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Acoustic inspection is a valuable technique that can detect early stage defects in equipment, thereby facilitating predictive maintenance. In recent times, ultrasonic sensors have made detecting partial discharges through acoustic sensing increasingly feasible. However, interpreting the acoustic signals can pose challenges, as it requires extensive expertise and knowledge of equipment configuration. To address this issue, a technique based on zero-crossing rate and fundamental frequency estimation has been proposed to standardize insulator diagnosis. In an experiment involving a database of 72 raw acoustic signals with frequencies ranging from 0 to 128 kHz, various types of pollution and defects were introduced to a chain of insulators. By employing the proposed technique, the occurrence of partial discharges can be detected and classified according to type, such as corona or surface discharges. This advanced approach to diagnosis simplifies the process while providing valuable insights into the severity of observed phenomena in the field.

Railway system insulators are affected by pollution, altitude, and other environmental situations during operation, which causes reduced electrical performance or even flashover accidents. These factors threaten the safety of railway operations in high-altitude areas. However, the natural contamination characteristics of a railroad in a plateau area is still unclear. In this study, a natural pollution accumulation test for railway insulators in a high-altitude area was carried out, and the distribution rules of nonsoluble deposit density (NSDD), equivalent salt deposit density (ESDD), NSDD/ESDD ratio, and nonuniformity (T/B) of the pollution distribution of the tested insulators were calculated. Meanwhile, the chemical compositions of the pollution from different test sites were analyzed. The differences of pollution accumulation between railway insulators and suspended insulators of a power system and the influencing factors were compared and analyzed by combining with a numerical simulation. The results show that the pollution level of railroad insulators is mainly distributed in level b and above. A pollution sample is mainly composed of sodium chloride, while the NSDD/ESDD ratio of pollution is mostly distributed from 0 to 5, with T/B value ranges from 1/0.62 to 1/1.76. The amount of insulator contamination is influenced by the location inside and outside the tunnel. Additionally, the pollution amount is influenced by the structure and type of insulators. Finally, this paper studies the creepage distance and structural height required by railway insulators in a plateau area according to the natural pollution accumulation characteristics of railway insulators, which can provide a reference for a railway electrical external insulation configuration in a high-altitude area.

At this stage, the inspection of transmission lines is dominated by UAV inspection. Insulators, as essential equipment for transmission line equipment, are susceptible to various factors during UAV detection, and their detection results often lead to leakages and false detection. Combining deep learning detection algorithms with the UAV transmission line inspection system can effectively solve the current sensing problem. To improve the recognition accuracy of insulator detection, the MS-COCO pre-training strategy that combines the FPN module with a cascading R-CNN algorithm based on the ResNeXt-101 network is proposed. The purpose of this paper is to systematically and comprehensively analyze mainstream isolator detection algorithms at the current stage and to verify the effectiveness of the improved Cascade R-CNN X101 model by combining the mAP (mean Average Precision) value and other related evaluation indices. Compared with Faster R-CNN, Retina Net, and other detection algorithms, the model is highly accurate and can effectively deal with the false detection, leakage, and non-recognition of the environment in online special detection. The research in this paper provides a new idea for intelligent fault detection of transmission line insulators and has some reference value for engineering applications.

For high electron mobility transistors (HEMTs) power transistors based on AlGaN/GaN heterojunction, p-GaN gate has been the gate topology commonly used to deplete the two dimensional electron gas (2-DEG) and achieve a normally-OFF behavior. But fully recessed MIS gate GaN power transistors or MOSc-HEMTs have gained interest as normally-OFF HEMTs thanks to the wider voltage swing and reduced gate leakage current when compared to p-GaN gate HEMTs. However the mandatory AlGaN barrier etching to deplete the 2-DEG combined with the nature of the dielectric/GaN interface generates etching-related defects, traps, and roughness. As a consequence, the threshold voltage (VTH) can be unstable, and the electron mobility is reduced, which presents a challenge for the integration of a fully recessed MIS gate. Recent developments have been studied to solve this challenge. In this paper, we discuss developments in gate recess with low impact etching and atomic layer etching (ALE) alongside surface treatments such as wet cleaning, thermal or plasma treatment, all in the scope of having a surface close to pristine. Finally, different interfacial layers, such as AlN, and alternative dielectrics investigated to optimize the dielectric/GaN interface are presented.

