performance and Partial Discharge Development in Transformer Oil-Based Metal Carbide Nanofluids

Abstract: In this work, the influence of semi-conductive SiC nanoparticles on the AC breakdown voltage and partial discharge development in natural ester oil FR3 is examined. Primarily, the dielectric constant and the electrical conductivity of the nanoparticles are measured following the broadband dielectric spectroscopy technique. The nanoparticles are added into the matrix following the ultrasonication process in three weight percentage ratios in order for their effect to be evaluated as a function of their concentration inside the base oil. The processing of the results reveals that the nanofluid containing SiC nanoparticles at 0.004% w/w demonstrates the highest AC dielectric strength improvement and shows the greatest resistance to the appearance of partial discharge activity. The mechanisms behind the aforementioned results are discussed in detail and confirmed by the broadband dielectric spectroscopy technique, which reveals that this particular nanofluid sample is characterized by lower dielectric constant and electrical conductivity than the one with double the weight percentage ratio.

Detection and Analysis of Partial Discharges in Oil-Immersed Power Transformers Using Low-Cost Acoustic Sensors

Abstract: Partial Discharge (PD) is one of the symptoms of an electrical insulation problem, and its permanence can lead to the complete deterioration of the electrical insulation in high-voltage equipment such as power transformers. The acoustic emission (AE) method is a well-known technique used to detect and localize PD activity inside oil-filled transformers. However, the commercially available monitoring systems based on acoustic sensors still have a high cost. This paper analyses the ability of low-cost piezoelectric sensors to identify PDs within oil-filled power transformers. To this end, two types of low-cost piezoelectric sensors were fully investigated using time-domain, frequency-domain, and time-frequency analysis, separately. Thereafter, the effectiveness of these sensors for PD detection and monitoring was studied. A three-phase distribution transformer filled with oil was examined. PDs were produced inside an oil-immersed transformer by applying a high voltage over two copper electrodes, and the AE sensors were coupled to the housing of the transformer. By extracting typical features from the AE signals, the PD signals were differentiated from on-site noise and interference. The AE signals were analyzed using acoustic signal metrics such as peak value, energy criterion, and other statistical parameters. The obtained results indicated that the used low-cost piezoelectric sensors have the capability of PD monitoring within power transformers.

Effect of Voltage Slew Rate on Partial Discharge Phenomenology During Voltage Transient in HVDC Insulation: The Case of Polymeric Cables

Abstract: In this article, the partial discharge (PD) behavior inside a cavity embedded in a dc cable, upon application of a voltage step from transient till steady-state dc, is analyzed as a function of voltage slew rate. The variation of PD characteristics, namely PD charge amplitude and repetition rate, is modeled and fitted from the beginning of the voltage transient to dc steady state, and the extent of aging associated with PD at different slew rates is evaluated through a cumulative damage concept. Two possible scenarios for the electric field transient and PD repetition rate are presented, differing for the ratio of conductivity and permittivity of dielectric and cavity medium. Having demonstrated that the proposed PD repetition rate model can predict reasonably the experimental results, it is shown that slowing down voltage rise time during, e.g., cable energization or voltage polarity inversion, could be beneficial to reduce the accelerated aging extent associated with voltage transients.

Study of Ultra High Frequency Measurement Techniques for Online Monitoring of Partial Discharges in High Voltage Systems

Abstract: Partial Discharge (PD) activity is a pre-cursor for insulation degradation which may eventually lead to catastrophic failure of the electrical equipment with severe social and economic consequences. It is therefore imperative that PD is detected at its early stages to permit repair or replacement, prior to total failure. The bulky non-planar construction of existing ultra-high frequency (UHF) sensors coupled with the lack of proper feeding techniques and the ultrawide signal bandwidth of PD signals which necessitates the use of digital storage oscilloscope have restricted field deployment of UHF technique for online PD detection. In this work, we present a compact ( $0.58 \boldsymbol {\lambda } $ ) wideband (0.5-3 GHz) dual arm Archimedean slot spiral with coplanar waveguide feed for PD detection, where $\boldsymbol {\lambda } $ is the wavelength at center frequency. Numerical simulations of the antenna were compared with the measurements of the fabricated antenna. The fabricated wideband antenna was used to detect PD emissions from a mineral oil test cell connected to 10 kVA 50 Hz transformer. We also present different UHF signal measurement techniques ranging from PD pulse detection to reconstruction of the bandlimited PD signal in the digital domain for online structural health monitoring of high voltage systems. The proposed UHF PD measurement techniques are low cost compared to the conventional approach and indicate the feasibility of an embedded system for online PD monitoring using the fabricated UHF sensor.

