Infrared detection method based on Faster R-CNN image processing for abnormal equipment in substation
Aiming at the problem of low intelligence in the analysis and processing of infrared monitoring images for primary equipment within intelligent substations,a Faster R-CNN-based infrared detection image analysis method for abnormal equipment within substations was proposed to realize the intelligent identification and cause analysis of faulty equipment in substations.The infrared images collected by the remote terminal unit(RTU)were preprocessed,and the substation equipment in images was identified.The OSTU algorithm in combination with the image gray value was used to rectify and segment image.Faster R-CNN was used to distinguish whether the equipment was in fault state and analyze the cause.Experimental results show that the as-proposed method has a recognition accuracy of more than 90%for a variety of faulty equipment,and has a comparatively excellent robustness.
万方数据
维普
