Target detection of helicopter electric power inspection based on the feature embedding convolution model.

ABSTRACT: This study aims to improve the helicopter electric power inspection process by using the feature embedding convolution (FEC) model to solve the problems of small scope and poor real-time inspection. First, simulation experiments and model analysis determine the keyframe and flight trajectory. Second, an improved FEC model is proposed, extracting features from aerial images in large ranges in real time and accurately identifying and classifying electric power inspection targets. In the simulation experiment, the accuracy of the model in electric power circuit and equipment detection is improved by 30% compared with the traditional algorithm, and the inspection range is expanded by 26%. In addition, this study further optimizes the model with reinforcement learning technology, conducts a com

SUBMITTER: Liu D 

PROVIDER: S-EPMC11458054 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature