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基于遗传算法的低频标准振动台簧片式回复结构优化
引用本文:张旭飞,张锋阳,李凯,权龙. 基于遗传算法的低频标准振动台簧片式回复结构优化[J]. 计量学报, 2021, 42(11): 1459-1465. DOI: 10.3969/j.issn.1000-1158.2021.11.08
作者姓名:张旭飞  张锋阳  李凯  权龙
作者单位:太原理工大学机械与运载工程学院,山西太原030024;太原理工大学新型传感器与智能控制教育部和山西省重点实验室,山西太原030024;太原理工大学机械与运载工程学院,山西太原030024
基金项目:国家自然科学基金(51805360); 山西省应用基础研究计划(201801D221229); 山西省高等学校科技创新项目(201802048); 中国博士后科学基金(2019T120196, 2018M640249); 山西省专利推广实施资助计划(20200703)
摘    要:为有效提高低频标准振动台簧片式回复结构的柔性导向性能及高频工作稳定性,分析了簧片式电磁振动台工作原理及其机电耦合简化模型,并通过Ansys模态和谐响应分析,得到不同尺寸组合回复簧片结构对振动台模态频率及输出特性的影响规律,结果表明:水平及侧簧片的宽度及厚度尺寸为主要影响因素。基于多目标遗传算法,迭代分析得到满足振动台输出特性要求的水平及侧簧片尺寸最优解,将回复簧片的第2阶扭曲模态频率提升到442.05Hz,相比最低值提高近一倍,有效扩展了振动台的稳定工作频率范围。

关 键 词:计量学  低频振动台  模态频率  遗传算法  簧片回复
收稿时间:2021-03-02

Optimization of Leaf-spring-type Recovery Mechanism for Low-frequency Standard Vibrator Based on Genetic Algorithm
ZHANG Xu-fei,ZHANG Feng-yang,LI Kai,QUAN Long. Optimization of Leaf-spring-type Recovery Mechanism for Low-frequency Standard Vibrator Based on Genetic Algorithm[J]. Acta Metrologica Sinica, 2021, 42(11): 1459-1465. DOI: 10.3969/j.issn.1000-1158.2021.11.08
Authors:ZHANG Xu-fei  ZHANG Feng-yang  LI Kai  QUAN Long
Affiliation:1. College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan, Shanxi 030024, China
2. Key Laboratory of Advanced Transducers and Intelligent Control System of Ministry of Education and Shanxi Province, Taiyuan University of Technology, Taiyuan, Shanxi 030024, China
Abstract:In order to effectively improve the flexible guiding performance and high-frequency working stability of the leaf spring recovery mechanism of the low-frequency standard vibrator, the working principle of the leaf-spring-type electromagnetic vibrator and its simplified electromechanical coupling model are analyzed. The influence of different combination of recovery spring sizes on the modal frequencies and output characteristics of the vibrator are obtained through the modal and harmonic response analyses based on Ansys. The results show that the width and thickness of the horizontal and side springs are the main influencing factors. Based on the multi-objective genetic algorithm, the optimal sizes of the horizontal and side springs are obtained iteratively under the condition of the vibrator output characteristics, and the second-order twisted mode frequency of the recovery spring is increased to 442.05Hz, which is nearly twice as much as the lowest value. The research results effectively expand the stable working frequency range and improve the working performance of the vibrator.
Keywords:metrology  low-frequency vibrator  modal frequency  genetic algorithm  leaf spring recovery  
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