Insulation Failure Research Articles

Effect of thermal shock on energy density of biaxially oriented polypropylene films for pulsed power capacitors

In this paper, thermal shock experiments are performed on the biaxially oriented polypropylene (BOPP) films, and the changes in dielectric and energy storage properties before and after the experiments are explored. The experimental results show that the films have reduced comprehensive performance with the thermal shock time and frequency increasing. After the thermal shock, both the permittivity and the dielectric loss increase slightly. And, the direct current (DC) conductivity has risen by 73.6%–714.2%. The lowest DC breakdown strength of film is 604.4 kV mm−1, showing a 13.5% reduction compared to that of pristine film. In addition, energy storage performance has also deteriorated. The maximum discharge energy density decreased from 4.62 J cm−3 of pristine film to 3.26 J cm−3 of treated film. There is a decrease in charge and discharge efficiency under the same electric field. The metallization layer of the film receives less influence; the capacitance is reduced by only 0.37%. The causes and mechanisms of performance changes are analyzed and discussed. The disruption of molecular chains during thermal shock is the most important factor leading to the degradation of films. This paper provides a powerful perspective and reference for studying the performance degradation and failure of polymer dielectrics under extreme operating conditions.

Research on Ultra-Fast Transient Overvoltage Characteristics of Electric Locomotive

Operating overvoltage occurs when the pantograph or main breaker of an electric locomotive is operated, which is prone to causing insulation failure of high-voltage equipment. The HXD1 electric locomotive is taken as the research object in this paper to explore the characteristics and influencing factors of operating overvoltage. Under pantograph lifting, main breaker closing, main breaker opening, and pantograph dropping, operating overvoltage waveform in the high-voltage system is recorded by a high-speed oscilloscope and resistance–capacitance voltage divider to analyze the overvoltage characteristics and distribution law. Tested data show that the amplitude of operating overvoltage is in the range of 80 to 330 kV with ultra-high steepness, which is similar to the Very Fast Transient Overvoltage (VFTO) in power systems. The maximum overvoltage during the entire test occurred during the main breaker closing and its amplitude is 328.60 kV with a steepness of 4.21 × 104 kV/μs. The max overvoltage of the other operations (pantograph lifting, main breaker opening, and pantograph dropping) are 280.60 kV, 194.73 kV, and 305.56 kV with ultra-high steepness. High-amplitude overvoltage is predominantly located at the pantograph, while the low-amplitude sort is mainly observed around other high-voltage equipment. The result indicates that operating overvoltage belongs to ultra-fast transient overvoltage and its amplitude and steepness are higher than existing research.

Enhancing insulating properties of glass-fiber reinforced polymers using plasma fluorination-modified boron nitride nanosheets

The insulation failure of glass fiber-reinforced polymers (GFRP) limits their use in high-voltage insulation fields. In this study, boron nitride nanosheets (BNNS) were prepared using ball-milling and further fluorinated via dielectric barrier discharge (DBD) plasma treatment. The GFRP nanocomposites were fabricated using different filler types and doping concentrations. The test results indicated that fluorinated BNNS (F-BNNS) displays good dispersion and interfacial compatibility, enhances the interfacial bonding strength of the “fiber-matrix-filler” ternary system in GFRP, and reduces the internal defects of materials. In addition, the insulating properties of the composites were related to the filler concentration. Adding a trace amount of F-BNNSs increased the flashover and breakdown voltages of the GFRP by up to 28.77% and 21.62%, respectively. The results of molecular dynamics simulations and trap distribution calculations showed that plasma fluorination of BNNS increases the bandgap and deep trap energy level at the interface. The extremely strong charge-binding ability of the deep traps inhibits continuous charge injection and regulates carrier migration, which improves the insulating properties of the composites. The results of this study provide a novel, environmentally friendly, and efficient solution for improving the insulating properties of GFRP.

Impact of barriers on dielectric strength and electric field distribution in point-plane air gap configurations

This study presents a numerical investigation into the dielectric strength of point-plane air gaps, specifically focusing on the influence of dielectric barriers on the potential and electric field distributions under alternating current (AC) voltage. By utilizing two-dimensional (2D) electrostatic simulations through the finite element method (FEM), both configurations—with and without dielectric barriers—are analyzed to assess their impact on vertically arranged point-plane gaps. The study demonstrates that the inclusion of a dielectric barrier plays a crucial role in redistributing the electric field, leading to a more uniform distribution and reducing localized peaks. This results in enhanced dielectric strength, allowing the system to withstand higher voltages without breakdown. The findings are significant for the design and optimization of high-voltage insulators, as incorporating dielectric barriers can improve overall insulation performance and reliability. By improving the electric field distribution, these barriers contribute to reducing the risk of insulation failure, thereby increasing the efficiency and longevity of high-voltage components, making them more reliable for applications in power transmission systems.

