Research on Vision Detection Technology for Defects in Display Backplate Embedded Component Assembly
To address the issue of low efficiency and high subjectivity in manual visual inspection of metal insert assembly defects on display backplates,this paper proposes a visual inspection method for detecting assembly defects of metal inserts on display backplates.By using preprocessing techniques,high-quality im-ages of the assembly area are obtained,and the dung beetle optimizer ( DBO) is applied to optimize the two-dimensional Otsu method to segment the inserts.The shape and position features of the inserts are ex-tracted and normalized for fusion,and then input into the DBO-optimized BP neural network for defect rec-ognition.Experimental results show that this method achieves an accuracy of 97.5％ on the dataset,and the performance of using DBO-optimized two-dimensional Otsu and BP neural network is superior to the opti-mization using particle swarm optimization ( PSO) and genetic algorithm ( GA) for both segmentation and classification problems.The proposed method can effectively detect assembly defects and is adaptable to factory noise and lighting condition changes,meeting the real-time requirements of enterprise production.
万方数据
维普
