The detection of steel surface anomalies has become an industrial challenge due to variations in production equipment,processes,and characteristics.To alleviate the problem,this paper proposes a detection and localiza...The detection of steel surface anomalies has become an industrial challenge due to variations in production equipment,processes,and characteristics.To alleviate the problem,this paper proposes a detection and localization method combining 3D depth and 2D RGB features.The framework comprises three stages:defect classification,defect location,an d warpage judgment.The first stage uses a dataefficient image Transformer model,the second stage utilizes reverse knowledge distillation,and the third stage performs feature fusion using3D depth and 2D RGB features.Experimental results show that the proposed algorithm achieves relatively high accuracy and feasibility,and can be effectively used in industrial scenarios.展开更多
为提高应用文编写效率,提出一种融合大语言模型(large language model,LLM)与向量知识库(vector knowledge base)的应用文自动生成框架.根据目标应用场景,以人工编写的标准应用文为范本,构建结构化辅助生成文件,并建立相应类型应用文的...为提高应用文编写效率,提出一种融合大语言模型(large language model,LLM)与向量知识库(vector knowledge base)的应用文自动生成框架.根据目标应用场景,以人工编写的标准应用文为范本,构建结构化辅助生成文件,并建立相应类型应用文的向量知识库.利用目标类型应用文的章节标题和用户输入的关键信息在知识库中进行检索,匹配相关文段;设置提示词引导LLM,以召回的参考文段及用户输入的提示信息为参考,使用末级标题作为分割标志,分章节生成应用文文本;最终按规定格式整合全文并输出完整的目标应用文.以应急预案为例,在同一评价标准下使用ChatGPT-4Turbo进行评测,自动生成的应急预案高度趋近于人工编写的质量,二者的文档质量相似度达95.87%.所提方法能够在算力资源有限的情况下突破字数限制,生成符合基本标准的长篇幅应用文,可供人工参考或直接使用,极大提高了编写人员的工作效率.展开更多
Vision-based measurement technology benefits high-quality manufacturers through improved dimensional precision,enhanced geo-metric tolerance,and increased product yield.The monocular 3D structured light visual sensing...Vision-based measurement technology benefits high-quality manufacturers through improved dimensional precision,enhanced geo-metric tolerance,and increased product yield.The monocular 3D structured light visual sensing method is popular for detecting online parts since it can reach micron-meter depth accuracy.However,the line-of-sight requirement of a single viewpoint vision system often fails when hiding occurs due to the object’s surface structure,such as edges,slopes,and holes.To address this issue,a multi-view 3D structured light vi-sion system is proposed in this paper to achieve high accuracy,i.e.,Z-direction repeatability,and reduce hiding probability during mechani-cal dimension measurement.The main contribution of this paper includes the use of industrial cameras with high resolution and high frame rates to achieve high-precision 3D reconstruction.Moreover,a multi-wavelength(heterodyne)phase expansion method is employed for high-precision phase calculation.By leveraging multiple industrial cameras,the system overcomes field of view occlusions,thereby broadening the 3D reconstruction field of view.Finally,the system achieves a Z-axis repetition accuracy of 0.48µm.展开更多
基金supported by ZTE Industry-University-Institute Cooperation Funds under Grant No. HC-CN-20221107001。
文摘The detection of steel surface anomalies has become an industrial challenge due to variations in production equipment,processes,and characteristics.To alleviate the problem,this paper proposes a detection and localization method combining 3D depth and 2D RGB features.The framework comprises three stages:defect classification,defect location,an d warpage judgment.The first stage uses a dataefficient image Transformer model,the second stage utilizes reverse knowledge distillation,and the third stage performs feature fusion using3D depth and 2D RGB features.Experimental results show that the proposed algorithm achieves relatively high accuracy and feasibility,and can be effectively used in industrial scenarios.
文摘为提高应用文编写效率,提出一种融合大语言模型(large language model,LLM)与向量知识库(vector knowledge base)的应用文自动生成框架.根据目标应用场景,以人工编写的标准应用文为范本,构建结构化辅助生成文件,并建立相应类型应用文的向量知识库.利用目标类型应用文的章节标题和用户输入的关键信息在知识库中进行检索,匹配相关文段;设置提示词引导LLM,以召回的参考文段及用户输入的提示信息为参考,使用末级标题作为分割标志,分章节生成应用文文本;最终按规定格式整合全文并输出完整的目标应用文.以应急预案为例,在同一评价标准下使用ChatGPT-4Turbo进行评测,自动生成的应急预案高度趋近于人工编写的质量,二者的文档质量相似度达95.87%.所提方法能够在算力资源有限的情况下突破字数限制,生成符合基本标准的长篇幅应用文,可供人工参考或直接使用,极大提高了编写人员的工作效率.
基金supported by the 2023 Guangdong Basic and Applied Basic Research Fund Regional Joint Fund Key Project under Grant No. 2023B15151200172023 Key Project of Guangdong Provincial Department of Education for General Universities under Grant No. 2023ZDZX3024ZTE Industry-University-Institute Cooperation Funds under Grant No. K2133Z167
文摘Vision-based measurement technology benefits high-quality manufacturers through improved dimensional precision,enhanced geo-metric tolerance,and increased product yield.The monocular 3D structured light visual sensing method is popular for detecting online parts since it can reach micron-meter depth accuracy.However,the line-of-sight requirement of a single viewpoint vision system often fails when hiding occurs due to the object’s surface structure,such as edges,slopes,and holes.To address this issue,a multi-view 3D structured light vi-sion system is proposed in this paper to achieve high accuracy,i.e.,Z-direction repeatability,and reduce hiding probability during mechani-cal dimension measurement.The main contribution of this paper includes the use of industrial cameras with high resolution and high frame rates to achieve high-precision 3D reconstruction.Moreover,a multi-wavelength(heterodyne)phase expansion method is employed for high-precision phase calculation.By leveraging multiple industrial cameras,the system overcomes field of view occlusions,thereby broadening the 3D reconstruction field of view.Finally,the system achieves a Z-axis repetition accuracy of 0.48µm.
