Partial Discharge — A Valuable Stator Winding Evaluation Tool

We constructed an on-line partial discharge (PD) monitoring system (PDOM) with a CT sensor, an analogue-digital converter, and a tablet PC. A sampling frequency for data acquisition is 100 MHz, and we exchange on-site PD data through a cloud system. We successfully measured PDs in the early stage of insulation deterioration of a cross-linked polyethylene (XLPE) cable in a field site. Additionally, following PD detection by using a PDOM, we can locate a PD position by using a PD locator (PDL) system. By locating a PD, we can estimate the actual PD magnitude considering attenuation factor of a high frequency pulse. We show how the PDL system works on a XLPE cable network with time synchronization between two positions by using an injection current pulse. The locating accuracy of the PDL system is evaluated.

Partial discharge (PD) based condition monitoring has been widely applied to power cables. However, difficulties in interpretation of measurement results (location and criticality) remain to be tackled. This paper aims to develop further knowledge in PD signal propagation in power cables and attenuation by the PD monitoring system devices to address the localization and criticality issues. As on-line or in-service PD monitoring sensors commonly comprise of a high frequency current transformer (HFCT) and a high-pass filter, the characteristics of detected PD pulses depend on the attenuation of the cable, the HFCT used and the filter applied. Simulation of pulse propagation in a cable and PD monitoring system are performed, based on analyses in the frequency domain using the concept of transfer functions. Results have been verified by laboratory experiments and using on-site PD measurements. The knowledge gained from the research on the change in pulse characteristics propagating in a cable and through a PD detection system can be very useful to PD denoising and for development of a PD localization technique.

Partial discharge (PD) monitoring applications enable the performance of appropriate diagnosis regarding the insulation condition of high-voltage (HV) electrical grids. During the last decade on-line PD monitoring systems have been increasingly implemented by utilities and large electricity consumers in HV installations. Therefore, the evaluation of their performance is interesting in order to check whether they are generally effective with respect to their functionalities. For the characterisation of the PD monitoring instruments and of the requirements of acquisition time (number of cycles per second), the performance of laboratory tests with real insulation defects is required. As these are monitoring tests, they entail a long time (at least one day), and during this time the monitored insulation defects must behave in a stable manner. The main scope of the study presented is to design, manufacture and characterise the behaviour of three test cells, each integrating a characteristic insulation defect, with the aim of using them in laboratory monitoring tests lasting at least one day. The considered insulation defects are as follows: an internal cavity in a solid dielectric, corona effect and a surface defect. The measurements carried out with the designed test cells have shown that they are suitable for their implementation in PD monitoring tests of long duration.

The assessment of the insulation condition of high-voltage power transmission networks using a non-invasive method of online partial discharge (PD) monitoring is currently a common practice in maintenance programs for elements of the distribution and transmission networks. The joint-stock company „Elektromreža Srbije“ Belgrade (EMS AD) manages a large number of power equipment (EES), on which various partial discharge monitoring strategies can be applied to control the insulation condition. One of the goals of EMS AD is to implement a real-time monitoring system aimed at optimizing the maintenance process and conducting diagnostics for the early detection of insulation defects and predicting failures in cable lines. The paper describes the activities related to the implementation of an online monitoring system for partial discharge detection, which involves the installation of permanent high-frequency sensors at strategic locations to diagnose the insulation condition of cable lines. Additionally, different levels of diagnostics are presented through the use of a software tool for automatically eliminating partial discharges that do not originate from insulation defects, as well as a tool for localizing partial discharges along the length of the cable line.

Partial Discharge (PD) monitoring is nowadays a worldwide accepted method for the condition-based assessment of stator insulation. Different solutions for sensors and acquisition techniques have been recommended, applied and lately acknowledged by international technical bodies [1-2]. Therefore, there is a strong need for a versatile PD monitoring system that can be applied to different types of rotating machines, and which can be connected to a wide range of PD sensors. Such a versatile partial discharge monitoring system is described in this paper, which is applicable to different machines and can be connected to a vast range of sensors. The advantage of having a fully digital system, whose settings can be easily remotely adjusted, is shown.

