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Polymeric insulators, in particular silicone rubber (SIR) are lightweight, have good hydrophobicity characteristics, and are easy to carry and install. They are commonly used for outdoor insulation in power lines. However, pollution, UV radiation, temperature, discharge, wetness, and stress can cause them to degrade over time, losing their electrical properties. Therefore, evaluating the ageing and degradation of polymeric insulators under different conditions becomes crucial. This paper investigates the ageing effects of the polymeric insulators with differences in pollution, applied voltage, hydrophobicity class, and geometrical structures of insulators. The investigation includes the experimental tests of the insulators’ electrical properties such as leakage current and flashover voltage, after assessing the initial characteristics of insulators based on their age and supply voltage. In addition, the aged polymeric insulator model based on an equivalent circuit model was developed to determine the leakage current and breakdown voltage of aged insulators. Moreover, an artificial neural network model is carried out to predict the critical leakage current and flashover voltage of the insulator under the ageing effect. The experiment results were used to validate the accuracy of the proposed models; with an aggregate error of less than 10%, the proposed models appeared to be satisfactory. These models can serve as a scholarly resource for designing, operating, and maintaining insulators, especially in polluted environments.

Over the past decades, extensive experimental-based research works have been carried out to investigate the flashover phenomenon on the performance of polluted transmission line insulators. The critical focus has been on developing methods that can determine the safety, reliability, and sustainability of the overall power transmission network based on experimental results obtained from polluted insulators’ flashover voltage tests. In this paper, a systematic review of available scientific works, published as early as the 1990s, for the analysis of pollution flashover voltage, is undertaken. The review mainly focuses on factors influencing the efficiency of transmission line insulators under polluted conditions. Specifically, publication databases utilizing various synonyms and keywords associated with the terms “contaminated insulators” and “flashover voltage test” have been scrutinized. The search has resulted in 1364 articles, from which 97 articles have satisfied the review requirements and have been subsequently analyzed to determine the parameters associated with polluted insulators. Major factors that affect the performance of insulators, including electrical and environmental impacts, are discussed. Variations in factors affecting flashover test development and insulator efficiency are also considered. Overall, the current analysis provides an important insight toward successful evaluations of the health of transmission line insulators and research advancements of electric power transmission line insulators.

This work aimed to study the influence of contamination profiles and humidity on flashover electrical characteristics of polluted insulators. Firstly, the flashover tests on cap and pin glass insulators under four pollution levels represented by salinity were conducted. Eight artificial contamination profiles based on the solid layer method have been modeled for the selected insulators. The numerical analysis has been used to determine the insulator electrical characteristics such as potential, electric field, and power dissipation under proposed contamination profiles using finite element methods (FEM). Next, the power dissipation has been simulated with consideration of thermal stress propagation in locations with high power. Finally, flashover voltage gradient tests have been conducted under various humidity and contamination profiles. The values of the flashover voltage gradient due to pollution were determined as the percentage of the value of the flashover voltage gradient in the clean condition which was identified as the reference point. The numerical model indicated that the initiation of arc generally occurs at area in which the electric field and power dissipation is maximum. It was also observed from experimental results that the flashover voltage gradient under different contamination profiles has different values depends on the location and dimension of the pollution region.

Frequency Response Analysis (FRA) is the most reliable technique currently used to evaluate the mechanical integrity of power transformers. While the measurement devices have been well developed over the past two decades, interpretation of the FRA signatures is still challenging regardless of the several papers published in this regard. This paper adds an attempt to understand the power transformer FRA signatures through experimental and simulation analyses. In this context, experimental FRA measurements are conducted on a 33/11 kV, 30 MVA transformer under various faults, including winding deformation, the short circuit turns, loss of clamping, and bushing fault. At the same time, the high-frequency transformer model that comprises series capacitance, self-inductance, series resistance, and mutual inductance is simulated using MATLAB / Simulink to compare simulation and experimental results. The correlation between physical circuit parameters and various faults facilitates a better understanding of each fault’s effect on the FRA signature. To quantify the impact of such faults, correlation coefficient, the absolute sum of logarithmic error, standard deviation, and sum square error are calculated with respect to the healthy signature at three frequency regions. Results show that using statistical coefficients over three frequency ranges of the FRA signature facilitates better fault identification and quantification.

This paper presents a new investigation to detect various faults within the three-phase star and delta induction motors (IMs) using a frequency response analysis (FRA). In this regard, experimental measurements using FRA are performed on three IMs of ratings 1 HP, 3 HP and 5.5 HP in normal conditions, short-circuit fault (SC) and open-circuit fault (OC) conditions. The SC and OC faults are applied artificially between the turns (Turn-to-Turn), between the coils (Coil-to-Coil) and between the phases (Phase-to-Phase). The obtained measurements show that the star and delta IMs result in dissimilar FRA signatures for the normal and faulty windings. Various statistical indicators are used to quantify the deviations between the normal and faulty FRA signatures. The calculation is performed in three frequency ranges: low, middle and high ones, as the winding parameters including resistive, inductive and capacitive components dominate the frequency characteristics at different frequency ranges. Consequently, it is proposed that the boundaries for the used indicators facilitate fault identification and quantification.

