Power Cabinet Door-opening State Recognition Technology Based on Edge Feature Extraction of Monocular Vision


With the increasing intelligent demand of substations, more and more machine vision technologies are applied in smart substations. This paper deals with the power cabinet door-opening state recognition based on edge feature extraction. Firstly, the substation patrol robot with machine vision is introduced, and the image acquirement and main processing flowchart including image line segment fitting of the power cabinet door-opening state is presented. Secondly, main algorithms, such as grey scale, image denoising, edge feature detection and Hough transform, used in the image feature extraction are provided. Finally, the proposed power cabinet door state recognition is implemented with real image of typical terminal box state, and the experimental results show that the proposed technology can identify the power cabinet door-opening state with accuracy as high as 99%.

9th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (IEEE-CYBER 2019)
Chuande Liu
Chuande Liu

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