AUTOMATIC DETECTION METHOD OF BIRDS NEST ON TRANSMISSION LINE TOWER

In this paper,we advocate that the Bird disruption to transmission line tower is becoming more frequent as the number of high-voltage transmission lines increases. On transmission line tower, some birds build their nests. The birds' nests serve as conductors during rainstorms, causing power lines to trip. In a dry climate, the branches of the bird's nest are also vulnerable to burning, which not only disrupts regular power supply but also poses a major security danger. As a result, the research issue of identifying and finding bird nests on transmission lines and poles is of considerable importance in order to ensure the stable and efficient functioning of transmission line tower, as well as to minimise the negative effects of bird activities on transmission lines and other facilities is of great scientific importance and practical significance. The identification of a bird's nest on a high-voltage transmission line is an issue of image classification and target detection. As a result, our project is built on a CNN convolution neural network-based automatic detection system of a bird's nest on a transmission line tower. Using photographs taken with drones, this approach will automatically detect the bird's nest on the transmission line tower. Unsupervised learning is used to train the algorithm. This approach has a greater applicability and generalisation ability than the conventional nest detection method. It provides scientific assistance in evaluating bird behaviour and implementing appropriate preventative steps.