Study on Partial Discharge Characteristics During Electrical Tree Growth at XLPE-SIR Interface

The large number of high-frequency pulse voltages generated by the frequent switching of power electronic equipment is one of the important reasons for the generation of electrical trees in its insulation materials. The purpose of this paper is to study the initiation and growth characteristics of silicone rubber electrical trees under different rising edge pulse voltages, and to explain the mechanism of the above experimental phenomenon from the influence of pulse rising edge on space charge vibration. In this paper, based on the steptype accumulation method, a silicone rubber electrical tree aging experimental platform is designed. The three characteristics of fractal dimension, expansion coefficient and cumulative damage of electric tree image analysis and their implementation methods are proposed. By changing the time of the rising edge of pulse voltage, the influence of the rising edge of pulse on the emergence and development of electric trees in silicone rubber is discussed. According to the characteristics of the electric tree, the mechanism of space charge vibration induced by pulsed electric field is analyzed, and it is concluded that the pulsed electric field will cause space charge vibration, and space charge vibration will produce a series of high-energy reactions to produce energy trees. The phenomenon of space charge vibration will intensify with the decrease of pulse rise time, which provides a theoretical basis for reducing the electrical fault of power electronic devices.

Epoxy resin (EP) for current lead insulation in superconducting equipment offers advantages such as low costs, high chemical stability, and excellent electrical and insulation properties. However, during operation, the combined effects of complex voltage and a wide temperature range from room temperature to 77 K can easily induce partial discharge, leading to insulation faults and posing a threat to the safety and stability of the power system. In this work, we conducted electrical tree tests on bisphenol F EP to investigate the influence of environmental temperature, voltage forms, impulse frequency, and other factors on the inception and growth characteristics of electrical tree. The results indicate that low temperature can effectively inhibit the inception and growth of electrical tree in EP. Continuous dc voltage application affects traps, making superimposed voltage more likely to promote electrical tree growth than a single impulse voltage at 300 K. The impulse voltage component dominates in the superimposed voltage, and its polarity significantly affects electrical tree characteristics, though the mechanisms differ. Additionally, the form of voltage superposition influences electrical tree characteristics. The promotion effect of heteropolar superposition voltage on electrical tree is slightly lower than that of homopolar superposition voltage, but the influence is not as obvious as that of positive and negative polarity.

Optimal selection of features of Partial Discharge (PD) signals recorded from defects in High Voltage (HV) cables will contribute not only to the improvement of PD pattern recognition accuracy and efficiency but also to PD parameter visualization in HV cable condition monitoring and diagnostics. This paper presents a novel Random Forest (RF)-based feature-selection algorithm for PD pattern recognition of HV cables. The algorithm is applied to feature selection of both PD signals and interference signals with the aim of obtaining the optimal features for data processing. First, the experimental data acquisition and feature extraction processes are introduced. PD signals were captured from faults created in a cable to obtain the raw PD data, and then, a set of 3500 transient PD pulses and a set of 3500 typical interference pulses were extracted, based on which 34 PD features were extracted for further processing. Furthermore, 119 two-dimensional features and 1082 three-dimensional features were generated. The paper then discusses the basic principle of the RF algorithm. Finally, RF-based feature selection was implemented to determine the optimal features for PD pattern recognition. The results were obtained and evaluated with the Back Propagation Neural Network and Support Vector Machine. Results show that the proposed RF-based method is effective for PD feature selection of HV cables with the potential for application to additional HV power apparatus.

Barrier effect on electrical tree growth characteristics in silicone rubber

In this paper, room temperature vulcanized (RTV) silicone rubber (SiR) was employed as test sample to investigate the tree aging phenomena and mechanism of silicone rubber under commercial voltage. The structures and growth characteristics of electrical tree in SiR were observed by using a digital camera. A new parameter, the treeing proportion is introduced to describe the electrical tree propagation characteristics. Obtained results show that the tree channel of SiR composed of silicone compounds is non-conductive which is quite different from the conductive or semi-conductive carbonized channel within PE and XLPE. There are four kinds of electrical tree (few branch, branch, bush and mixed configurations) in RTV SiR under the commercial voltage, in which bush tree and branch tree take up a great proportion, and the probability of the appearance of bush tree increase with the applied voltage. In addition, three phases (initiation, rapid propagating and stagnation) of treeing propagation process are presented. The electrical tree propagates rapidly right after tree initiation, and the poor conductivity of electrical tree may have a great effect on the appearance of stagnation.

