Status recognition method for protecting panel of substation equipment with a mobile phone image
Abstract
Protecting panels in substations ensure the stable operation of electrical equipment, which is of great significant to the local electrical power system. In order to reduce the manual intervention and improve the efficiency, we propose a vision-based status recognition method for protecting panels which can be used in automatic inspection equipment. The approach is divided into three stages: pre-processing, switch localization and status recognition. During the preprocessing, the image is firstly wrapped into the front view with inverse perspective transformation (IPM), with the help of a set of four artificial auxiliary marks. Meanwhile, a ROI region is extracted from the wrapped image which discards most of the trivial context. Secondly, the gradient intensity feature is calculated to locate switches on a panel. After projecting the gradient intensity image horizontally and vertically, the distribution of the switches is determined by respectively analyzing the both directional projection curves. Finally, a SVM classifier is trained to recognize the status of the switches on a protecting panel. The input of the classifier is the gradient orientation feature extracted from a normalized single switch region, and the output is the connected or disconnected states of the switch. Experiments show that our approach has low time consumption and achieves an accurate recognition rate of 99%.
- Publication:
-
Tenth International Conference on Graphics and Image Processing (ICGIP 2018)
- Pub Date:
- May 2019
- DOI:
- 10.1117/12.2524168
- Bibcode:
- 2019SPIE11069E..3EZ