Preliminary work on the detection of partial discharges in SF6 under impulse voltages

This paper presents preliminary results of an investigation into the detection of partial discharges on the rise of impulse voltages from a point-to-plane gap in SF6. A parallel RC detection impedance is placed in the earth path of a point. Computer simulations are done to determine the values of R and C that will result in the smallest impulse voltage signal and the largest discharge signal across the detection impedance. These simulations and the experimental work show that the impulse voltage signal can not be sufficiently attenuated during the rise time of the applied voltage impulse using the RC detection impedance alone. An alternative discharge detection method is proposed in which a resonant partial discharge coupler is used. Elimination of noise and the impulse voltage signal can be achieved by shorting the coupler plate to the ground plane in the middle of the disk. However, due to the bandwidth of the measuring equipment and noise from the impulse generator it was not possible to detect discharges on the rising edge of a 1.5s voltage impulse using a coupler shorted in the middle. It was found that for this particular coupler, with no shorting points, and if the rising edge of the voltage impulse is longer than 5us, (10us) PD activity can be detected on the rising edge.

Partial discharges at low pressures in a dielectric interface between uniform field electrodes

Partial discharges in a gaseous interface due to the presence of a dielectric between two uniform field electrodes in air at different pressures from 0.5 to 685 mm Hg have been studied and measurements of inception and extinction voltages, number of pulses and their charge magnitudes at inception are reported. It has been observed that the extinction voltage can be as low as 70% of the inception voltage suggesting that the working voltage in such cases should be about 30% lower than the observed inception voltage. Small magnitude pulses are found to be more in number than large magnitude pulses. The charge is found to be pressure dependent. The results have been explained on the basis of an equivalent circuit consisting of resistance and capacitance in which the discharge gap functions as a switch.

Measurements of partial discharges-corrections to erroneous counts occurring in a cumulative pulse-counting system

The discharge pulse rates at different magnitude levels are often used as criteria for monitoring the partial-discharge aging of insulation systems. Use of suggested corrections for errors in cumulative probability counting leads to better use of available counters.

Detection of partial discharges at field in SF6 insulated equipments

This paper presents the results of research aiming to develop partial discharge detection techniques in high voltage equipment, at substation environment. Measurements of high frequency components of leakage current, at equipments' grounding conductor, were performed. This procedure was performed with the equipment energized and without disconnecting it from the system. The partial discharge generated current pulse is picked up by a high frequency CT, and is detected by an oscilloscope. The partial discharge identification was made considering previously obtained laboratory results, where partial discharges were characterized by means of its time domain signatures. This paper focuses measurements in SF6 circuit breakers. Encouraging results were obtained, showing the feasibility of detecting partial discharges in energized equipment in the laboratory and in the field, in a substation environment, using this method.

Signal analysis and feature generation for pattern identification of partial discharges in high-voltage equipment

This paper proposes a method for the identification of different partial discharges (PDs) sources through the analysis of a collection of PD signals acquired with a PD measurement system. This method, robust and sensitive enough to cope with noisy data and external interferences, combines the characterization of each signal from the collection, with a clustering procedure, the CLARA algorithm. Several features are proposed for the characterization of the signals, being the wavelet variances, the frequency estimated with the Prony method, and the energy, the most relevant for the performance of the clustering procedure. The result of the unsupervised classification is a set of clusters each containing those signals which are more similar to each other than to those in other clusters. The analysis of the classification results permits both the identification of different PD sources and the discrimination between original PD signals, reflections, noise and external interferences. The methods and graphical tools detailed in this paper have been coded and published as a contributed package of the R environment under a GNU/GPL license.

Signal analysis and feature generation for pattern identification of partial discharges in high-voltage equipment

This paper proposes a method for the identification of different partial discharges (PDs) sources through the analysis of a collection of PD signals acquired with a PD measurement system. This method, robust and sensitive enough to cope with noisy data and external interferences, combines the characterization of each signal from the collection, with a clustering procedure, the CLARA algorithm. Several features are proposed for the characterization of the signals, being the wavelet variances, the frequency estimated with the Prony method, and the energy, the most relevant for the performance of the clustering procedure. The result of the unsupervised classification is a set of clusters each containing those signals which are more similar to each other than to those in other clusters. The analysis of the classification results permits both the identification of different PD sources and the discrimination between original PD signals, reflections, noise and external interferences. The methods and graphical tools detailed in this paper have been coded and published as a contributed package of the R environment under a GNU/GPL license.

