Short Time Modified Hilbert Transform-Aided Sparse Representation for Sensing of Overhead Line Insulator Contamination

The service condition of the overhead line insulators is significantly affected by the contamination deposited on the insulator surfaces. The reliability of transmission lines is therefore affected in the case of insulator failures. Leakage current signature has widely been reported to be a good indicator of the contamination level on the insulators. Different characteristics extracted from leakage current can be used to sense and classify insulators based on their contamination levels. In this paper, a method based on short time modified Hilbert transform (STMHT) and sparse representation-based contamination level sensing of overhead line insulator has been proposed. STMHT is capable of enhancing the local characteristic of the leakage current waveform and provides a good technique for differentiating between similar kinds of data. Sparse representation-based classification is used for classification of the extracted features. Results show that the performance is comparable or even better with respect to the results reported in the literature. The present method is generic in nature and can be implemented for any other applications addressing topologically similar problems. All necessary experiments are conducted based on IEC 60507 standard.