Switch defect detection method based on LabVIEW deep learning

The invention provides a switch defect detection method based on LabVIEW deep learning. The method comprises the following steps: S1, image acquisition: acquiring a to-be-detected switch image; s2, image denoising: filtering the to-be-detected image to obtain a denoised image; s3, image enhancement: carrying out image enhancement on the denoised image; s4, edge detection: identifying defects in the image by adopting a Sobel edge detection operator, and performing edge identification on the defects; and S5, identification and classification: carrying out deep learning training on the defects after edge identification by adopting LabVIEW to obtain defect information. According to the method, intelligent identification of various switch defects is realized by utilizing image acquisition, image denoising, image enhancement, edge detection and identification classification, and a manual detection and identification process is replaced, so that the labor cost is reduced. 本发明提供了一种基于LabVIEW深度学习的开关缺陷检测方法，包括：S1图像采集：获取待