Impact of Harmonic Voltage on the Partial Discharge Properties of Eco-Friendly Nanofluid

The Insulation is crucial in transformers to maintain electrical isolation between components and windings, ensuring safe and efficient operation. Mineral oil acts as both insulation and coolant in transformers. It is a substance that does not naturally degrade and can persist in the environment for an extended period if accidentally released. Therefore, Sunflower oil is used as a substitute for mineral oil. However, harmonic distortion is a common issue in power systems, leading to increased dielectric loss and partial discharge activity, ultimately causing insulation failure and equipment damage. Hence, it is vital to analyze the partial discharge performance of pure Sunflower oil under varying harmonic AC voltages to ensure the reliable operation of electrical devices. The study examines the partial discharge characteristics of a sunflower oil-based nanofluid under harmonic AC voltages, which is a blend of pure sunflower oil and SiO2 nanoparticles. Two nanofluid mixtures were created, one with a 0.01% mass ratio and the other with 0.05% sunflower oil. Various PD characteristics were evaluated, including Partial Discharge significance, starting voltage, duration of increase, maximum amplitude, Phase-Resolved PD sample, and frequency and time graphs of the Partial Discharge signal. All tests were carried out under IEC regulations. A comparison was made between the outcomes of Nano blended sunflower oil and natural sunflower edible oil. Experiments were conducted on partial discharges in Sunflower oil using specific harmonic superimposed AC Voltages, utilizing the third and fifth harmonics. The findings reveal that: a) PDIV value decreases with increasing harmonic order when using AC voltage with superimposed harmonics, b) PD characteristics are closely related to the voltage waveform, and the addition of Silica to sunflower oil results in reduced PD amplitude, pulse duration, and time duration compared to pure sunflower oil.

Degradation Mechanism and Online Electrical Monitoring Techniques of Stator Winding Insulation in Inverter-Fed Machines: A Review

Inverter-fed machines are widely used in electric vehicle drive systems and have shown a trend toward high voltage and frequency in recent years. They are subjected to multiple types of stress during operation, causing potential short-circuit fault damage to the stator winding insulation. Online condition monitoring of the insulation before or in the early stage of the short circuit fault can effectively reduce maintenance costs and ensure its health. This paper reviews and summarizes the deterioration mechanism and the recent online electrical monitoring techniques. First, four types of failure stress and each type’s failure factors and mechanisms are analyzed. The coupling effect and overall process of multi-physical fields on stator insulation failure are considered. Secondly, the latest online electrical monitoring technologies are summarized. Each technique’s principles, methods, advantages, and disadvantages are analyzed. Finally, existing problems and possible directions for improvement in current research are discussed, focusing on their feasibility and accuracy in practical applications.

Degradation induced by charge relaxation in silicone gels under the ultra‐fast pulsed electric field

AbstractThe insulating properties of silicone gel used for silicon carbide‐insulated gate bipolar transistors encapsulation may deteriorate seriously under ultra‐fast pulsed electric fields. The essence of insulation degradation lies in the deterioration of materials caused by dynamic phenomena at microscopic scale, such as charge trapping and detrapping. Different from the steady‐state operating condition, insulating materials exhibit a sharp decrease in their insulating properties when subjected to a rapidly changing electric field. To investigate the insulation failure of silicone gel materials under an ultra‐fast pulsed electric field, Marcus hopping mechanism for charge response is proposed. By calculating the relaxation time with different defects, we characterise the degradation of the materials. According to the force analysis of space charge, the authors establish a relationship between insulation failures and charge relaxation time. Combined with the experimental results on electrical treeing in silicone gel, the feasibility of the theory is verified. The experimental phenomenon can be well explained, that is, the initial voltage of the electrical trees decreased sharply with shortening the edge time of the pulsed electric field, especially on the nanosecond time scale.

