LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Intelligent fault detection of high voltage line based on the Faster R-CNN

Photo from wikipedia

Abstract To realize intelligent fault detection of high voltage line, a deep convolution neural network method based on Faster R-CNN method is proposed to locate the broken insulators and bird… Click to show full abstract

Abstract To realize intelligent fault detection of high voltage line, a deep convolution neural network method based on Faster R-CNN method is proposed to locate the broken insulators and bird nests. With the region proposal network, the Faster R-CNN chooses a random region in the features of the image as the proposal region, and trains them to get the corresponding category and location for a certain component in the image. Since the internal and regional features of the image can be learned, the Faster R-CNN method transforms the problem of target classification into the problem of target detection and recognition. Based on the ResNet-101 network model, the damage of insulators and bird nests in the electric power line can be located effectively.

Keywords: intelligent fault; faster cnn; line; fault detection; detection high; detection

Journal Title: Measurement
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.