Partial Discharge Characteristics Research Articles

Partial discharge characteristics of peek utilized in press-pack IGBT under DC voltage

Partial discharge characteristics of peek utilized in press-pack IGBT under DC voltage

Nanosecond Partial Discharge Current Waveforms with Polyethylene Naphthalate Films on IEC(b) Electrode

The polyethylene naphthalate (PEN) film has been widely applied as a heat‐resistant thin insulation film and sensor film. For the safe and long application of the film in various products, one significant characteristic is the partial discharge (PD) resistivity. In this study, a well‐known IEC(b) electrode is used to measure PD characteristics such as the maximum partial discharge, qmax and fast PD current waveforms at AC peak voltages of 1–3 kVp and 50–1000 Hz over PEN films with thicknesses of 75, 50, or 25 μm. All experiments are conducted at room temperature of ~20 °C. The positive PD current is defined as the current flowing from a high‐voltage electrode to a ground electrode. The positive and negative qmax increased rapidly with the applied voltage increase but remained almost the same for the applied voltage frequency changes. The PD current duration time was less than 40 ns for the positive current and 30 ns for the negative current at all voltages, frequencies, and film thicknesses. It was deduced that the positive current peak magnitude was approximately twice of the negative one at all applied voltages, frequencies, and film thicknesses. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Investigation of Partial Discharge Characteristics inside Vacuum Interrupter with Various Floating Shield Potentials

The reliable operation of vacuum circuit breakers (VCBs) plays an important role in the power system's reliability. The common cases which lead to the failure in the VCB are related to the loss of vacuum inside the vacuum interrupters (VIs). VIs commonly loses the vacuum with a higher leakage rate, resulting in a decrease in discharge voltage and partial discharge (PD) inside the VI which can lead to the eventual failure of the VCBs. Detecting vacuum leakage at the early stage became an important issue. In the prior study, vacuum failure was studied by detecting PD characteristics inside the VIs by regulating the different internal pressures. This study introduces a novel approach to investigating vacuum leakage within the VIs by detecting PD characteristics under various floating shield potentials to study the possibility of shield potential control on PD measurement. Comparing the experimental results measured at different internal pressures under various shield potentials, this study highlights the measurement of PD characteristics and the possibility of shield potential control on PD measurement. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

A Study on Simultaneous Measurement of Partial Discharge in Epoxy Resin Insulator using IMC and Rogowski Coil

In practice, field measurement of partial discharge is easily suffered by interferences due to the noisy signal has been mixed with the resulting partial discharge signal. Therefore, the detection and measurement of PD are important to monitor the insulation life in high voltage (HV) power equipment. The paper presents the simultaneous measurement of partial discharge (PD) pulse parameters using the impedance matching circuit and the Rogowski coil sensor to study the features of partial discharge on the epoxy resin insulator. Two different thicknesses of samples were used to observe the PD pulse parameters with the voltage applied vary depending on the thickness of the sample to attain constant electric field intensity for both samples. The step response parameters resulted from the measurement can be used as a time domain features to discriminate various types of PD in HV power equipment. Thus, the PD can be observed clearly, maintenance can be performed, and the performance of the power system can be improved.

A study on the effect of temperature rise on the effectiveness of detecting typical defects in rubber-impregnated paper sleeves

Epoxy rubber-impregnated paper casing has the advantages of stable electrical performance, explosion-proof function, small volume, lightweight, etc., and has been widely used in transformer casing and through-wall casing. However, its manufacturing process is complex, which makes it easy to produce defects in the production process, and it is difficult to detect certain defects in the test at room temperature. To study the partial discharge and dielectric loss characteristics of typical defects of rubber-impregnated paper bushings after temperature rise, we designed and prepared defective bushings with moisture, metal particles, and core cracks, and measured the partial discharge pattern and dielectric loss factor of the bushings after they were heated to a certain temperature. The results show that the core crack defective casing discharge increases more after heating, followed by moisture defective casing, and metal particles defective casing has the smallest impact, indicating that for the temperature rise test in the thermal state of the core crack, moisture defective casing detection effect is better. The results of the study can provide certain references and guidance for the factory inspection and troubleshooting of rubber-impregnated paper casing.