A Domain Adaptive Deep Transfer Learning Method for Gas-Insulated Switchgear Partial Discharge Diagnosis

Abstract: Intelligent fault diagnosis methods, especially convolutional neural network (CNN), have made significant progress in gas-insulated switchgear (GIS) partial discharge (PD) diagnosis, which are attributable to two reasons: 1) the training and testing samples come from the identical distribution; 2) there are massive labeled data with PD information. However, owing to the specific operating conditions of GIS, collecting massive samples from the same distribution is difficult in field conditions. With the purpose of resolving the data dilemma of conventional diagnosis methods in the field, we propose a domain adaptive deep transfer learning (DADTL) CNN for small samples GIS PD diagnosis. First, we adopted a CNN to automatically extract transferable features from PD samples. Then, a multilayer DADTL is developed to reduce the marginal and conditional distribution of learned transferable features, and Sliced Wasserstein distance (SWD) is employed as a penalty to reduce the negative migration. The experimental verification was performed on experimental and on-site GIS PD datasets. The results show that DADTL CNN can effectively achieve a high-accuracy diagnosis of GIS PD for small samples. Compared with other methods, the DADTL CNN can achieve more accurate and robust GIS PD diagnosis for on-site small samples.

Application of Image Sensors to Detect and Locate Electrical Discharges: A Review

Abstract: Today, there are many attempts to introduce the Internet of Things (IoT) in high-voltage systems, where partial discharges are a focus of concern since they degrade the insulation. The idea is to detect such discharges at a very early stage so that corrective actions can be taken before major damage is produced. Electronic image sensors are traditionally based on charge-coupled devices (CCDs) and, next, on complementary metal oxide semiconductor (CMOS) devices. This paper performs a review and analysis of state-of-the-art image sensors for detecting, locating, and quantifying partial discharges in insulation systems and, in particular, corona discharges since it is an area with an important potential for expansion due to the important consequences of discharges and the complexity of their detection. The paper also discusses the recent progress, as well as the research needs and the challenges to be faced, in applying image sensors in this area. Although many of the cited research works focused on high-voltage applications, partial discharges can also occur in medium- and low-voltage applications. Thus, the potential applications that could potentially benefit from the introduction of image sensors to detect electrical discharges include power substations, buried power cables, overhead power lines, and automotive applications, among others.

Characterization of Partial Discharges in High-Frequency Transformer Under PWM Pulses

Abstract: Partial discharge (PD) is a phenomenon often occurring in insulation system defects (cavities), which can significantly affect life and reliability. While broad knowledge on PD phenomenology of high-frequency transformers (HFT) has been achieved under ac sinusoidal voltage, much less work has been done to infer PD behavior under emerging high frequency pulsewidth modulation (PWM) operation conditions. An impediment has been the limited appropriate test equipment. A recently developed novel ±5 kV GaN-based high-frequency PWM supply with controllable dV/dt, voltage level and frequency has been developed. This article explores the application of these measurements to the testing of materials in this electrical environment. Two commonly used windings for HFT were tested under different applied voltage magnitudes, frequencies, and slew rates. According to the test results, at high frequency (up to 50 kHz) the electric field generated by space charge deposited by PD occurring during previous PWM pulses plays an important role in PD behavior. The frequency dependent permittivity of the insulation material can also affect PD measurement results.

Impact of Magnetic Field on Corona Discharge Behavior of Mineral Oil Under AC Voltage

Abstract: This article reports an experimental investigation of the impact of magnetic field on corona discharge activity in mineral oil, using both ultrahigh-frequency (UHF) and fluorescence techniques under ac voltage. The results show that corona inception voltage (CIV) increased under ac voltage with varying harmonic frequencies without considering any phase shift and reduced marginally under magnetic field. In addition, the impact of the magnetic field shifted the dominating frequency of the UHF signal (0.9 GHz) obtained under ac voltage toward lower frequencies (0.3 and 0.6 GHz). Under high magnetic fields, the parameters such as rise time, fall time, and pulsewidth of the fluorescence signal increased in its magnitude compared to its effect without a magnetic field. Also, using both the UHF sensor and the fluorescence sensor, there was no clear difference in the phase-resolved partial discharge (PRPD) pattern caused by corona discharge (with and without magnetic field). Furthermore, the number of discharges is observed to be high under the impact of harmonic ac voltages with third- and seventh-order containing total harmonic distortions (THDs) of 4% and 40%.