Field strength prediction of 220 kV cable oil terminal defects based on multivariate nonlinear regression model

During the installation of a cable oil terminal, it is easy to leave scratches on the main insulation owing to uneven forces when removing the semi-conductive layer. Scratch defects cause field intensity distortion, which leads to partial discharge and insulation failure. This study attempts to establish a simulation model of a 220 kV cable terminal to determine the effect of the length, depth, and position of the scratch on the maximum field strength at the defect. The simulation and experiment demonstrate that the maximum field strength at the defect increases with greater length and decreases as the depth increases. Therefore, a prediction method for the terminal defect field strength based on a multivariate nonlinear regression model was proposed in this study. When the defect is located at 20 mm from the root of the stress cone, the maximum field strength is 14.5 MV/m when the length and depth are 2 mm and 1 mm, respectively. The maximum field strength at the defect was predicted based on the length, depth, and position of the scratch defect to evaluate the severity of the defect.

A study of XLPE insulation failure in power cables under electromagnetic stress

Underground cables with cross-linked polyethylene (XLPE) insulation are integral to medium voltage (MV) power transmission systems, ensuring continuous electricity supply amidst operational challenges and environmental conditions. However, the reliability of these cables can be compromised over time due to aging and installation-related factors, particularly at joints and terminations. This study offers a comprehensive analysis of how various defects, including spherical air voids, pinholes, and irregularities in semiconducting layers, affect electric field and potential distributions within cable end terminations using COMSOL Multiphysics software. Through detailed simulations, the study identifies significant variations in electric field strength caused by these defects, highlighting critical stress concentration areas. In this study, it assumed that the cable and termination have the same cross-section. By analyzing these simulations, the study provides insights into optimizing cable design and installation practices to enhance the reliability and lifespan of underground power transmission systems. This study introduces a novel approach by combining advanced COMSOL Multiphysics simulations with a detailed analysis of defect impacts on electric field distributions, offering new insights into stress concentrations and degradation at cable terminations. Simulation outcomes reveal significant variations in electric field strengths due to air voids and pinholes in cables and terminations: for 2 mm voids, up to 2.45×106 V mm−1 near the conductor and 56.5 V mm−1 at termination. These findings enhance the understanding of XLPE-insulated cable behavior under electromagnetic stress, providing a basis for mitigating failures and improving overall system performance.

A new method for diagnosing insulation failures in battery packs based on BiLSTM networks

A new method for diagnosing insulation failures in battery packs based on BiLSTM networks

Performance analysis of high voltage disc insulators with different profiles in clean and polluted environments using flashover, withstand voltage tests and finite element analysis

Severe pollution-induced flashovers on insulators present a pressing challenge to power system safety. The frequent failure of high-voltage insulators, particularly in the polluted environments of Pakistan, poses a critical concern. This paper investigates the impact of insulator profile on reducing pollution flashovers, testing two designs as per IEC standard 60383 and simulated using the Finite Element Method in COMSOL Multiphysics®. The test results revealed that deep under-ribs insulators exhibited a 5.008% reduction in flashover voltage, while alternating shed insulators experienced a 3.233% decrease in polluted conditions compared to clean conditions. Notably, under both clean and polluted conditions, alternating shed insulators consistently outperformed deep under-ribs insulators, with a 25.377% higher flashover voltage in clean conditions and a 27.400% superiority in polluted conditions. Computational analysis through the Finite Element Method in COMSOL Multiphysics shows a consistent pattern in potential distribution with increasing insulator count, but the presence of a pollution layer introduces spikes in the electric field distribution, validating experimental results. These findings highlight the superior performance of alternating shed insulators, especially in polluted environments.

Investigation of Partial Discharge Transformation Characteristics in Polyimide (PI) Insulations under High-Frequency Electric Stress.

This research delves into the primary issue of polyimide (PI) insulation failures in high-frequency power transformers (HFPTs) by scrutinizing partial discharge development under high-frequency electrical stress. This study employs an experimental approach coupled with a plasma simulation model for a ball-sphere electrode structure. The simulation model integrates the particle transport equation, Poisson equation, and complex chemical reactions to ascertain microscopic parameters, including plasma distribution, electric field, electron density, electron temperature, surface, and space charge distribution. The effect of the voltage polarity and electrical energy on the PD process is also discussed. The contact point plays a pivotal role in triggering partial discharges and culminating in the breakdown of PI insulation. Asymmetry phenomena were found between positive and negative half-cycles by analyzing the PD data stage by stage. A significant number of PDs increased at every stage and the PD amplitude was higher during the negative cycle at the initial stage, but in later stages, the PD amplitude was found to be higher in the positive half-cycle, and scanning electron microscopy (SEM) revealed that the maximum damage occurred near the contact point junction. The simulation results show that the plasma initially accumulates the electron density near the contact point junction. Under the action of the electric field, plasma starts traveling at the PI surface outward from the contact point. Before the PD activity, all parameters have higher values in the plasma head. The microscopic parameters reveal maximum values near the contact point junction, during PD activities where significant damage takes place. These parameter distributions exhibit a decreasing trend over time as when the PD activity ends. The model's predictions are consistent with the experimental data. The paper lays the foundation for future research in polymer insulation design under high-frequency electrical stress.

