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The measurement of acoustic and electrical signals for the partial discharge (PD) activity due to the presence of metallic particles within transformer oil are utilized for the characterization of the incipient hazards. The utilization of phase resolved, in addition, to time resolved partial discharge signals is undertaken to extract numerous features using statistical and frequency analyzers. The extracted features are down scaled to pinpoint the effective attributes that render an intelligent classification means useful for determining contaminating particle type and dimensions. This is accomplished by utilizing feature selection wrapper models undertaking the sequential floating forward selection (SFFS) and particle swarm optimization as alternative search strategies. Support vector machines (SVM) is finally used for the classification of contaminating particles identity. A comprehensive comparison between various selection techniques of the best feature vector for the most efficient classification is tackled based on size of selected feature vector, processing time and success of classification. Results of this study can be integrated into a smart automatable tool based on recent data mining techniques that would provide an efficient and prompt identification for the nature of incipient hazards due to lack in insulation integrity. [ABSTRACT FROM PUBLISHER]

Over the last decade, dibenzyl-disulphide was found to be present in a large number of mineral insulating oils. This sulfur compound tends to react with the copper of the windings, forming harmful byproducts, such as Cu2 S. Different techniques to overcome the problem, including metal deactivation, oil change, and chemical treatment, have been applied. The long-term effectiveness of these techniques is examined and compared. [ABSTRACT FROM AUTHOR]

The relationships between the total copper content, both in dissolved and suspended form, and the dielectric loss characteristics were examined in transformer-type oils. It was established that the dielectric losses in the oils are a function of the total copper content. However, no measurable influence of the sulfur corrosivity of the oils was detected upon the magnitude of the dielectric losses in the oils, notwithstanding that the conductive copper sulfide deposits on the paper tapes impregnated with corrosive sulfur oils resulted in the tapes having highly augmented dielectric losses. It was demonstrated that oil chemical treatment processes that are capable of reducing copper content in the oil, result in a significant improvement of the dielectric losses of the oil. [ABSTRACT FROM AUTHOR]

The behavior of corrosive sulfur in mineral oils is examined in terms of the failures observed in transformers, the surfaces of the copper sulfide covered conductors and degraded paper insulating tapes. The role of Dissolved Gas Analysis (DGA) in the evaluation of the risk of copper sulfide formation is described. The degree of corrosiveness of some sulfur compounds is examined and compared using a Kraft paper wrapped-copper test (Standard IEC 62535). The occurrence of DBDS as the most relevant corrosive compound is compared with the presence of other corrosive species in insulating mineral oils. A number of mitigation techniques for corrosive sulfur are described and evaluated. [ABSTRACT FROM AUTHOR]

The nature and causes of corrosive sulfur induced failures are examined in oil-filled transformers and shunt reactors. Copper sulfide, which is formed when the corrosive sulfur in a mineral oil reacts with the copper conductors, is likely to diffuse into the paper tapes insulating the conductors. Since copper sulfide is partially conducting, the dielectric losses of the contaminated oil-impregnated-paper tapes are markedly increased; paper tapes in close proximity to the copper conductors are found to attain tan 5 values > 1.0 even at room temperature. It is highly likely that thermal instabilities develop at those sites at operating temperatures, leading to increased loss currents and, ultimately, short circuits between the turns. This sequence of events is substantiated by evidence from the field, which indicates large areas of thermally degraded insulations and charred breakdown regions along the coils, the extent of which becomes more pronounced at higher operating temperatures (toward the top of the windings). [ABSTRACT FROM AUTHOR]

Acoustic measurements of partial discharge (PD) are employed to classify particles in transformer mineral oil according to material and size. Wavelet multi-resolution analysis data of the acoustic signals together with higher order statistics of the particle intercollision times and magnitudes comprise the input features to a Support Vector Machine (SVM) classifier. The training and validation measurement data, which are contaminated by time varying noise, are first filtered using wavelet decomposition. Results indicate that the SVM algorithm with the selected features provides a remarkably high success rate when classifying particles by size and material type. A potentially significant conclusion is that acoustic measurements alone are by themselves effective in classifying discharged particles in terms of the foregoing selected features. The proposed algorithm can be employed to enhance quality control procedures based on acoustic measurements of partial discharge. [ABSTRACT FROM AUTHOR]

Focuses on a study which examined the mechanism of partial discharge (PD) or corona discharges. Comparison of PD detection and measurement procedures for cables, capacitors, transformers and rotating machines; PD pattern recognition; Development and utilization of intelligent machines.

An introduction to the journal is presented in which the guest editors discuss the papers that focus on dielectric liquids, on conduction mechanisms governing the dielectric behavior of mineral oils, and on synthetic and natural ester fluids that are used in low power transformers.