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作 者:李萍[1] 徐安林[1] LI Ping;XU Anlin(Wuxi Institute of Technology,Wuxi 214121,China)
出 处:《现代电子技术》2016年第18期107-109,共3页Modern Electronics Technique
基 金:国家自然科学基金资助项目(11171316);江苏省高等职业院校国内高级访问学者计划资助项目(2015FX082);江苏高校品牌专业建设工程资助项目PESP(PPZY2015C240)
摘 要:研究了基于BP神经网络的智能制造系统图像识别技术。在当前制造业系统设计中,由于图像资源结构复杂,通过BP神经网络,有助于提取图像特征、优选特征向量组成方案,从而优化实现智能制造系统图像识别技术。该文基于BP神经网络设计了一个智能制造系统,并采用B/S模式设计系统结构,制造系统的图像识别技术,可以降低系统在使用过程中18.0的冗余度,同时也提升该系统12.0%的应用性能。结论表明,基于BP神经网络设计实现智能制造系统图像识别技术,可以使系统的平台更具智能性,符合制造业信息化发展要求,提升智能制造系统图像识别性能。The aim of this paper is to study the image recognition technology of intelligent manufacturing system based onBP neural network. With the development of BP neural network,the manufacturing industry in China towards to information de?velopment has become a major trend. In the system design of current manufacturing industry,since the image resources struc?ture is complex,the BP neural network is employed to extract the image features and optimize the composing solution of featurevectors,so as to optimize and realize the image recognition technology of intelligent manufacturing system. The results show thatthe BP neural network based image recognition technology of intelligent manufacturing system can reduce the system redundancyof 18.0 in using process,and improve the system application performance of 12.0%. The conclusion shows that the image recog?nition technology based on BP neural network can make the system platform more intelligent,meet the development require?ments of manufacturing information,improve the image recognition performance of intelligent manufacturing system,and play apositive impact.
关 键 词:B/S模式 智能制造系统 BP神经网络 图像识别技术
分 类 号:TN926.34[电子电信—通信与信息系统]
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