For the benefit of knowing the method of insulator deicing using hot water, this paper investigated the physical aspects of propagation and the spatial temperature distribution of a hot water jet in the air. The numerical calculation model for the water jet flow field was established and validated, and the temperature spatial variation rule and influencing factors of the water jet were analyzed. The results indicate that the water column breaks as the distance increases. The numerical calculation results and the experimental results of the water jet flow field were approximated. As the distance increases, the mass entrainment rate of the water jet gradually increases, and the normalized axis velocity decreases approximately linearly. The jet temperature rises with the rise in the initial temperature of the hot water, and the rising rate decreases with the increase in distance. The temperature of the water jet falls as the jet distance increases. With the rise in the outlet pressure, the temperature of the water jet drops slightly. The influence of environmental wind speed on the water jet temperature is more significant than ambient temperature—the water jet temperature increases as the nozzle diameter increases. The thorough deicing efficiency is most outstanding when the hot water output temperature is around 86 °C and the jet pressure is ~3.5 MPa.

Successive flashover would result in carbonized tracking on insulator surface and cause deterioration to the insulation. Thus, investigation of the tracking can be beneficial in understanding flashover characteristics during long-term operation. In this paper, DC flashover was operated on the insulator, and the image of tracking after successive discharge were captured. Improved differential box-counting method (IDBM) was applied to analyze these images based on fractal theory. Weighted item was suggested during the counting procedure for rectangle image with margin covered by cut-size box. Fractal dimension of the tracking was calculated according to the suggested method. It is claimed that the suggested method could estimate the discharge propagation property and deterioration characteristics on the insulator surface. Moreover, IDBM showed advantages in image pre-processing and deterioration property revealed compared to traditional box-counting method attributing to the consideration of color depth. This image analysis method shows universality in dealing with tracking image and could provide additional information to flashover voltage. This paper suggested a potential approach for the investigation of discharge mechanism and corresponding deterioration in future research.

Among the main causes of outdoor insulation failures is their poor specifications in terms of leakage distances. This happens when the selected criteria are unable to cope with all the stresses imposed by the changes in environmental pollutions. Therefore, it is important for utilities to fully understand the actual pollution characteristics of the service environment in which the insulators are operating. In this paper, the pollution severity and performance of some 13.2 kV ceramic insulators, sampled in different areas of a Canadian aluminum factory, are assessed. The investigations were performed taking into account the influence of air humidity. Various characteristics were investigated to assess the pollution levels of the insulators, such as equivalent salt deposit density (ESDD) and non-soluble deposit density (NSDD), surface resistance, and leakage current characteristics (density, 3rd harmonic amplitude, and phase). It was witnessed that the insulators, collected around the factory, were much more polluted in comparison to the initial expectation. The pollution level should not be considered static due to the environmental parameters’ dynamics. Lessons to learn: the reliability of an electrical grid is dependent on components whose own reliability is strongly affected by external factors, of which there is often a poor awareness. If care is not taken to re-evaluate the post-installation pollution levels of the insulators, the light may simply turn out!

Predicting the electrical breakdown of polymers is critical for certifying the endurance and lifetime of high voltage power equipment. Since various factors contribute nonlinearly to the breakdown phenomena of polymer insulators, it is difficult to assess the impact of each factor independently. In this study, we numerically analyzed the breakdown phenomenon because of the ramp rate of the DC voltage applied to a polymer insulator, low-density polyethylene (LDPE), using the finite element method (FEM). To predict the breakdown initiation, we analyzed the relaxation time of the conduction current through the insulator as a significant indicator. The bipolar charge transport (BCT) model was used to analyze the charge behavior within the LDPE, and the breakdown voltage was predicted by incorporating the molecular displacement model. This analysis was conducted for a wide range of ramp rates from 10 to 1500 V/s. The current density was calculated using two different methods, namely the energy and average methods, and the results were compared with each other. The results of the numerical model were further verified by comparing with those from experiments reported in the literature.

