With the increasing requirements of precision mechanical systems in electronic packaging,ultra-precision machining,biomedicine and other high-tech fields,it is necessary to study a precision two-stage amplification mi...With the increasing requirements of precision mechanical systems in electronic packaging,ultra-precision machining,biomedicine and other high-tech fields,it is necessary to study a precision two-stage amplification micro-drive system that can safely provide high precision and a large amplification ratio.In view of the disadvantages of the current two-stage amplification and micro-drive system,such as poor security,low motion accuracy and limited amplification ratio,an optimization design of a precise symmetrical two-stage amplification micro-drive system was completed in this study,and its related performance was studied.Based on the guiding principle of the flexure hinge,a two-stage amplification micro-drive mechanism with no parasitic motion or non-motion direction force was designed.In addition,the structure optimization design of the mechanism was completed using the particle swarm optimization algorithm,which increased the amplification ratio of the mechanism from 5 to 18 times.A precise symmetrical two-stage amplification system was designed using a piezoelectric ceramic actuator and two-stage amplification micro-drive mechanism as the micro-driver and actuator,respectively.The driving,strength,and motion performances of the system were subsequently studied.The results showed that the driving linearity of the system was high,the strength satisfied the design requirements,the motion amplification ratio was high and the motion accuracy was high(relative error was 5.31%).The research in this study can promote the optimization of micro-drive systems.展开更多
为评估交通管控策略的环境效益,提出有效融合微观交通仿真模型和微观车辆排放模型的方法。利用VISSIM平台构建案例微观交通仿真模型,提出基于轨迹数据的不同速度区间的加减速特征,应用K-means聚类方法划分4种驾驶行为,通过驾驶特性标定...为评估交通管控策略的环境效益,提出有效融合微观交通仿真模型和微观车辆排放模型的方法。利用VISSIM平台构建案例微观交通仿真模型,提出基于轨迹数据的不同速度区间的加减速特征,应用K-means聚类方法划分4种驾驶行为,通过驾驶特性标定仿真模型全局参数,描述了参数总敏感度以及参数之间相互作用的敏感度。利用DBSCAN(density-based spatial clustering of applications with noise)聚类分析并标定局部参数值,优化了参数标定流程。计算仿真轨迹工况,本地化MOVES(motor vehicle emission simulator)微观排放模型,得到交叉口不同流向和不同驾驶行为下的HC、CO、NO_(x)、CO_(2)排放。研究表明:仿真模型优化效果显著,所提方法可精确识别高排放的空间位置,解析排放与驾驶行为之间的联系。应用DBSCAN聚类分析参数寻优值有助于实现自动化标定流程,全局参数标定将速度分布χ^(2)误差由0.6327降至0.1306,加速度分布χ^(2)误差由0.1441降至0.0528,对于环境视角下仿真模型构建至关重要。展开更多
基金The research was funded by the National Natural Science Foundation of China,No.51805428Innovation Capability Support Plan of Shaanxi Province,No.2021 TD-27.
文摘With the increasing requirements of precision mechanical systems in electronic packaging,ultra-precision machining,biomedicine and other high-tech fields,it is necessary to study a precision two-stage amplification micro-drive system that can safely provide high precision and a large amplification ratio.In view of the disadvantages of the current two-stage amplification and micro-drive system,such as poor security,low motion accuracy and limited amplification ratio,an optimization design of a precise symmetrical two-stage amplification micro-drive system was completed in this study,and its related performance was studied.Based on the guiding principle of the flexure hinge,a two-stage amplification micro-drive mechanism with no parasitic motion or non-motion direction force was designed.In addition,the structure optimization design of the mechanism was completed using the particle swarm optimization algorithm,which increased the amplification ratio of the mechanism from 5 to 18 times.A precise symmetrical two-stage amplification system was designed using a piezoelectric ceramic actuator and two-stage amplification micro-drive mechanism as the micro-driver and actuator,respectively.The driving,strength,and motion performances of the system were subsequently studied.The results showed that the driving linearity of the system was high,the strength satisfied the design requirements,the motion amplification ratio was high and the motion accuracy was high(relative error was 5.31%).The research in this study can promote the optimization of micro-drive systems.
文摘为评估交通管控策略的环境效益,提出有效融合微观交通仿真模型和微观车辆排放模型的方法。利用VISSIM平台构建案例微观交通仿真模型,提出基于轨迹数据的不同速度区间的加减速特征,应用K-means聚类方法划分4种驾驶行为,通过驾驶特性标定仿真模型全局参数,描述了参数总敏感度以及参数之间相互作用的敏感度。利用DBSCAN(density-based spatial clustering of applications with noise)聚类分析并标定局部参数值,优化了参数标定流程。计算仿真轨迹工况,本地化MOVES(motor vehicle emission simulator)微观排放模型,得到交叉口不同流向和不同驾驶行为下的HC、CO、NO_(x)、CO_(2)排放。研究表明:仿真模型优化效果显著,所提方法可精确识别高排放的空间位置,解析排放与驾驶行为之间的联系。应用DBSCAN聚类分析参数寻优值有助于实现自动化标定流程,全局参数标定将速度分布χ^(2)误差由0.6327降至0.1306,加速度分布χ^(2)误差由0.1441降至0.0528,对于环境视角下仿真模型构建至关重要。