Surface Discharge Studies with Uniform Field Electrodes at Low Pressures

An investigation of power frequency (50 Hz) surface partial discharges in dry air, using 21r/3 Rogowski profile electrodes in the low pressure range of 0.067 to 91.333 kPa, shows that for the discharges occurring symmetrically around the electrodes and just outside the uniform field region, the breakdown voltages are 20 to 30% lower than those accounted for by the usual Paschen values. Emphasis, therefore, has been given to modified values of breakdown voltages for any useful calculations. The effect of reduced pressure on inception voltage has been discussed and an attempt has been made to explain the difference between the observed and calculated values on the basis of a pressure-dependent secondary ionization coefficient. It is shown that increasing the insulation thickness in a critical pressure range (0.067 to 0.400 kPa) does not allow any significant increase in the discharge free working stress of the insulation system. At higher pressures (>0.400 kPa) the increase in inception voltage with thickness and pressure follows an equation which is expected to hold for other insulating materials as well.

A PPCA based non-parametric modeling and retrieval of PD signal buried in excessive noise

The problem of on-line recognition and retrieval of relatively weak industrial signals such as partial discharges (PD), buried in excessive noise, has been addressed in this paper. The major bottleneck being the recognition and suppression of stochastic pulsive interference (PI) due to the overlapping broad band frequency spectrum of PI and PD pulses. Therefore, on-line, onsite, PD measurement is hardly possible in conventional frequency based DSP techniques. The observed PD signal is modeled as a linear combination of systematic and random components employing probabilistic principal component analysis (PPCA) and the pdf of the underlying stochastic process is obtained. The PD/PI pulses are assumed as the mean of the process and modeled instituting non-parametric methods, based on smooth FIR filters, and a maximum aposteriori probability (MAP) procedure employed therein, to estimate the filter coefficients. The classification of the pulses is undertaken using a simple PCA classifier. The methods proposed by the authors were found to be effective in automatic retrieval of PD pulses completely rejecting PI.

A Long Memory Process Based Parametric Modeling and Recognition of PD Signal

We address the problem of recognition and retrieval of relatively weak industrial signal such as Partial Discharges (PD) buried in excessive noise. The major bottleneck being the recognition and suppression of stochastic pulsive interference (PI) which has similar time-frequency characteristics as PD pulse. Therefore conventional frequency based DSP techniques are not useful in retrieving PD pulses. We employ statistical signal modeling based on combination of long-memory process and probabilistic principal component analysis (PPCA). An parametric analysis of the signal is exercised for extracting the features of desired pules. We incorporate a wavelet based bootstrap method for obtaining the noise training vectors from observed data. The procedure adopted in this work is completely different from the research work reported in the literature, which is generally based on deserved signal frequency and noise frequency.

Accelerated multistress aging of polymer nanocomposites and its condition monitoring

In recent years, the time dependant maintenance of expensive high voltage power equipments is getting replaced by condition based maintenance so as to detect apriori an impending failure of the equipment. For condition based maintenance, most monitoring systems concentrate on the electrical quantities such as measurement and evaluation of partial discharges, tan delta, tip-up test, dielectric strength, insulation resistance, polarization and depolarization current. However, in the case of equipments being developed with novel nanodielectric insulating materials, the variation in these parameters before an impending failure is not available. Hence in this work, accelerated electrothermal aging studies have been conducted on unfilled epoxy as well as epoxy nanocomposite samples of 5 wt% filler loading, and the tan d values were continuously monitored to obtain the condition of the samples under study. It was observed that those samples whose tan d increased at a rapid rate failed first.

Plant species identification using multi-scale fractal dimension applied to images of adaxial surface epidermis

This paper presents the study of computational methods applied to histological texture analysis in order to identify plant species, a very difficult task due to the great similarity among some species and presence of irregularities in a given species. Experiments were performed considering 300 ×300 texture windows extracted from adaxial surface epidermis from eight species. Different texture methods were evaluated using Linear Discriminant Analysis (LDA). Results showed that methods based on complexity analysis perform a better texture discrimination, so conducting to a more accurate identification of plant species. © 2009 Springer Berlin Heidelberg.