Improvement of Insulator Image Processing Using Deep Learning Algorithms

Insulator fault within the transmission lines is the main consideration in power transmission accidents. The photographs captured from the aerial inspection will be utilized to detect the fault of insulators for further maintenance. To verify the effectiveness of insulator detection methods supported by deep learning, we tested and compared the great performance of 4 state-of-the-art deep-learning-based detectors with different characteristics. Damaged insulators seriously threaten the safe operation of power transmission lines. This paper proposes an insulation fault detection method supported by some deep learning state-of-art algorithms. This aim provides a reference for intelligent inspection and defect detection of insulators and vibration dampers on transmission lines.