Separation and Classification of Corona Discharges Under Low Pressures Based on Deep Learning Method

Abstract: With the growing concern toward the global warming crisis, the electrification of commercial aircraft is targeted to reduce greenhouse gas emissions from the aviation industry. However, the environment that an aircraft operates in provides significant design challenges. Moreover, the technologies that enhance the power density of the powertrain (such as higher voltage levels and wide bandgap devices) lead to severe tension on the insulation systems. The combination of harsh environmental conditions and insulation-threatening technologies raises concern about the reliability of electrical equipment, such as power generators, motors, and cables. Since the failure of the insulation system translates into the failure of the entire equipment, it is crucial to investigate the behavior of discharge sources under low-pressure conditions. In this regard, this study develops a dense convolutional neural network (DenseNet) model based on experimental data to separate and classify various sources of corona discharge under low-pressure conditions. The results show that DenseNet models can achieve high accuracy within a reasonable training time. The accurate detection and classification of discharge sources provide the backbone of a dielectric online condition monitoring system (DOCMS) that can actively monitor the health of electrical equipment in an electric aircraft.

Discharge Characteristics and Detectability of Metal Particles on the Spacer Surface in Gas-Insulated Switchgears

Abstract: Metal particles and dirty contaminants on the spacer surface are mainly considered to be the critical factor in sudden flashovers. Understanding the discharge characteristics as well as the detectability of metal particles in the gas-insulated switchgear (GIS) will be helpful in improving its safety and reliability. In this paper, a high-sensitivity measurement system based on cross-reference pulse current (PC) and ultra-high-frequency (UHF) methods was established. The PC and UHF signals generated by partial discharges (PDs) of metal particles of different lengths (Φ = 0.5 mm, L = 2, 5, 8, and 10 mm) at different positions on a real spacer surface were studied. The PD characteristics and detectability of the metal particles on the spacer surface were obtained while the detection limitation was also discussed. It is found that under PD test condition, the apparent charge of the PDs is less than 1 pC for particles shorter than 5 mm, and the conventional PD detection method have limitations in detecting these short particles on the spacer surface. Under operation condition, only the apparent charge of particles longer than 8 mm can exceed 1 pC, which means it is difficult to detect the particles shorter than 8 mm in field. However, the result indicates that even the 5 mm long particle will be harmful to the GIS. Meanwhile, it is also been found that the detection sensitivity also has a great influence on the judgement of PD severity. This study is of great interest for understanding the PD characteristics, discharge levels, and detectability of short metal particles on spacer surface.

A rapid capacity evaluation of retired electric vehicle battery modules using partial discharge test

Abstract: As the number of EVs hitting the roads increased, dealing with their waste such as retired LIBs become an increasingly important issue to guarantee sustainability and reduce the cost of the recycling process. This imposes establishing a practical and cost-effective gateway testing framework to sort the retired batteries based on their remaining energy capacity, and to assign them for repurposing/reusing or for recycling to extract the raw materials. Therefore, the purpose of this paper is to introduce a practical sorting method that entails the use of incremental capacity, equivalent circuit model, and manipulated coulomb counting to evaluate the full capacity of retired battery modules based on partial discharge profile. The feasibility of the proposed method is demonstrated on both truncated full discharge profile and pulse discharge profile from partially charged battery. For the investigation, 48 lithium-ion modules from retired 24 kWh Nissan Leaf battery pack are used. The experimental results show that the proposed method is capable to estimate the full capacity with a maximum error of 5%. Furthermore, a considerable reduction in the test time is achieved, with only the terminal voltage and discharge current are used, which is of great practical significance to the battery recycling industry where the cost and time are dominant. • Discharge capacity is a key feature that influences the End-of-Life decision of a battery pack in electric vehicles. • Full discharge capacity, partial discharge capacity, and incremental capacity are applied on 48 retired battery modules. • Partial discharge capacity is investigated to reduce the testing time of retired modules subjected to recycling or reuse.

