Particle Detection in Oil Using Acoustic and Electrical Based Techniques in Correlation with an Inference Method

Partial discharge (PD) measurement is a proven flaw detection technique for finding defects in the insulating materials and thus accessing the integrity of the tested insulation. The different PD measurement techniques as well as the interpretation of the measurement results have been important research topics in the recent years. This paper contributes to the detection of the presence of free conducting particles in oil insulated apparatus. Acoustic and electrical based PD measurements were undertaken by deliberately introducing metallic particles of various compositions and dimensions in oil. The acoustic signal, formed due to the statistical analysis of the particle impact momentum during motion in oil was used as the basis for designing and training an intelligent classifier for disclosing the characteristics of the contaminating particle. It is proven that measurements and simulation results of the produced acoustics are in homogeneity