Abstract: In this paper, partial discharge analysis is performed in cavities artificially created in insulation. The setup is according with Cigre-II Method. Circular Samples created from Perspex Sheet with different configuration with changing number of cavities. Assessment of insulation health can be performed by Partial Discharge measurement as this has been found to be important means of condition monitoring. The experiments are done using MPD 540, which is a modern partial discharge measurement system. By analyzing the PD activity obtained for various voids/cavities, it is observed that the PD voltages show variation for cavity’s diameter, depth even for its ratios. This can be employed for scrutiny of insulation system.
Abstract: An acoustic emission (AE) technique is useful for
detection of partial discharges (PDs) at a joint and a terminal section of
a cross-linked polyethylene (XLPE) cable. For AE technique, it is not
difficult to detect a PD using AE sensors. However, it is difficult to
grasp whether the detected AE signal is owing to a single discharge or
not. Additionally, when an AE technique is applied at a terminal
section of a XLPE cable in salt pollution district, for example, there is
possibility of detection of AE signals owing to creeping discharges on
the surface of electric power apparatus. In this study, we evaluated AE
signals in order to grasp what kind of information we can get from
detected AE signals. The results showed that envelop detection of AE
signal and a period which some AE signals were continuously detected
were good indexes for estimating state-of-discharge.
Abstract: This paper presents the effectiveness of artificial
intelligent technique to apply for pattern recognition and
classification of Partial Discharge (PD). Characteristics of PD signal
for pattern recognition and classification are computed from the
relation of the voltage phase angle, the discharge magnitude and the
repeated existing of partial discharges by using statistical and fractal
methods. The simplified fuzzy ARTMAP (SFAM) is used for pattern
recognition and classification as artificial intelligent technique. PDs
quantities, 13 parameters from statistical method and fractal method
results, are inputted to Simplified Fuzzy ARTMAP to train system
for pattern recognition and classification. The results confirm the
effectiveness of purpose technique.
Abstract: Partial Discharge measurement is a very important
means of assessing the integrity of insulation systems in a High
Voltage apparatus. In compressed gas insulation systems, floating
particles can initiate partial discharge activities which adversely
affect the working of insulation. Partial Discharges below the
inception voltage also plays a crucial in damaging the integrity of
insulation over a period of time. This paper discusses the effect of
loose and fixed Copper and Nichrome wire particles on the PD
characteristics in SF6-N2 (10:90) gas mixtures at a pressure of
0.4MPa. The Partial Discharge statistical parameters and their
correlation to the observed results are discussed.
Abstract: Insulation used in transformer is mostly oil pressboard insulation. Insulation failure is one of the major causes of catastrophic failure of transformers. It is established that partial discharges (PD) cause insulation degradation and premature failure of insulation. Online monitoring of PDs can reduce the risk of catastrophic failure of transformers. There are different techniques of partial discharge measurement like, electrical, optical, acoustic, opto-acoustic and ultra high frequency (UHF). Being non invasive and non interference prone, acoustic emission technique is advantageous for online PD measurement. Acoustic detection of p.d. is based on the retrieval and analysis of mechanical or pressure signals produced by partial discharges. Partial discharges are classified according to the origin of discharges. Their effects on insulation deterioration are different for different types. This paper reports experimental results and analysis for classification of partial discharges using acoustic emission signal of laboratory simulated partial discharges in oil pressboard insulation system using three different electrode systems. Acoustic emission signal produced by PD are detected by sensors mounted on the experimental tank surface, stored on an oscilloscope and fed to computer for further analysis. The measured AE signals are analyzed using discrete wavelet transform analysis and wavelet packet analysis. Energy distribution in different frequency bands of discrete wavelet decomposed signal and wavelet packet decomposed signal is calculated. These analyses show a distinct feature useful for PD classification. Wavelet packet analysis can sort out any misclassification arising out of DWT in most cases.
Abstract: This paper investigates the influence of various
parameters on the behaviour of water droplets on polymeric surfaces
under high electric fields. An inclined plane test was carried out to
understand the droplet behaviour in strong electric field. Parameters
such as water droplet conductivity, droplet volume, polymeric
surface roughness and droplet positioning with respect to the
electrodes were studied. The flashover voltage is affected by all
aforementioned parameters. The droplet positioning is in some cases
more vital than the droplet volume. Surface damages were analysed
using Scanning Electron Microscopy (SEM) studies and by Energy
dispersive X-ray Analysis (EDAX). It is observes that magnitude of
discharge have direct influence on amount of surface da
Abstract: Design of Converter transformer insulation is a major
challenge. The insulation of these transformers is stressed by both
AC and DC voltages. Particle contamination is one of the major
problems in insulation structures, as they generate partial discharges
leading it to major failure of insulation. Similarly corona discharges
occur in transformer insulation. This partial discharge due to particle
movement / corona formation in insulation structure under different
voltage wave shapes, are different. In the present study, UHF
technique is adopted to understand the discharge activity and could
be realized that the characteristics of UHF signal generated under
low and high fields are different. In the case of corona generated
signal, the frequency content of the UHF sensor output lies in the
range 0.3-1.2 GHz and is not much varied except for its increase in
magnitude of discharge with the increase in applied voltage. It is
realized that the current signal injected due to partial
discharges/corona is about 4ns duration measured for first one half
cycle. Wavelet technique is adopted in the present study. It allows
one to identify the frequency content present in the signal at different
instant of time. The STD-MRA analysis helps one to identify the
frequency band in which the energy content of the UHF signal is
maximum.