Partial Discharge Diagnostics: Data Cleaning and Feature Extraction

Abstract: Detection of partial discharge (PD) in switchgears requires extensive data collection and time-consuming analyses. Data from real live operational environments pose great challenges in the development of robust and efficient detection algorithms due to overlapping PDs and the strong presence of random white noise. This paper presents a novel approach using clustering for data cleaning and feature extraction of phase-resolved partial discharge (PRPD) plots derived from live operational data. A total of 452 PRPD 2D plots collected from distribution substations over a six-month period were used to test the proposed technique. The output of the clustering technique is evaluated on different types of machine learning classification techniques and the accuracy is compared using balanced accuracy score. The proposed technique extends the measurement abilities of a portable PD measurement tool for diagnostics of switchgear condition, helping utilities to quickly detect potential PD activities with minimal human manual analysis and higher accuracy.

Partial Discharge Monitoring of Medium Voltage Switchgears: Self-Condition Assessment Using an Embedded Bushing Sensor

Abstract: Condition assessment of Medium Voltage switchgears requires effective, but inexpensive solutions to become a common practice. On the other hand, failure of a switchgear component can cause cascade effects and outage of other apparatus, in addition to significant economic losses due, e.g., to lack of energy availability. A major diagnostic property to evaluate switchgear health and reliability is partial discharges, being a direct cause of failure of organic insulation systems. A new approach to automatic, self-assessment of switchgear reliability based on partial discharge, PD, acquisition and processing, as well as a new type of PD sensor solution are presented in this paper. The sensor is based on the capacitive divider existing in most bushings to indicate the presence or absence of voltage. The innovative automatic software is able to provide automatic noise and PD separation, noise rejection and type of PD-source identification. The embedded bushing sensor has been tested on switchgears in the presence of defective components as cable terminations and bushings. Results show that the sensor, coupled with the automatic software, is able to provide good sensitivity compared to other sensors, and good capability to locate the cabinet and identify the type of source generating partial discharges.

Influence of Voltage Harmonics on Partial Discharge Diagnostics in Electric Motors Fed by Variable-Frequency Drives

Abstract: Typically, in partial discharges (PD) diagnostics tests carried out in a laboratory, harmonic content in a voltage waveform is ignored. However, during the operation of variable-frequency drives (VFD)-fed electric motors, the distorted voltage waveform is produced due to the addition of harmonics components in the sinusoidal voltage waveform. The distortion level increases when the VFD is operated at a lower speed ratio. The additional spectral components in the applied voltage waveform can have a significant impact on the PD behavior in the insulation of the electric motor. Therefore, during online PD monitoring, overlooking the harmonic regime in the applied voltage may lead to a false interpretation of PD data. This article investigates the influence of voltage harmonics distortion produced during the variable-speed operation of VFD on PD characteristics. For this purpose, online PD measurements have been carried out by performing a series of experiments on eight VFD-fed motors under variable operating conditions. The PD severity at different harmonic compositions is experimentally investigated by determining various PD characteristic parameters including PD inception voltage, accumulated apparent charge, average discharge current, discharge power, and quadratic rate. Also, two terms Gaussian models have been mathematically developed using 288 data samples to quantify the variations in PD characteristic parameters against distortion parameters. The article proposes a framework for properly evaluating harmonics impact in PD for electric motors and correctly estimating stator insulation degradation.

Investigation of Partial Discharges in AlN Substrates Under Fast Transient Voltages

Abstract: The objective of this article is to characterize partial discharge (PD) inception voltages and patterns at sinusoidal and square voltages in insulating ceramic substrates with generic manufacturing defects. PD tests were conducted on active metal brazed (AMB) aluminum nitride (AlN) substrates either with cavities in the polymer coating or sharp protrusions of the metal brazing. The substrates were tested in silicone liquid instead of silicone gel. Light sensitive imaging was used to localize the PD sites on the surface. PDs at square voltage with rise time of $1.6 ~\mu \text{s}$ were measured with a high-frequency current transformer and a photomultiplier. In both substrate types, the peak–peak value of the PD inception voltage (PDIV) was higher at sinusoidal voltage compared to peak-peak value of the square wave. This difference was more pronounced in uncoated substrates, where discharges incepted at sharp edges surrounded by silicone liquid. For both types of defects, comparable PDIVs were measured at bipolar and unipolar square waves. Results for unipolar pulses are discussed considering the role of charge memory effect.

