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The dielectric properties of oil-paper insulation degrade due to moisture ingression and ageing. This degradation significantly impacts the space charge accumulation and charge trapping behaviour in the insulation, which are vital parameters for insulation health under the high-voltage direct current environment. In this work, an improved model based on the isothermal relaxation current (IRC) has been developed to study the charge trapping behaviour of an oil pressboard under the influence of moisture and ageing. The conventional IRC model considers the total relaxation current because of charge de-trapping only. However, in the case of a composite dielectric like oil pressboard, dipolar relaxation also affects the relaxation current. In this work, a methodology has been proposed to investigate charge de-trapping behaviour of oil-pressboard insulation considering the dipole relaxation process from IRC measurements. For this purpose, frequency domain spectroscopy measurements and IRC measurements have been performed on oil-impregnated pressboard specimens carefully prepared in the laboratory having different ageing conditions and moisture contents. Results presented in this work depict that charge trapping parameters, i.e. the trap depth and trapped charge distribution are highly affected both by ageing and moisture. It was observed that ageing leads to the generation of deeper traps, while moisture mainly enhances the density of shallow traps.

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This paper presents a methodology of cross-wavelet transform aided Fischer linear discriminant analysis (FLDA)-based feature selection and classification for sensing simultaneous occurrence of multiple power quality disturbances. A linear support vector machine is used for classification of the extracted features as it suits well with FLDA. This scheme is implemented in a general purpose microcontroller as a standalone module and the performance of the standalone module for sensing simultaneous occurrence of multiple power quality disturbances is judged by both online and offline testing. Results show that the performance is comparable with the results reported in the literatures. Moreover, the scheme is immune to real life uncorrelated noises due to incorporation of cross spectrum analysis in the feature extraction phase. The present method is generic in nature and can be implemented for any other microcontrollerbased applications addressing topologically similar problems. IndexTerms-Fischer linear discriminant analysis, microcontroller, cross wavelet transform, multiple power quality disturbance, support vector machine, standalone module.

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