Ultrasonic propagation characteristics of partial discharge in oil-impregnated paper traction transformer

Partial Discharges (PDs) are a significant factor in reducing the insulation life of traction transformers. In recent years, the Acoustic Emission (AE) method has become the most advanced method for detecting PD signals in transformers. The AE method utilizes AE sensors placed on the transformer tank to detect ultrasonic signals emitted by PD and determine the Time Of Arrival (TOA) of the head wave. The windings and cores of a traction transformer consist mainly of metal, which greatly affects the propagation of PD ultrasonic waves. This paper establishes a 110 kV “pressure acoustic, transient” physical field model of the traction transformer with dimensions of 4.63 × 1.48 × 2.84 m3. The model is used to carry out the PD pressure acoustic physical field simulation study of the traction transformer, to clarify the physical characteristics of the ultrasound of the PD defects, and to establish observation points on the transformer tanks to receive ultrasonic time-domain waveforms for PD detection. The simulation results indicate that PD ultrasonic waves exhibit complex propagation characteristics, including reflection, refraction, and reverberation, as they pass through the windings and cores to the observation points. The TOA of the head wave in the ultrasound time-domain waveform is indicated by the first maximum value of the wave crest line. Finally, this paper proposes a multi-level localization method based on the AE method to determine which winding generates the PD in the large-scale traction transformer using only four dynamically moving observation points.

A method for testing partial discharge characteristics of switch cabinet based on improved particle swarm algorithm

In the current operational environment of the switch cabinet, the presence of mixed-frequency signals poses interference from white noise to partial discharge detection, resulting in suboptimal detection efficiency and accuracy. Therefore, this study explores a method for testing the partial discharge characteristics of switch cabinets based on an improved particle swarm algorithm. This novel approach involves signal processing of partial discharge in a switch cabinet, feature extraction based on the particle swarm algorithm, and feature output for partial discharge detection. Experimental comparisons demonstrate that the new detection method significantly enhances detection efficiency and ensures the accuracy of results, meeting the operational requirements of substations.

Partial discharge behaviour analysis of silicon nitride ceramics

Silicon nitride ceramic, one of the most promising power electronics carrier board materials, is examined non-destructively by means of partial discharge measurement. A variety of sample-electrode combinations is evaluated regarding inferences about characterization of the ceramics as well as the field application of power electronics carrier boards. It is shown that electrode type, substrate thickness and supplier-specific ceramic materials in combination with the manufacturing process influence the partial discharge occurrence characteristics. In contrast to the literature, partial discharges within the ceramic are not excluded, while a metallization-free characterization option is demonstrated by aggregating measurements with different electrode geometries. Finally, an overview of the partial discharge characteristics of active metal brazing-metallized silicon nitride ceramics is presented.

WITHDRAWN: Design of partial discharge measurement model for internal cavities in high voltage power cables

The phenomenon of partial discharge (PD) in power cables can result in insulation degradation and eventual failure if left undetected and unaddressed. As a result, the measurement of PD is key to evaluating the performance of insulation diagnostics in the power cables. This paper presents a PD measurement model for internal cavities in XLPE insulating material for medium voltage power cables. The proposed PD measurement model is designed using the COMSOL Multiphysics software as a finite element analysis (FEA) tool added to MATLAB environment, specifically tailored for power cables. The proposed PD measurement model uses the multiphysics capabilities of COMSOL to simulate the electrical discharges behavior within power cables. The model considers factors such as cable geometry, material properties, cavity size, applied voltage and numerical conditions to accurately capture the PD characteristics. Distributions of both electric potential and electric field were studied before and after occurrence of PD across the internal cavity. According to the results, it has been noticed that the discharge magnitude mainly depends on the cavity diameter; as increasing cavity diameter leads to increasing the magnitude of the measured PD. Moreover, the leakage current magnitude is recorded during the PD event period. The proposed model also enables the evaluation of different cable designs, insulation materials, and operating conditions to optimize cable performance and mitigate PD risks.

Research on a Partial Discharge Expert System for the Diagnosis of Damaged Transformation Equipment

Partial discharge (PD) characteristics are very important for the diagnosis of damaged transformation equipment. If the power transmission and transformation equipment fails, it will cause large economic losses, and thus prevention is better than treatment. One of the effective methods for high-voltage insulation degradation detection is to observe the phenomenon of partial discharge of equipment, which is the earliest characteristic. Prevention can be carried out in advance, and trend observation is better than periodic inspection. Long-term observation can effectively reduce the probability of misjudgment. This project intends to develop a high-speed data-acquisition device to acquire the original discharge waveform data of partial discharge for noise suppression. In order to improve the diagnostic efficiency and accuracy of the diagnostic system, it is necessary to suppress the noise of the measurement data, so as to carry out the fault identification of the discharge type. Through this method, the actual operating data of the system can be recorded as the original discharge waveform, in order to understand the original discharge waveform conditions of the power transmission and transformation equipment in multiple partial discharge measurements, and then after noise suppression, it can be regarded as a type of partial discharge identification.

