A novel approach for inspecting the condition of porcelain insulators based on statistical analysis of electromagnetic radiations of live insulators is demonstrated in this thesis. Physical defects such as puncture and contamination can degrade the insulators performance and result in power outages, potentiating costs to utilities. Therefore, condition assessment of line insulators has always been one of the most important aspects of maintenance programs in power networks. Realistic replicas of punctured and contaminated insulators were created in the High Voltage Lab at University of Manitoba, following the IEC standards. These defective insulators were tested under high voltage stress while the electromagnetic radiations originated from the partial discharge activities on the insulators were captured using electromagnetic sensors. During the experimental part of this thesis, a multitude of tests were conducted and resulted in measuring and recording a total of 410,000 cycles of discharge activities. The feature extraction algorithm, developed as part of this thesis, calculates the statistical features of the phase resolved interpretation of partial discharge (PD) pulses. The results of analyzing the extracted features from the radiated signature of defective insulators indicate that the scale and shape parameters of a two sided Weibull distribution function fit to the recorded measurement entail distinct information about the source of discharges that can be used to identify the source of defects. Based on the library of features extracted from the recorded electromagnetic radiations, a support vector machine (SVM) classier, developed as part of this thesis, can successfully classify the radiation signature of punctured and contaminated insulators. Therefore, the main outcome of this research was introducing a novel porcelain insulator inspection technique that can remotely differentiate the defective punctured and contaminated insulators using their electromagnetic radiation signature in a laboratory environment. By utilizing the signature of common discharge activities present in the recorded signature of all tested insulators, a gating algorithm was developed which improved the successful classification rate from 51 % to 75%. The inspection technique proposed in this research can eliminate the safety hazards involved in the live maintenance of line insulators, lower the maintenance costs, and improve the inspection efficiency considering the conventional labour intensive live maintenance assessments. / February 2016