Frequency Response Analysis (FRA) technique has been recognized by worldwide utilities as a matured technology to assess the mechanical integrity of power transformers. While some industrial critical assets such as induction motors have the same construction principle as power transformers, the application of FRA technique to induction motors has not yet been fully explored. This paper presents analogical experimental studies for the application of FRA on power transformers and induction motors. For a consistent analogy, the FRA technique has been employed to detect short and open circuit turns in both appliances, which helps explore a wider scope of the FRA applications on rotating machines. In this regard, experimental FRA measurements are performed on an 11/0.415 kV, 500 kVA, three-phase distribution transformer and a 5.5 HP three-phase induction motor. Several short and open circuit faults are staged on the windings of both tested equipment and the FRA signature is recorded and compared with the reference signature at no fault. To quantify the impact of faults on the FRA signature, several statistical indicators are used and threshold limits for these indicators are proposed to automate the interpretation process. Results reveal a good correlation between the FRA signatures of induction motors and power transformers that attests to the feasibility of using FRA technique to detect various faults within large rotating machines.

Insulator monitoring using leakage current characteristics is essential for predicting an insulator’s health. To evaluate the risk of flashover on the porcelain insulator using leakage current, experimental investigation of leakage current indices was carried out. In the first stage of the experiment, the effect of contamination, insoluble deposit density, wetting rate, and uneven distribution pollution were determined on the porcelain insulator under test. Then, based on the laboratory test results, leakage current information in time and frequency characteristics was extracted and employed as assessment indicators for the insulator’s health. Six indicators, namely, peak current indicator, phase shift indicator, slope indicator, crest factor indicator, total harmonic distortion indicator, and odd harmonics indicator, are introduced in this work. The obtained results indicated that the proposed indicators had a significant role in evaluating the insulator’s health. To evaluate the insulator’s health levels based on the extracted indicator values, this work presents the naïve Bayes technique for the classification and prediction of the insulator’s health. Finally, the confusion matrix for the experimental and prediction results for each indicator was established to determine the appropriateness of each indicator in determining the insulator’s health status.

The industry has widely accepted Frequency Response Analysis (FRA) as a reliable method to detect power transformers mechanical deformations. While the FRA technique has been recommended in recent literature as a potential diagnostic method to detect internal faults within rotating machines, detailed feasibility studies have not been fully addressed yet. This paper investigates the feasibility of using the FRA technique to detect several short circuit faults in the stator winding of three-phase induction motors (TPIMs). In this regard, FRA testing is conducted on two sets of induction motors with various short circuit faults. Investigated faults include short circuits between two phases, short circuit turns within the same phase, phase-to-ground, and phase-to-neutral short circuit. The measured FRA signatures are divided into three frequency ranges: low, medium, and high. Several statistical indicators are employed to quantify the variation between faulty and healthy signatures in each frequency range. Experimental results attest the feasibility of the FRA technique as a diagnostic tool to detect internal faults in rotating machines, such as induction motors.

Power transformers are located in the electrical transmission and distribution networks where different voltage levels are needed. The turn ratio of the low voltage and high voltage windings is mechanically controlled by an on-load tap changer or de-energized tap changer. As the tap changer is the transformer’s only moving part, it is highly susceptible to mechanical failure and aging degradation. While some diagnostic tools have been used to determine the mechanical condition of tap changer contacts, not much attention was given to use the frequency response analysis to diagnose the transformer’s tap changers’ mechanical integrity. This paper is taking one step forward into maturing the application of the frequency response analysis (FRA) technique to detect transformer tap changer faults. In this regard, two common tap changer faults are created, and experimental testing for four FRA test configurations is conducted. For a better understanding of the tap changer fault mechanism, an electrical equivalent circuit model is proposed and designed using Simulink. The simulation and implementation of the equivalent circuits using MATLAB\R2018a.

Frequency response analysis (FRA) is a method of monitoring a power transformer’s mechanical integrity. However, identifying the type of fault and its severity by comparing measured responses is still challenging and mostly relies on personnel expertise. This paper is taking one step forward to standardize the FRA interpretation process by proposing guidelines based on various international standards and FRA case studies. In this study, the FRA signature is divided into three regions: low-, mid- and high-frequency regions. The deviation from the fingerprint signature for various faults is classified into small, large, and no variations, based on the calculation of the correlation coefficient. The proposed guidelines are developed based on the frequency regions, and the level of variation is represented using a simple arrow method to simplify the interpretation process. A case study is conducted on a three-phase 11/0.433 kV, 500 kVA distribution transformer with a short circuit winding fault to validate the proposed guidelines.