The Study on a New Method for Detecting Corona Discharge in Gas Insulated Switchgear

Abstract: Partial discharge (PD) is the main cause of insulation deterioration and failure of gas-insulated switchgear (GIS). Corona discharge (CD) is a typical type of PD in gas-insulated switchgear. Accurate and sensitive measurement of CD in GIS is of great significance for theoretical research in the laboratory and fault prediction of GIS in the actual operation. A novel method for detecting CD in GIS is proposed in this article. A coaxial structure model for simulating GIS is established. The CD detecting sensor based on the proposed method is designed for this model. An artificial tip defect is designed on the internal high voltage conductor of the coaxial model to simulate CD in GIS. A 50 Hz ac power supply, a dc negative power supply, and a dc positive power supply are applied as excitations to generate the CD at the defect, respectively. The discharge pulse signal is detected by the proposed sensor. The results show that the proposed sensor can completely obtain the information of the CD pulse signal. The proposed method has the same anti-electromagnetic interference ability as the ultrahigh-frequency method and has a high sensitivity to CD in GIS.

Research progress on photoacoustic SF6 decomposition gas sensor in gas-insulated switchgear

Abstract: In the power industry, sulfur hexafluoride (SF6) as an insulating gas is widely used in gas-insulated switchgears (GISs). Owing to the latent inner insulation defects of GIS, various SF6 gas decompositions are generated in the process of partial superheating and partial discharge (PD). The decomposition components and concentrations are different under different PD types. A number of gas sensors were reported for the detection of these decompositions. Photoacoustic spectroscopy (PAS) gas sensors have been developed for many applications owing to their high sensitivity and selectivity, such as gas pollutant detection, industrial process control, and non-invasive medical diagnosis. Due to the SF6 physical constants being different from that of nitrogen (N2) or air, the sensor structure should be redesigned. A detailed review of four different types of PAS-based gas sensors is discussed and compared.

Altitude Readiness of High-Voltage IGBTs Subjected to the Partial Discharge at Harsh Environmental Conditions for Hybrid Electric Aircraft Propulsion

Abstract: The reliability of the insulation of commercially used high-voltage insulated gate bipolar transistor (IGBT) subjected to untimely initiation of partial discharge (PD) at low pressures and high temperatures is investigated and discussed in this letter. To date, no research has addressed the vulnerability of the high-voltage IGBTs to the PDs at harsh environmental conditions for aerospace applications. This letter aims to fill this gap and illustrate the PD characteristics initiated between the electronic components inside the silicone gel. To this end, five commercial 3.3-kV IGBT modules and four 4.5-kV IGBT modules were tested at ac voltage under low pressures (20, 15, and 10 kPa) and high temperatures up to 120 °C. An efficient PD test method and an anti-series connection configuration are suggested, which emulate a realistic operational scenario for IGBTs together with the one suggested by the current standard. Experimental results reveal the occurrence of inconsistent PDs initiating from possible dynamic PD source inside the gel at low pressures, and more intense and consistent PDs when the temperature increases. It is expected the findings highlight the importance of PD tests on IGBTs at the abovementioned operation conditions and provide a selection and modification guidelines of PD-free IGBTs for manufacturers and engineers in the aerospace industry.

SF₆ Decomposed Component Analysis for Partial Discharge Diagnosis in GIS: A Review

Abstract: This paper compiles, summarizes, and deliberates over one hundred important works on the different approaches and advances in the surveillance and diagnosis of the internal status of SF ₆ gas-insulated equipment (GIE), particularly partial discharge (PD) diagnosis in gas-insulated switchgear (GIS), and the proposed diagnosis techniques used. This review focused on four research aspects on PD diagnosis related to the SF ₆ decomposition mechanism under PD activity, the developments in PD detection techniques, PD sources identification, and PD severity evaluation. Besides, the effect of various factors such as gas pressure, applied voltage, and impurities on the deterioration of the insulation gas and its influence on the diagnosis process has been reviewed. Currently, some reviews on PD diagnosis in SF ₆ -insulated switchgear have been presented and analysed; however, to date, most of them tend to focus on various PD detection techniques in GIS, while others are not extensive and comprehensive reviews. Unlike the available review publications, this paper highlighted various aspects of PD diagnosis in GIS and created a base for further development. The research trend in this field is expected to be directed toward a comprehensive assessment. This review provided a position of the current PD diagnosis in GIS studies and developments that can be a guideline for researchers for further research on the topic’s actual impact in the field.

