中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Real-time Tuning of Cavity Filters by Learning from Human Experience: A Vector Field Approach

文献类型:会议论文

作者Zhiyang Wang; Shaokun Jin; Jingfeng Yang; Xinyu Wu; Yongsheng Ou
出版日期2016
会议名称World Congress on Intelligent Control and Automation(WCICA)
会议地点中国桂林
英文摘要The technique of tuning a cavity filter is purely a rule of thumb: only experienced tuning engineer is competent to the task. However, with the great development of the communication industry and the rapid increasing of production capacity, the need for tuning technicians becomes urgent. It is meaningful to replace this traditional manual tuning task with some more advanced and automatic methods. We hereby propose a real-time computer-aided tuning method based on the vector field approximating approach, which can be applied in robotic tuning systems in the near future. In this paper, we first make a literature review on some previous intelligent cavity filter tuning solutions. Then the method of employing vector fields to represent the change of S-parameters is proposed. We provide concrete procedures to drive the S-parameters curves to approximate towards the target. In the end, we give the experimental results which validate the flexibility of the method
收录类别EI
语种英语
源URL[http://ir.siat.ac.cn:8080/handle/172644/10131]  
专题深圳先进技术研究院_集成所
作者单位2016
推荐引用方式
GB/T 7714
Zhiyang Wang,Shaokun Jin,Jingfeng Yang,et al. Real-time Tuning of Cavity Filters by Learning from Human Experience: A Vector Field Approach[C]. 见:World Congress on Intelligent Control and Automation(WCICA). 中国桂林.

入库方式: OAI收割

来源:深圳先进技术研究院

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