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作 者:谷留涛 张卫平 卢浩琳 吴雨婷 范重阳 GU Liutao;ZHANG Weiping;LU Haolin;WU Yuting;FAN Chongyang(National Key Laboratory of Science and Technology on Micro/Nano Fabrication,Shanghai 200240,China;Department of Micro/Nano Electronics,Shanghai Jiao Tong university,Shanghai 200240,China)
机构地区:[1]微米纳米加工技术国家级重点实验室,上海200240 [2]上海交通大学电子信息与电气工程学院微纳电子学系,上海200240
出 处:《中国惯性技术学报》2023年第5期490-494,共5页Journal of Chinese Inertial Technology
基 金:国家自然科学基金(61574093)。
摘 要:针对有限元分析方法中工作模态识别问题,提出一种基于边缘提取的MEMS谐振器谐振模态识别算法。首先使用图像灰度化、颜色翻转、边缘提取算法对微谐振器谐振模态的边缘形状进行提取,减少内部结构对识别算法的影响。然后计算不同模态边缘形状的圆形度和偏心率,并根据这两个图像特征实现了在有限元分析过程中对获取的微谐振器谐振模态的识别分类。使用随机产生的1000个不同结构参数的鸟巢型微谐振器的10000个谐振模态对算法进行了测试,其中对于椭圆形工作模态的识别准确度可以达到100%,其他模态的识别准确度超过99%。最后利用所提算法搭建了一套通用的有限元计算平台,该平台在没有人为干预条件下可以实现大规模样本的快速有限元分析,为微谐振器结构的优化设计提供了一种可靠的工具。In order to realize the identification of working modes in the finite element analysis method,a resonant mode identification algorithm for MEMS resonators based on edge extraction is proposed.Firstly,the image graying,color flipping and edge extraction algorithms are used to extract the edge shape of the resonant mode of the micro resonator,so as to reduce the influence of the internal structure on the identification algorithm.Then the roundness and eccentricity of different mode edge shapes are calculated,and the identification and classification of the resonant modes of the micro resonator obtained in the finite element analysis process are realized according to these two image features.The algorithm is tested by using 10000 resonant modes of micromachined birdbath shell resonator with 1000 different structural parameters randomly generated.The identification accuracy of elliptical working modes can reach 100%,and that of other modes can exceed 99%.Finally,a set of general finite element computing platform is built by using the proposed algorithm.The platform can realize fast finite element analysis of large-scale samples without human intervention,which provides a reliable tool for the optimization design of micro resonator structure.
分 类 号:TP212[自动化与计算机技术—检测技术与自动化装置]
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