On-Line Partial Discharge Localization in Power Cables Based on Electromagnetic Time Reversal Theory - Numerical Validation

Abstract: This paper presents the numerical validation of a new on-line location method of partial discharge (PD) in cables of Medium Voltage (MV) power networks based on the electromagnetic time reversal (EMTR) theory. Because PD events are a symptom of cable insulation degradation, PDs localization is a key topic for fault prevention on power networks, increasing their reliability and resilience and to guaranteeing electricity security. A description of the proposed EMTR PD location method is given and its effectiveness and accuracy are analyzed in lines with both homogeneous and inhomogeneous power cables. The accuracy of PD location methods is strongly affected by the distortion of the PD pulses during their propagation on power lines, caused mainly by the skin effect. For this reason, the accuracy of the proposed location method is analyzed using a lossy model of power networks that is able to reproduce PD signals distortion. The model used, realized using the transmission line matrix (TLM) method, is also presented here and theoretically validated.

Automatic PRPD Image Recognition of Multiple Simultaneous Partial Discharge Sources in On-Line Hydro-Generator Stator Bars

Abstract: In this study, a methodology for automatic recognition of multiple simultaneous types of partial discharges (PDs) in hydro-generator stator windings was proposed. All the seven PD sources typical in rotating machines were considered, and up to three simultaneous sources could be identified. The functionality of identifying samples with no valid PDs was also incorporated using a new technique. The data set was composed of phase-resolved partial discharge (PRPD) patterns obtained from on-line measurements of hydro-generators. From an input PRPD, noise and interference were removed with an improved version of an image-based denoising algorithm previously proposed by the authors. Then, a novel image-based algorithm that separates partially superposed PD clouds was proposed, by decomposing the input pattern into two sub-PRPDs containing discharges of different natures. From the sub-PRPDs, one extracts features quantifying the PD distribution over amplitudes and the contour of PD clouds. Those features are fed as inputs to several artificial neural networks (ANNs), each of which solves a part of the classification problem and acts as a block of a larger system. Once trained, ANNs work collaboratively to identify an unknown sample. Good results were obtained, with overall accuracies ranging from 88% to 94.8% for all the considered PD sources.

Voltage Equivalence of Partial Discharge Tests for XLPE Insulation Defects

Abstract: Partial discharge (PD) is an important factor leading to insulation deterioration and fault of power cables. Due to large cable capacitances, power supplies should provide high reactive charging currents during field tests; common PD test methods of power frequency (PF) voltage or alternating current resonance (ACR) voltage cannot meet the field test requirements with the increase of cable voltage levels and line lengths. At present, the equivalence between PF-like (PFL) voltages, such as damped alternating current (DAC) voltage, very low-frequency sine (VLF-Sine) wave voltage, or very low-frequency cosine rectangular (VLF-CR) wave voltage and PF is still unclear. In this article, four kinds of defect flat models of the needle tips, air gaps, metal particles, and moisture are made. The PD tests are carried out under different voltage waveforms [DAC, sine, and cosine rectangular (CR)] and frequencies (0.1–1000 Hz). The PD inception voltages (PDIV), phase-resolved PD (PRPD) spectra, and PD amplitudes of various defects are studied. The PDIV’s equivalent coefficient ${K}_{\text {PDIV}}$ , total discharge amplitude’s equivalent coefficient ${K}_{\textit {W}}$ , and PRPD’s statistical operators are proposed to characterize the PD equivalence between PFL and PF quantitatively. The results show that ${K}_{\text {PDIV}}$ , ${K}_{W}$ , and PRPD’s statistical operators can better evaluate the PD discovery abilities, PD severities, and PD-type recognition abilities of different voltage types. This study provides a technical basis for selecting the appropriate test voltage types and ensuring the test scientificity and reliability of cable PD tests in the field.