A Simple Model for Fault Detection of UAV Photoelectric Load Based on Image Classification

A simple image-based unmanned aerial vehicle (UAV) optoelectronic load fault detection model is proposed to address the types of distortion that occur during the imaging process due to device failures. The model adopts the classic AlexNet network, adjusts the key parameters of the network, adds a BN layer, and then optimizes the original network using LeakyReLU, achieving a fault detection model based on image classification. The experimental results show that the clas-sification accuracy of our model has reached over 90%, which is higher than the comparison method. Moreover, the training samples required for our model are small and easy to implement.