This paper introduces a computerized online PD (Partial Discharge) monitoring and diagnostic system for power transformers, which has been installed in a 500 kV substation in China. It consists of wide-band active transducers and DAU (Data Acquisition Unit) with modularized and exchangeable components. This system has been developed to monitor multiple parameters of multiple power transformers, which is based on COM (Component Object Model). In addition, the system can also be used to monitor other power equipment. Some results of on-line monitoring are discussed.

A Partial Discharge (PD) monitoring system for Air Insulated Substations (AIS) has been developed for monitoring of partial discharge activities of various insulators and insulating media that are distributed over an electrical substation. The proposed system utilizes four UHF sensors, which are to be placed around the area of interest so that any impulsive UHF signal originated from PD activity can be captured and subsequently processed for detection and localization of multiple PD sources. To improve the localization accuracy and to improve the detection specificity, i.e. to eliminate false impulsive UHF signals originated from other sources, a novel nearest-neighbour based approach is proposed, which utilizes the physical layout of the AIS to identify most probable PD source locations. The proposed algorithm can accurately find the PD source locations even in the presence of high time-delay-of-arrival (TDOA) estimation error by making necessary corrections in the PD source location estimation. The proposed algorithm has been field trialed in many small and medium-size distribution substations. A detailed comparative study with the other algorithms in different extreme situations has been performed with the help of simulation and laboratory-based testing. The obtained results are worthwhile for supporting widespread implementation of the proposed method.

Online partial discharge monitoring system (PDMS) was developed to assess the condition of stator winding in high voltage motors. 80 pF capacitive couplers were connected to a 6.6 kV motor stator coil terminal. The voltage applied to stator coils were at 3.81 kV, 4.76 kV and 6.6 kV, respectively. These stator coils have various types of artificial insulation defects such as large voids, semi-conductive coating damage and strand insulation fault. On-line PD monitoring system, digital PD detector (PDD) and turbine generator analyzer (TGA) were used to measure PD activity. Most of the defect mechanisms of a large motor can be associated with PD patterns such as internal, slot and conductor surface discharges. PD patterns coincide with on-line PD monitoring system, PDD and TGA. These instruments have an input bandwidth of 100 kHz-50 MHz, 40-400 kHz and 0.1350 MHz. Continuous on-line PD monitoring system was measuring the discharge activity of large motors that were installed with 80 pF capacitive couplers at the terminal box.

Partial Discharge (PD) measurement is an effective method to detect degradation processes in medium and high voltage equipment. As an example, after-laying PD test have become mandatory in many countries as a commissioning test for high voltage cable systems. This type of test can assess the presence of defects just after installation, but thermal cycling, electrical and thermal stress as well as contamination can lead to the onset of defects at a later time. To cope with defects arising during operation, the key is PD monitoring (offline tests are often too costly in terms of equipment, personnel and loss of revenues). This paper presents the application a of permanent PD monitoring system based on a Ultra-Wide band (UWB) detector to high voltage transition joints linking old fluid-filled cables with new XLPE cable lines. These cable accessories are highly critical because of the complexity of their insulation system and the fact they are realized on field (uncontrolled environment). The innovative monitoring scheme fully exploits the benefits coming from using a UWB detector, i.e., selective tracking of PD based on PD pulse characteristics. This approach enables to trend various PD sources separately, highlighting those that are associated with degradation phenomena within the insulation system. This approach will be unraveled and demonstrated by monitoring data coming from two cable lines.

There is a high risk of insulation system dielectric instability when partial discharge (PD) occurs. Therefore, measurement and monitoring of PD is an important preventive tool to safeguard high-voltage equipment from wanton damage. PD can be detected using optical method to increase the detection threshold and to improve the performance of on-line measurement of PD in noise environment. The PD emitted energy as acoustic emission. We can use this emitted energy to detect PD signal. The best method to detect PD in power transformer is by using acoustic emission. Optical sensor has some advantages such as; high sensitivity, more accuracy small size. Furthermore, in on-site measurements and laboratory experiments, it isoptical methodthat gives very moderate signal attenuations. This paper reviews the available PD detection methods (involving high voltage equipment) such as; acoustic detection and optical detection. The advantages and disadvantages of each method have been explored and compared. The review suggests that optical detection techniques provide many advantages from the consideration of accuracy and suitability for the applications when compared to other techniques.