Analysis of electric field and partial discharge characteristics of cable joint stress cone dislocation defects

AbstractThe mechanisms governing electric field and partial discharge (PD) under stress cone dislocation remain unclear. This study employs the finite element method to explore the relationship between the electric field, externally applied voltage, and length of dislocation. Subsequently, the correlation between voltage and electric field is determined. The relationship between voltage and PD is established through PD tests conducted under stress cone dislocation conditions. By considering the influence of voltage, the association between the electric field and PD is established, revealing the mechanism of PD initiation by electric field distortion in joints. The findings suggest that the lifetime and reliability were increased by wrapping semi‐conductive self‐adhesive tape around the exposed cross‐linked polyethylene (XLPE) insulation layer. The electric field at a specific location is approximately proportional to the applied voltage. However, the slope is influenced by the composite insulation interface and the radial distance of the copper conductor. When crossing the interface between the XLPE insulation layer and the accessory insulation layer, the slope decreases significantly. The threshold for electric field PD is determined by examining the electric field distribution and the PD inception voltage during testing. When the voltage is sufficiently high, significant electric field distortions can occur at multiple points in the joint, potentially leading to concurrent PDs at several locations.

Partial discharge pattern recognition algorithm of overhead covered conductors based on feature optimization and bidirectional LSTM‐GRU

AbstractRecognition of partial discharge (PD) patterns is essential for insulation diagnosis of covered conductors in overhead lines. Current research has not sufficiently addressed the complex background noise in real environments, and most detection methods depend primarily on feature engineering or deep learning, suggesting potential for improvement in accuracy and efficiency. This has led the authors to propose a PD pattern recognition algorithm that integrates feature selection and deep learning. This algorithm incorporates the design of a discrete wavelet denoising function specifically tailored to the characteristics of PD for data preprocessing. It employs Bayesian optimization algorithms and light gradient boosting machines for characterizing corona discharge features. Furthermore, it develops multi‐scale clustering features and phase‐resolved features for feature fusion, and constructs insightful features based on the light gradient boosting machine. Finally, a novel deep learning model is formulated, demonstrating exceptional detection performance for early faults in covered conductors. Experimental results show that this algorithm attains an Matthews correlation coefficient score of 0.814, a 13.2% improvement over the baseline algorithm's 0.719, and a speed increase of 39.18%. The final accuracy amounts to 97.85%. This algorithm demonstrates exceptional performance in detecting early insulation faults in conductors.

Investigation of partial discharge characteristics in XLPE cable insulation under increasing electrical stress

Insulation degradation in power components is a looming issue that can have a significant impact on the reliability of power system if not attended timely. Partial discharge (PD) diagnostics is a key technique used for the condition monitoring and health assessment of insulation. Inception of PD is a primary indicator which shows degradation and decreased local dielectric strength of the insulation. PD magnitude can increase with time and level of stress, which may result in failure of insulation. This article investigates the behavior of PD characteristics in a medium voltage (MV) cross-linked polyethylene (XLPE) cable sample, containing a defect at the cable termination, under elevated electrical stresses. PD behavior is studied by investigating the key PD characteristics, such as partial discharge inception voltage (PDIV), phase of occurrence (ɸ), mean amplitude (Vmean), pulse repetition rate (PRR), and phase span (ɸspan). These quantities are extracted from a phase-resolved partial discharge (PRPD) pattern using a pulse detection algorithm. Later, these characteristics are analyzed in correlation with the electrical stress. Various regression models are implemented and compared to find the best fit model that represents trending attributes of major PD characteristics. The presented study can be used as an effective process to analyze the measured PD data for evaluation of the insulation condition in the power components.

