Influence of additional dielectric coatings on the electrode surfaces on selected parameters of acoustic emission signals in high-voltage gas insulation systems

The paper is devoted to the study of impact of additional dielectric coatings placed on the surface of the electrodes on the operation of a high-voltage insulation system with air as insulating medium. The study mainly focused on measurement of partial discharges (PDs) with the use of acoustic emission method. Tests were conducted in various levels of chamber pressure. Applicable parameters of recorded signals were analyzed with the use of applications developed in the environment of MATLAB software. The results of analyses clearly show that presence of additional coatings has impact on signal parameters and thus indirectly on PDs. The use of coatings reduces the duration of a single pulse (event) and increases its amplitude. Furthermore, the influence of degradation of the coating caused by individual discharges on the values of the analyzed parameters was analyzed. The study has shown, however, that this effect is negligible.

Non-Contact Methods for High-Voltage Insulation Equipment Diagnosis during Operation

The article describes a complex of non-contact methods for remote diagnosis of high-voltage insulators as well as the two-channel method for remote diagnostics of the operating state of high-voltage insulators, based on the registration of partial discharges by electromagnetic and acoustic sensors. The presented device allows visual inspection and searches for faulty high-voltage equipment and a remote non-contact method of recording high-intensity electric fields of industrial frequency and their spatial distribution based on the electro-optical effect. The scheme of using the system for monitoring and diagnosing the technical condition of high-voltage support insulators of open switchgear is described. The results of experimental studies confirm the possibility of industrial applicability of the proposed method for non-contact remote diagnostics of the state of high-voltage insulators under operating voltage.

Anomaly Detection, Trend Evolution, and Feature Extraction in Partial Discharge Patterns

In the resilient and reliable electrical power system, the condition of high voltage insulation plays a crucial role. In the field of high voltage insulation integrity, the partial discharge (PD) inception and development trends are essential for assessment criteria in diagnostics systems. The observed trend to employ more and more sophisticated algorithms with machine learning features and artificial intelligence (AI) elements is observed everywhere. The classification and identification of features in PD images is perceived as a critical requirement for an effective high voltage insulation diagnosis. In this context, techniques allowing for anomaly detection, trends observation, and feature extraction in partial discharge patterns are important. In this paper, the application of few algorithms belonging to image processing, machine learning and optical flow is presented. The feature extraction refers to image segmentation and detection of coherent forms in the images. The anomaly detection algorithms can trigger early detection of the trend changes or the appearance of a new discharge form, and hence are suitable for PD monitoring applications. Anomaly detection can also handle transients and disturbances that appear in the PD image as an indication of an abnormal state. The future monitoring systems should be equipped with trend evolution algorithms. In this context, two examples of insulation aging and application of PD-based monitoring are shown. The first one refers to deep convolutional neural networks used for classification of deterioration stages in high voltage insulation. The latter one demonstrates application of optical flow approach for motion detection in partial discharge images. The motivation for the research was the strive to machine-controlled pattern analysis, leading towards intelligent PD-based diagnostics.

Multi-Stressed Nano and Micro-Silica/Silicone Rubber Composites with Improved Dielectric and High-Voltage Insulation Properties

The scope of silicone rubber (SiR) is confined due to the deprivation of its dielectric propertiesupon exposure to various ambient stresses. The aim of this research is to develop silicone rubber-based composites by employing inorganic oxide fillers for improved dielectric and high voltage insulation properties for widening its scope in the field of electrical appliances. This study reports the preparation of different composites of silicone rubber with varying concentrations of micro and nano-silica fillers. The dielectric propertytrends of these as-prepared neat and impregnated samples were examined via an indigenously developed weathering chamber capable of applying multiple stresses of acid rain, heat, humidity, UVA radiation, and salt fog. Dielectric constant values were measured before and after applying stresses. Upon applying stresses, a periodic decline in dielectric constant was observed. Improved dielectric properties were obtained by adding micro and nano-silica as fillers. A nano silica-incorporated silicone rubber product exhibited good potential for dual applications as dielectric and high voltage insulation.