The detection of insulators in power transmission and transformation inspection images is the basis for insulator state detection and fault diagnosis in thereafter. Aiming at the detection of insulators with different aspect ratios and scales and ones with mutual occlusion, a method of insulator inspection image based on the improved faster region-convolutional neural network (R-CNN) is put forward in this paper. By constructing a power transmission and transformation insulation equipment detection dataset and fine-tuning the faster R-CNN model, the anchor generation method and non-maximum suppression (NMS) in the region proposal network (RPN) of the faster R-CNN model were improved, thus realizing a better detection of insulators. The experimental results show that the average precision (AP) value of the faster R-CNN model was increased to 0.818 with the improved anchor generation method under the VGG-16 Net. In addition, the detection effect of different aspect ratios and different scales of insulators in the inspection images was improved significantly, and the occlusion of insulators could be effectively distinguished and detected using the improved NMS.

In this paper, an artificial pollution test is carried out to study the leakage current of porcelain insulators. Fractal theory is adopted to extract the characteristics hidden in leakage current waveforms. Fractal dimensions of the leakage current for the security, forecast and danger zones are analyzed under four types of degrees of contamination. The mean value and the standard deviation of the fractal dimension in the forecast zone are calculated to characterize the differences. The analysis reveals large differences in the fractal dimension of leakage current under different contamination discharge stages and degrees. The experimental and calculation results suggest that the fractal dimension of a leakage current waveform can be used as a new indicator of the discharge process and contamination degree of insulators. The results provide new methods and valid indicators for forecasting contamination flashovers.

Due to the complex structure of insulators, it is difficult to use parameters such as icicle length or ice thickness of an insulator to directly characterize the degree of icing of an insulator. Rotating conductors are widely used in monitoring icing degree on insulators, but the relationship between ice degree on the insulator and the rotating conductor has not been verified. In this paper, the water droplets collision coefficient α1 was put forward to characterize icing degree, and a new numerical calculation model where α1 on different regions of an insulator is calculated was proposed. Combining the freezing fraction α3 of the insulator and rotating conductor, the equivalent relationship of ice weight between insulator and rotating conductor can be established, which was afterwards verified through the icing tests. The test results indicate that ice weight on an insulator increases linearly with the increase of ice weight on the rotating conductor, and the model proposed in this paper can reflect actual results more accurately than previous models. In such cases, the method of using ice weight on a rotating conductor to predict that on an insulator based on the model proposed in this paper could be widely adopted.

Icing can adversely influence electric power system security. Two main issues are caused by icing: the overload of transmission lines, and the reduction in the insulation ability of the insulators. Most previous research has focused on the flashover characteristics of ice-covered insulators, but research on the icing process of the insulator is seriously lacking. Considering the effect of icing shape, the outer airflow field of an insulator was calculated and the local collision efficiencies of water droplets (β1) were investigated according to the Lagrange algorithm. The simulation showed that the values of β1 on the insulator edge and rod are much higher than on the insulator surface, and both were significantly influenced by the wind speed and median volume diameter (MVD) of the water droplets. Based on thermal balance equations, a dynamic dry-growth icing model was established. Using the natural icing conditions of Xuefeng Mountain (China) as an example, validation experiments were conducted on a composite insulator and the climate parameters measured by multi-cylinders were used to model the icing shape and mass. The results indicate that high wind speed and low temperature increase icing rate; the icing was mainly concentrated on the windward side and the greatest horizontal thickness was generally on the insulator edge. The dry-growth model had an average error lower than 25% for icing thickness and an average error lower than 20% for icing mass, which were affected by icing roughness.

Energized insulator’s surface contamination is greatly affected by its electric field properties. However, few reports about the electric field influencing mechanism on the pollution deposition have been presented. In this paper, the coupling-physics model of a three-unit XP-160 insulator string was established, and the particles’ deposition process was simulated by using the finite element method. The effects of the electric field on the pollution particles’ motion were analyzed. Research results indicate that the closer to the insulator string, the larger the intersection angle θ between the electric force and its horizontal component. The main function of the electric field on insulator contamination is that it changes the pollution particles’ vertical moving speed, thus accelerating the particles’ deposition process. The particle capture coefficient ratio ck can be used to reflect the pollution degree discrepancy between DC-energized and non-energized insulators. In this paper the ratio ck of the DC-energized to non-energized condition is in the range of 1.04 to 1.98, very close to the field measurement results of the DC pollution ratio k.