On-line partial discharge (PD) monitoring is widely used to detect stator winding insulation deterioration. The most common type of on-line PD sensor for turbine generators is the 80 pF capacitive coupler installed at the machine terminals which detects the PD in the very high frequency (VHF) range. More recently, ultra high frequency (UHF) antennae have also been used to detect stator winding PD in large turbine generators. Both types of sensors have been installed in 16 turbine generators. This paper discusses the results from near simultaneous measurements from both types of sensors on the same machines. It was expected that the UHF sensors would have stronger discrimination of the electrical disturbances internal to the machine compared to the VHF sensors, but the VHF sensors would be more sensitive to PD. As expected, the VHF sensors were generally more corrupted by electrical disturbances. However, in about half of the machines investigated here, the UHF sensors were significantly more sensitive than the VHF sensors. Many examples of phase-resolved PD patterns that illustrate these findings are presented.

High-voltage equipment materials are the most important part in determining the quality of equipment products, the selection of these materials is basically to determine the sustainability and durability of the equipment. The safety factor of insulation on high voltage equipment is strongly influenced by the type of material used. There are many insulation failures and material failures, both in production systems and production defects, this is part of the production process. One test for high voltage equipment can be done using the Partial Discharge (PD) testing method. PD testing on equipment is carried out to determine the characteristics of PD. In this study, the Surface Partial Discharge test was carried out on the surface around the edge of the Printed Circuit Board (PCB) with a plate electrode model. The parameters measured in PD are PDIV values, PD waveforms, and PD patterns. Monitoring in PD testing is done using the Electric method, namely the RC Detector sensor, HFCT, and the Non-electric method, namely the Loop Antenna. Tests are carried out on gas insulation (air)

Asset condition monitoring through Partial Discharge (PD) measurements is widely used for pre-emptive maintenance especially in cable networks. Several monitoring systems rely on measurements in the High Frequency (HF) band using wideband sensors when it comes to PD monitoring to have higher Signal to Noise Ratios (SNR), ignoring the radical attenuation of the higher frequencies by the cable. This paper presents measured values of attenuation from measuring loops and several other important insights that can help in the interpretation of PD measured data.

Supervised contrastive learning (SCL) has recently emerged as an alternative to conventional machine learning and deep neural networks. In this study, we propose an SCL model with data augmentation techniques using phase-resolved partial discharge (PRPD) in gas-insulated switchgear (GIS). To increase the fault data for training, we employ Gaussian noise adding, Gaussian noise scaling, random cropping, and phase shifting for supervised contrastive loss. The performance of the proposed SCL was verified by four types of faults in the GIS and on-site noise using an on-line ultra-high-frequency (UHF) partial discharge (PD) monitoring system. The experimental results show that the proposed SCL achieves a classification accuracy of 97.28% and outperforms the other algorithms, including support vector machines (SVM), multilayer perceptron (MLP), and convolution neural networks (CNNs) in terms of classification accuracy, by 6.8%, 4.28%, 2.04%, respectively.

Partial discharge (PD) monitoring is critical for ensuring the safe and stable operation of transformers and shunt reactors. Developing a non-invasive PD monitoring method applicable to both offline and online scenarios can significantly enhance operational safety. Conventional bushing current transformers (BCTs), primarily designed for power-frequency current measurement, exhibit topological similarities to Rogowski coils commonly used for high-frequency current sensing. The authors have verified their high-frequency current sensing capability. Diagnostic PD test data from an ultra-high-voltage shunt reactor (returned to the factory due to acetylene generation) at an ultra high voltage(UHV)substation demonstrate that bushing CTs exhibit consistent variation trends with conventional high-frequency current transformers (HFCTs) installed at the core and clamping structures. The correlation coefficient R2 between the two exceeds 0.89, with matching phase-resolved partial discharge (PRPD) patterns and comparable signal-to-noise ratios to HFCTs. These findings validate the feasibility and advantages of utilizing BCTs for online PD monitoring in transformers and shunt reactors.