Multi-source partial discharge pattern recognition algorithm based on DCGAN-Yolov5

This study aims to overcome the complication that deep learning-based pattern recognition in partial discharge (PD) diagnosis of gas-insulated switchgear (GIS) can only identify single-source partial discharge but not multi-source partial discharge. Specifically, a GIS multi-source partial discharge detection algorithm based on Deep Convolution Generative Adversarial Networks and You Only Look Once (DCGAN-YOLOv5) is proposed. First, the Phase Resolved Partial Discharge (PRPD) features of multi-source PD are analyzed, a GIS experiment platform is established, and four typical PD defects are simulated. Besides, sample data are collected, and the DCGAN network is used for sample expansion. Then, a YOLOv5 network model is designed, and a spatial and channel attention mechanism is added to the feature extraction network with a positive sample equilibrium strategy. Finally, the effectiveness of the proposed algorithm is verified using laboratory data and field data collected from a 220 kV substation. The experimental results demonstrate that the proposed algorithm can effectively detect the multi-source PD features in PRPD patterns under complex noise and thus successfully identify the types of multi-source PD. The mean Average Precision (mAP) can reach 98.4%. The precision of single-source PD and multi-source PD can reach 95.2% and 89.3%, when testing with field data.

Gas Production Characteristics of Partial Discharge in Needle-plate Electrodes under Typical Vibration Conditions in a UHV Shunt Reactor

Gas Production Characteristics of Partial Discharge in Needle-plate Electrodes under Typical Vibration Conditions in a UHV Shunt Reactor

Partial discharge characteristics of epoxy insulation surface under AC/LI superimposed voltages in SF6/N2 gas mixtures

Partial discharge characteristics of epoxy insulation surface under AC/LI superimposed voltages in SF₆/N₂ gas mixtures

Effect of Temperature on Partial Discharge Characteristics of BOPP Film Under Nanosecond Pulse Voltage

Effect of Temperature on Partial Discharge Characteristics of BOPP Film Under Nanosecond Pulse Voltage

Dynamic Partial Discharge Characteristics of Generator Stator Bar With Four Typical Defects

Dynamic Partial Discharge Characteristics of Generator Stator Bar With Four Typical Defects

Research on Transformer Omnidirectional Partial Discharge Ultrasound Sensing Method Combining F-P Cavity and FBG.

To achieve omnidirectional sensitive detection of partial discharge (PD) in transformers and to avoid missing PD signals, a fiber optic omnidirectional sensing method for PD in transformers combined with the fiber Bragg grating (FBG) and Fabry-Perot (F-P) cavity is proposed. The fiber optic omnidirectional sensor for PD as a triangular prism was developed. The hollow structure of the probe was used to insert a single-mode fiber to form an F-P cavity. In addition, the three sides of the probe were used to form a diaphragm-type FBG sensing structure. The ultrasound sensitization diaphragm was designed based on the frequency characteristics of PD in the transformer and the vibration model of the diaphragm in the liquid environment. The fiber optic sensing system for PD was built and the performance test was conducted. The results show that the resonant frequency of the FBG acoustic diaphragm is around 20 kHz and that of the F-P cavity acoustic diaphragm is 94 kHz. The sensitivity of the developed fiber optic sensor is higher than that of the piezoelectric transducer (PZT). The lower limit of PD detection is 68.72 pC for the FBG sensing part and 47.97 pC for the F-P cavity sensing part. The directional testing of the sensor and its testing within a transformer simulation model indicate that the proposed sensor achieves higher detection sensitivity of PD in all directions. The omnidirectional partial discharge ultrasound sensing method proposed in this paper is expected to reduce the missed detection rate of PD.

Nanosize Filler Effect on Propagation of Electron Avalanche in Terms of Waveform Characteristics of Partial Discharge

Nanocomposite materials have excellent insulating properties, such as improved treeing resistance. The propagation properties of electrical trees are often determined using optical observations and partial discharge (PD) characteristics regarding phase angle distribution patterns. There is a limit to confirming the effects of physical barriers on the PD by optical observation alone. Conversely, there is a high possibility that the PD waveform reflects the characteristics of the electron avalanche in the discharge space. In this study, we constructed a PD measurement system with the widest possible frequency range and acquired 1000 PD waveforms along the time series. Although the acquired waveforms have a single peak or multiple peaks, adding nano-fillers increased the observation ratio of the waveform with multiple peaks. Furthermore, the multiple peaks suggested that the electron avalanche progresses with difficulty considering that the nano-fillers easily captures electrons. We investigated the effect of adding nano-fillers from the viewpoint of the waveform characteristics. The time difference between the peaks and the peak ratio is also supported by the property changes in the electron avalanche because of the electron capture by nano-fillers.