COMPARISON OF CORONA DISCHARGE IDENTIFICATION IN 20 kV CUBICLES BASED ON VOLTAGE AND NOISE USING ED, HMM, AND FCM

Phenomena such as corona discharge (CD) still occurs in many electrical systems in Indonesia. As a first step for early detection of insulation failure. Identification of CD acoustic in this study namely clustering based on voltage and based on noise. So that the CD acoustic classification is set into 3 clusters. In addition, this study also classifies CD acoustic based on noise with three clusters, namely pure CD, CD with noise, and pure noise. Clustering was performed using the linear predictive coding (LPC) method as feature extraction, then a comparison of pattern matching results of feature extraction was performed using Euclidean distance (ED), hidden Markov model (HMM) and fuzzy cluster mean (FCM). The temperature in the cubical is between 27.5 ℃ - 35.3 ℃ and humidity ranges from 70% - 95%. The results of clustering accuracy on the average base voltage using the ED, HMM and FCM methods were obtained respectively 100%, 100% 93.93% for training data and 80.74%, 84.44%, 80.55% for testing data. While the results of the average base noise clustering accuracy using the ED, HMM and FCM methods were obtained respectively 100%, 100%, 94.69% for training data and 100%, 100%, 100% for testing data.

Effect of Environmental and Operating Conditions on Partial Discharge Activity in Electrical Machine Insulation: A Comprehensive Review

Electrical machines for transportation applications are subjected to harsh environmental conditions during their operations. Partial discharge (PD), which is one of the main reasons for insulation failure, is greatly affected by ambient conditions (i.e., temperature, pressure, and humidity). Countless efforts are made for a comprehensive understanding of the physics of PD under variable environmental factors. This paper aims to review recent works addressing temperature, pressure, and humidity impact on PD activity. The main content of the paper is organized into three sections dealing with each environmental factor. In every section, relevant publications are reviewed considering the type of samples tested, voltage waveform applied, mutual effects, and the most common PD modeling strategies used. The applicability of the PD measurements for PD risk assessment is also discussed. Based on the review, the current progress in understanding the environmental effects on the PD inception mechanism and PD characteristics is presented and discussed in detail, and future research trends in this field are outlined.

FAULT DETECTION AND CLASSIFICATION USING DENSENET, SURF-BASED ANN, AND INFRARED THERMOGRAPHY

The reliability and efficiency of electric motors are critical in industrial applications, where unexpected faults can lead to costly downtime and safety hazards. Traditional fault detection methods often require extensive manual inspection and may not capture subtle anomalies in motor behavior. Infrared thermography has emerged as a non-invasive technique to detect temperature variations in motor components, which can indicate potential faults. However, the challenge lies in accurately classifying these faults to prevent failures. Current methods lack the precision needed to classify various motor faults accurately and quickly, especially when dealing with complex thermal patterns. The integration of advanced deep learning architectures with feature extraction techniques presents an opportunity to enhance the detection and classification of motor faults. This study proposes a hybrid model combining DenseNet, a deep learning architecture known for its high performance in image analysis, with a Speeded-Up Robust Features (SURF)-based Artificial Neural Network (ANN) for feature extraction and classification. Infrared thermography images of motors were first processed through DenseNet for initial feature extraction. The SURF algorithm further refined these features, which were then classified using ANN. The model was trained and validated on a dataset of infrared thermography images, representing various motor fault conditions, including bearing wear, misalignment, and insulation failure. The proposed model achieved an overall accuracy of 98.7% in detecting and classifying motor faults, outperforming traditional methods by 5.2%. The model also demonstrated high sensitivity (97.8%) and specificity (99.1%) in identifying subtle temperature variations indicative of early-stage faults. These results highlight the effectiveness of the DenseNet and SURF-based ANN approach in enhancing the reliability of motor fault detection using infrared thermography.