This study investigates the effect of barriers and interfaces on the lifetime of epoxy resin samples, as well as the growth characteristics of electrical trees. Four sample types are presented; all having been prepared in the point-plane configuration using a hypodermic needle as the HV electrode. Tests were carried out at 13 kV rms and sample images were taken at fixed one minute intervals during the test period. Results show that the incorporation of a barrier improves the time to breakdown of the epoxy resin tested. The inclusion of a major void defect did not accelerate failure of a sample which included an effective barrier.

The application of wide band-gap power electronic devices brings more challenges to insulating packaging technology. Knowing the influence of applied voltage parameters on insulation performance is helpful to evaluate the insulation condition of electric power equipment. In this paper, the effect of repetitive square wave voltage duty cycle on the growth characteristics of electrical trees in epoxy resin was studied. The experimental results show that the square wave voltage duty cycle has a significant influence on treeing features. The electrical tree proportion initiation has shown a decreasing trend, and the shape of the electrical tree changes from pine-like to branch-like by increasing the duty cycles. The length and damaged area of electrical tree increased with the increase in the duty cycle up to 10% and then decrease by increasing the duty cycle higher than 30%. It indicates that a low duty cycle will enhance the electron injection and accumulate space charges and thus accelerate electrical tree development. Under short duty cycles, the electric field due to the shielding effect near the needle tip suppresses the electrical tree growth, which results in treeing growth stagnation. The obtained results are helpful to keep these parameters in mind during the design of epoxy-based insulation such high-voltage rotating machines and power electronic device packaging.

Recent studies have shown that wavelet transform can effectively be used for noise reduction in the context of partial discharge (PD) signal detection and classification. Several thresholding approaches for wavelet denoising have been reported in the literature. In this study, a novel wavelet threshold estimation method, named energy conservation‐based thresholding (ECBT), is introduced. The proposed thresholding function is capable of conserving a significant portion of the original signal energy, while the threshold value is determined based on the relative difference between the original and noisy signal energies. The proposed method is first applied to PD signals contaminated with different levels of simulated noise. Results show that ECBT produces a denoised PD signal with higher signal‐to‐noise ratio (SNR) and less distortion than PDs produced by the existing wavelet methods. Then, ECBT is modified to address actual PD signals corrupted with real noise, where a robust SNR estimation method is derived to estimate the noise level embedded in the measured PD signals. The denoised PD signals indicate that the proposed method yields higher reduction in noise levels than other methods.

Today the sensitive measurement of partial discharge (PD) signals in XLPE cable can be an important element for quality assurance and diagnostics in the factory and during the on-site test procedure. The results clearly indicate that PD analysis of XLPE cable is an excellent online tool to assess its dielectric condition. However, as the serious interference in-field, the acquired PD signals may be interrupted by periodic interferences and white noises, easily. This paper describes an intelligent morphological filter algorithm to remove the periodic pulse interference and white noise contained in the PD signals. The algorithm consists of two stages of morphological processing. The performance of the algorithm is evaluated with simulated and real PD signals. Compared with classical wavelet, there are substantial improvements in the indexes of average error, root mean square (rms) error and maximum error, especially in reducing distortion of the baseline waveform.

In this article, the temperature of the needle tip and the ground electrode were changed to obtain different temperature gradients. The harmonic superimposed DC voltage was also simultaneously applied to study the electrical tree initiation, growth and breakdown characteristics in cross-linked polyethylene (XLPE) under the temperature gradient. The tree inception voltage, tree structure, tree length, accumulated damage (AD) and breakdown time were used to analyze the electrical tree degradation process. It was found that the greater the temperature gradient, the easier it is for electrical trees to be initialed which is related to the different charge behaviors affected by the trap distribution indicated by surface potential decay (SPD) results at different temperatures. With the temperature gradient increasing, the electrical tree length increases firstly but then decreases slightly when the temperature of the ground electrode is fixed, but the electrical tree length and AD increase linearly with the temperature gradient increasing when the temperature of the needle tip is fixed. The temperature rise of the ground electrode has a more serious impact on the safety of the insulation compared with the temperature rise of the needle tip. Positive DC bias voltage is more likely to cause damage and breakdown than negative DC bias voltage under the temperature gradient. These results indicate that the temperature gradient and harmonic superimposed DC voltage will promote the electrical growth in cable insulation, so special attention should be paid to the safety of electrical equipment under such special conditions.

