Power Insulator Defect Detection

Insulators are the key components of the power system. Insulator failures can cause outages and affect the safety and power supply. It is important to perform insulator defect detection. Due to the collection of insulator images by moving catenary inspection vehicles, the consistency of the images is poor, and the number of insulator defect samples is very small. The conventional template matching cannot meet the requirements of insulator defect detection. This project proposes an automatic device to detect defects for different types of insulators.

Chuande Liu
Chuande Liu
Lecturer

My current research interests focus on sensory-based manipulation, robotic motion planning, AI-augmented visual servoing and under-actuated robot systems.

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