Mitigation Plans for Insulation Failures and Arcing in the ITER Magnets

Mitigation Plans for Insulation Failures and Arcing in the ITER Magnets

Effect of aluminum particles on the insulating properties of C4F7N/CO2 mixed gas

The C4F7N/CO2 mixed gas is most expected to replace SF6 in high-voltage power equipment, and the generation of free metal particles in gas-insulated equipment is unavoidable and highly susceptible to inducing insulation failures. In this paper, the effects of flaky, spherical, and mixed shape aluminum particle defects on the breakdown characteristics of C4F7N/CO2 mixed gas are investigated and compared to those of SF6 under the same conditions. The experimental results show that the effect of particle defects on the insulating properties of C4F7N/CO2 gas mixtures is visualized by the fact that particle defects reduce the breakdown voltage of C4F7N/CO2 gas mixtures, increase their stochasticity, and reduce the enhancement of the insulating properties of C4F7N/CO2 gas mixtures by increasing the air pressure. The greater the number of particles, the greater is the degree of influence. Comparison of the SF6 and C4F7N/CO2 gas mixtures reveals that, in the case of flake defects, increasing the air pressure improves the insulation performance of the SF6 gas better than that of the C4F7N/CO2 gas mixture. Under the condition of the same number of particles, the larger the proportion of spherical particles in the hybrid particles, the smaller is the influence of metal particles on the C4F7N/CO2 mixed gas and on SF6 gas.

Partial discharge detection, diagnosis, and location technology based on a novel transient earth voltage-ultrasonic integrated sensor used for switchgear equipment.

Medium-voltage (MV) switchgear and gas insulated switchgear (GIS) are essential components of power-grid systems. Their safe operation is crucial for the electricity consumption of users. However, insulation faults often occur during the operation of MV switchgear and GIS because of pollution, humidity, heat, mechanical shock, and other factors. Partial discharge (PD) measurements are the most effective indicator to prevent insulation failure. Transient earth voltage (TEV) and ultrasonic methods are the most popular PD measurement methods for switchgear. Currently, these two methods are used widely and independently. In this study, a novel TEV-ultrasonic integrated sensor is proposed based on the independent structure of the TEV and the ultrasonic sensor. The performance parameters of the proposed sensor were tested on test platforms. PD measurement experiments were conducted in a 10kV switchgear and 220kV GIS to analyze the performance of the integrated sensor. The results show that the sensor can simultaneously measure the TEV and ultrasonic signals in the same location. The integrated sensor can realize effective and sensitive detection, precise location, and accurate diagnosis of PD in the MV switchgear and GIS.

High energy storage performance in BTO-based ferroelectric films

Dielectric capacitors play an increasingly important role in modern electronic power systems due to their ultrahigh charging and discharging speeds and power density. Much research has focused on enhancing dielectric breakdown strength to achieve better energy storage performance; however, this increases the potential for heat generation and unexpected insulation failures, thereby affecting the stability and lifespan of devices. This study introduces a small amount of Na+ dopants at the A-site of BaTiO3, inducing lattice distortions and enhancing local polarization to increase energy storage density rather than through enhancing breakdown strength. The introduction of Na+ enhances the ferroelectric properties, with polar nano-regions (PNRs) gradually evolving into long-range ordered large domains. In the Ba0.985Na0.015TiO3 films, the coexistence and coupling of abundant PNRs with a few long-range ordered ferroelectric domains result in high saturation polarization and low residual polarization. At a moderate electric field of 2.3 MV cm−1, an ultrahigh energy density of 44.3 J cm−3 and a high energy storage efficiency of 78.6 % were obtained. Additionally, the film exhibits excellent frequency stability (100 Hz-20 kHz), temperature stability (30–180 °C), fatigue resistance (107 cycles), and high pulsed discharge energy density, along with great thermal stability. This work provides new insights into achieving exceptional energy storage performance in single-phase films.

AC ripple on DC voltage: Experimental and theoretical investigation of the impact on accelerated ageing in electrical insulation

AbstractWith the increasing penetration of DC systems into the high voltage and medium voltage power industry, DC voltage is becoming common for distribution/transmission and to supply different typologies of loads. The allowable extent of AC ripple superimposed to DC, and its effect on insulation ageing, is a long‐term discussed topic. The most harmful phenomenon causing extrinsic ageing acceleration and insulation system premature failure is partial discharges (PD); thus, the risk of incepting PD due to AC ripple could become a primary issue for electrical asset equipment reliability. In this work, the impact of AC sinusoidal ripple on insulation system life and reliability is dealt with, considering both intrinsic and extrinsic ageing but focusing on the latter, that is, the PD aspect. Experiments are performed to assess how the jump voltage (due to AC ripple) and the DC component impact on PD activity in terms of amplitude and repetition rate. For the first time, the correlation between the magnitude of jump voltage associated with ripple and PD inception is established, shedding a light on the allowable ripple extent which does not impact significantly on ageing and premature insulation failure. This approach can provide straightforward tools for design specification and ageing inference of insulation systems.