Capacitor voltage transformers (CVTs) composed of aluminum foil/oil-impregnated paper insulation system have been operated over 30 years in substations. For the condition monitoring and diagnosis of aged CVTs, partial discharge (PD) detection is expected. However, PD characteristics from PD inception and progress to breakdown (BD) have not yet been clarified. Thus, PD characteristics of a fundamental insulation model composed of aluminum foil/oil-impregnated paper insulation systems are discussed in this paper. Experimental results under a fixed applied voltage revealed that PD characteristics can be classified into 3 periods. In Period 1, PD signals were intermittently generated mainly around the peak phase of applied voltage. In Period 2, PD signals were continuously generated around zero crossing (void discharge) to peak phase. In Period 3, PD signals larger than 10,000 pC were generated. Together with the above electrical PD measurement, the optical measurement of PD light emission images, bubble behavior, and their time transmission were also carried out in order to discuss the mechanism of PD progress.

Partial discharge (PD) signals generated by defects in a transformer insulation can be captured through measurement instruments and they may be used, after preprocessing, to discriminate the PD Sources. Some of the artificial defect models, such as: corona, internal cavity and surface discharge in air are developed in the laboratory. These defect models are put in parallel under a high voltage stress. The PD signals stemmed from these sets of multiple PD sources are captured. In this paper six bandpass Alters (with two MPD 600 devices) are used for feature extraction of these signals. For PD signals discrimination, the Density-Based Spatial Clustering of Applications with Noise density (DBSCAN) method is employed with two freedom parameters which resulted in an accurate discrimination of types of partial discharge sources.

Epoxy resin insulation materials are mainly derived from petrochemical materials which have the disadvantages of resource consumption and environmental pollution. In order to cure bisphenol A epoxy resin, a maleopimaric anhydride (MPA) curing agent was prepared from rosin, a renewable resource, and blended with a petroleum-based curing agent (methylhexahy-drophthalic anhydride). The influence of maleopimaric anhydride content on the initiation and growth characteristics of electrical trees was studied and analyzed in this paper using molecular dynamics simulation (MD) and electrical tree tests at an 18-kilovolt power frequency voltage. When the MPA content used was ≤10%, the free volume percentage of the curing system increased with MPA content, and thus the initiation voltage became lower; when the MPA content was ≥20%, the hydrogenated phenanthrene ring structure content increased significantly with increasing MPA content, and the rigidity of the curing system increased significantly; thus, the initiation voltage gradually increased. MPA4 had an 11.11% higher initiation voltage than the petroleum-based control group. The effect of the polar rigid structure within the curing system significantly inhibited the growth rate and length of electrical trees as MPA content increased. Electrical trees developed into light-colored, thin, and narrow dendritic structures when the MPA content reached 40%. The results show that curing epoxy resin with the rosin-based curing agent maleopimaric anhydride (MPA), in place of a petroleum-based curing agent, can produce environmentally friendly resins with excellent electrical tree resistance and potential application prospects.

Metal particles and bubbles are two typical impurities in transformer oil that can cause partial discharge (PD) and even electric breakdown. The PD characteristics are closely related to the motions of these impurities in flowing transformer oil. In this paper, the motions of impurities were obtained by a camera and a simulation model at first. Then, we employed three methods, namely, antennas, a non-inductive resistor, and the method recommended by IEC 60270, to measure the PD signals simultaneously. The breakdown experiments of transformer oil containing the metal particles and bubbles were also performed. In terms of these, single PD waveforms, statistical characteristics, and breakdown voltage were obtained. The results showed that the metal particles could excite ultrahigh frequency (300 MHz-3 GHz) PD signals, whereas bubbles only excited signals in the very high-frequency band (30-300 MHz). Moreover, the PDs induced by the metal particles had a higher repetition rate and a smaller amplitude than the PDs induced by bubbles. In addition, the metal particles easily caused PD, whereas bubbles easily led to the breakdown. Possible reasons for different discharge characteristics between the two impurities were discussed on the basis of the motions of impurities and the distortions of electric field.

In on-line PD measurement, de-noising Partial Discharge (PD) signal from noisy environment with acceptable performance indices and also with minimum time cost is a major challenge. In this paper a new approach based on wavelet thresholding is proposed for de-noising on-line PD signal. This method first applied on two different type PD signals with White Gaussian Noise (WGN) and simulation results shows that new threshold function give better performance with less computing time as compare to other existing de-noising technique. Finally, a field detected signal is tested and the de-noised signal indicates that method is effective and efficient for this application also.