文章詳目資料

Journal of Computers EIMEDLINEScopus

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篇名 Research on Intelligent Assembly Strategy and Workpiece Grasping Method for Industrial Robots Based on Deep Learning
卷期 34:3
作者 Jie YuXi-Lin LiCai-Wen NiuYu-Xin ZhangShu-Hui Xu
頁次 315-324
關鍵字 deep learningassembly strategmachine viconvolutional neural networkEIMEDLINEScopus
出刊日期 202306
DOI 10.53106/199115992023063403023

中文摘要

英文摘要

To improve the recognition efficiency of surface defects in castings, this article first uses median filtering algorithm to denoise the defect image to distinguish between defects and background. Then, gray threshold method is used to segment the image, and the processed image is sent to the improved RefineDet network structure. Improving the RefineDet network structure mainly improves the network depth and incorporates dataset augmentation algorithms. Finally, an experimental platform was built to train, recognize, and compare the collected image dataset. The results show that the accuracy of detecting porosity, blowhole, and flaw defects is 95.6% and 97.3% and 98.15%, the method proposed in this article is accurate and efficient.

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