The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can caus...The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.展开更多
The spin-exchange relaxation-free atomic gyroscope,with its exceptionally high theoretical precision,demonstrates immense potential to become the next-generation strategic-grade gyroscope.However,due to technological ...The spin-exchange relaxation-free atomic gyroscope,with its exceptionally high theoretical precision,demonstrates immense potential to become the next-generation strategic-grade gyroscope.However,due to technological noise,there is still a significant gap between its actual precision and theoretical precision.This study identifies the key factor limiting the precision of the SERF gyroscope as coupling noise.By optimizing the detection loop structure,a distinction between the dual-axis signals'response to optical and magnetic fields was achieved-where the optical errors responded similarly,while the response to magnetic noise was opposite.Based on the differences in the optical-magnetic response of the dual-axis signals,empirical mode decomposition was used to decompose the dual-axis gyroscope signals into multiple intrinsic mode functions,and Allan deviation analysis was applied to analyze the noise characteristics of the intrinsic mode functions over various periods.This study successfully reveals that optical errors caused by thermal-optical coupling and long-period magnetic noise induced by thermal-magnetic coupling are the dominant factors limiting the long-term stability of the SERF gyroscope.Based on these analyses,the study concludes that to achieve strategic-grade precision for the SERF gyroscope,it is essential to effectively address the noise issues caused by multi-physical field couplings.展开更多
Because of an unfortunate mistake during the production of this article,the Acknowledgements have been omitted.The Acknowledgements are added as follows:Sasan YAZDANI would like to thank the Scientific and Technologic...Because of an unfortunate mistake during the production of this article,the Acknowledgements have been omitted.The Acknowledgements are added as follows:Sasan YAZDANI would like to thank the Scientific and Technological Research Council of Turkey(TÜB˙ITAK)for receiving financial support for this work through the 2221 Fellowship Program for Visiting Scientists and Scientists on Sabbatical Leave(Grant ID:E 21514107-115.02-228864).Sasan YAZDANI also expresses his gratitude to Sahand University of Technology for granting him sabbatical leave to facilitate the completion of this research.展开更多
提出了一种基于M u lti-A gen t的虚拟维修训练系统(VM TS)结构框架,整个系统分别由主控A gen t、仿真A gen t、和接口A gen t3个具有交互作用的A gen t组成,从而将虚拟维修训练系统的开发转化为一个多A gen t系统的设计与开发。基于多A...提出了一种基于M u lti-A gen t的虚拟维修训练系统(VM TS)结构框架,整个系统分别由主控A gen t、仿真A gen t、和接口A gen t3个具有交互作用的A gen t组成,从而将虚拟维修训练系统的开发转化为一个多A gen t系统的设计与开发。基于多A gen t的框架结构可实现受训者的智能模型及虚拟训练场景中虚拟物体的行为模型,从而可以提高VM TS的健壮性和可重用性。基于A gen t的概念模型实现了A gen t之间的交互和协作,并介绍了主控A gen t和仿真A gen t的具体实现方法。展开更多
基金Projects(U22B2084,52275483,52075142)supported by the National Natural Science Foundation of ChinaProject(2023ZY01050)supported by the Ministry of Industry and Information Technology High Quality Development,China。
文摘The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.
基金supported by Hefei National Laboratory,Innovation Program for Quantum Science and Technology(2021ZD0300400/2021ZD0300402)the Beijing Natural Science Foundation(3252013)the China Postdoctoral Science Foundation(2024T171116).
文摘The spin-exchange relaxation-free atomic gyroscope,with its exceptionally high theoretical precision,demonstrates immense potential to become the next-generation strategic-grade gyroscope.However,due to technological noise,there is still a significant gap between its actual precision and theoretical precision.This study identifies the key factor limiting the precision of the SERF gyroscope as coupling noise.By optimizing the detection loop structure,a distinction between the dual-axis signals'response to optical and magnetic fields was achieved-where the optical errors responded similarly,while the response to magnetic noise was opposite.Based on the differences in the optical-magnetic response of the dual-axis signals,empirical mode decomposition was used to decompose the dual-axis gyroscope signals into multiple intrinsic mode functions,and Allan deviation analysis was applied to analyze the noise characteristics of the intrinsic mode functions over various periods.This study successfully reveals that optical errors caused by thermal-optical coupling and long-period magnetic noise induced by thermal-magnetic coupling are the dominant factors limiting the long-term stability of the SERF gyroscope.Based on these analyses,the study concludes that to achieve strategic-grade precision for the SERF gyroscope,it is essential to effectively address the noise issues caused by multi-physical field couplings.
文摘Because of an unfortunate mistake during the production of this article,the Acknowledgements have been omitted.The Acknowledgements are added as follows:Sasan YAZDANI would like to thank the Scientific and Technological Research Council of Turkey(TÜB˙ITAK)for receiving financial support for this work through the 2221 Fellowship Program for Visiting Scientists and Scientists on Sabbatical Leave(Grant ID:E 21514107-115.02-228864).Sasan YAZDANI also expresses his gratitude to Sahand University of Technology for granting him sabbatical leave to facilitate the completion of this research.
文摘提出了一种基于M u lti-A gen t的虚拟维修训练系统(VM TS)结构框架,整个系统分别由主控A gen t、仿真A gen t、和接口A gen t3个具有交互作用的A gen t组成,从而将虚拟维修训练系统的开发转化为一个多A gen t系统的设计与开发。基于多A gen t的框架结构可实现受训者的智能模型及虚拟训练场景中虚拟物体的行为模型,从而可以提高VM TS的健壮性和可重用性。基于A gen t的概念模型实现了A gen t之间的交互和协作,并介绍了主控A gen t和仿真A gen t的具体实现方法。