Accurate and timely detection of insulator flashover on power transmission lines is of paramount importance to power utilities. Most available solutions mainly focus on the exploitation of the flashover mechanism or the discharge area detection, rather than the identification of a damaged area due to flashovers using captured aerial images. To this end, this paper proposes a multi-saliency aggregation-based porcelain insulator flashover fault detection approach. The target area of the insulator is determined using the Faster-Pixelwise Image Saliency by Aggregating (F-PISA) algorithm based on the color and structural features. The color model can be established based on the color feature of the damaged areas on the insulator surface, and hence the damaged area can be identified. Based on the information obtained above, the contour information can be extracted. With the preceding process, the fault location can be confirmed with a good accuracy. The performance of the proposed detection approach is assessed through a comparative study with other available solutions. The numerical result demonstrates that the suggested solution can detect the insulator flashover with improved performance in terms of the average detection rate and average efficient detection rate. Additional analysis is carried out to evaluate its robustness and real-time performance, which confirms its deployment feasibility in practice.

The cleaning effect of heavy rain (the rainfall reaches 5 mm every day) on surface contamination of insulators is more effective than dew, fog, mist, and other light rain conditions which can initiate leakage currents and increase the likelihood of flashover. It is well understood that heavy rain can wash away contamination from the surface of high voltage (HV) insulators and thereby reduce the risk of pollution flashover. This study examines the cleaning effect of natural wetting conditions on HV insulators on four 500 kV transmission lines in Hunan Province, China. Historical meteorological data, monthly equivalent salt deposit density (ESDD) and non-soluble deposit density (NSDD) measurements taken over a period of five years were analyzed to investigate the relationship between rainfall intensity and insulator cleaning. The measured data show that the ESDD/NSDD changes with the seasonal variation, which accumulates in dry season (January–April, about 117–122 days) and is washed off in the wet season (June–October, about 118–127 days). According to the measured data, the ESDD and NSDD on the surface of insulators were affected by the rainfall intensity (in the dry season it is about 1 mm/day and in the wet season it is about 5 mm/day). Based on a comparison of the four study sites, we propose a mathematical model to show the functional relationship between rainfall intensity and insulator self-cleaning capability. The mathematical model’s coefficient of determination (R2) is greater than 0.9 and the effective rate of self-cleaning capability reaches 80%.

Ice flashover threatens the security and reliability of power transmission. However, the ice flashover mechanism of insulators remains poorly understood. This study analyses water droplet freezing and ion distribution in ice layer under alternating electric field. It also investigates ion migration during icing process of insulator string under alternating electric field and its effects on insulator flashover. Results showed that the average freezing time of water droplets was related to electric field strength. The extent of ion migration during freezing decreased with increasing electric field strength. The maximal melting water conductivity of the ice layer and icicle of the insulator formed under energized condition was higher than the corresponding freezing water conductivity but lower than that under non-energized condition. Furthermore, the hanging location of each insulator significantly affected the melting water conductivity of the ice layer. The surface conductivity of the ice layer increased because of the conductive ion migration in freezing water during freezing, which was an important factor that decreased the flashover voltage of the ice-covered insulator. The existence of alternating electric field would impact the extent of ion migration. This study may serve as a reference for updating prediction flashover model of ice-covered insulators during the melting period.

Natural polluted insulator surfaces are always coated with various kinds of soluble constituents, and those constituents affect flashover performance differentially. Currently, this fact is not considered either in laboratory experiments or field pollution degree measurements, causing the existing insulation selection method to be deficient. In this paper, a systematic study on insulator flashover voltage gradient correction involving different types of soluble pollution constituents is presented. Using a typical type glass insulator as the sample, its flashover tests, polluted by typical soluble chemicals (NaCl, NaNO3, KNO3, NH4NO3, MgSO4, Ca(NO3)2 and CaSO4), were carried out. Then, the flashover gradient correction was made by combining the flashover performance of each soluble constituent, the equivalent salt deposit density (ESDD) contribution of the seven constituents, and the saturation performance of CaSO4. The correction agreed with the flashover test results of insulator polluted by three types of soluble mixture. Research results indicate that the flashover gradient correction method proposed in this paper performs well in reducing the calculating error. It is recommended to carry out component measurements and flashover gradient correction to better select outdoor insulation configuration.