A new hierarchical parameter estimation method for doubly fed induction generator （DFIG） and drive train system in a wind turbine generator （WTG） is proposed in this paper. Firstly, the parameters of the DFIG and ...A new hierarchical parameter estimation method for doubly fed induction generator （DFIG） and drive train system in a wind turbine generator （WTG） is proposed in this paper. Firstly, the parameters of the DFIG and the drive train are estimated locally under different types of disturbances. Secondly, a coordination estimation method is further applied to identify the parameters of the DFIG and the drive train simultaneously with the purpose of attaining the global optimal estimation results. The main benefit of the proposed scheme is the improved estimation accuracy. Estimation results confirm the applicability of the proposed estimation technique.展开更多
Automation advancements prompts the extensive integration of collaborative robot(cobot)across a range of industries.Compared to the commonly used design approach of increasing the payload-to-weight ratio of cobot to e...Automation advancements prompts the extensive integration of collaborative robot(cobot)across a range of industries.Compared to the commonly used design approach of increasing the payload-to-weight ratio of cobot to enhance load capacity,equal attention should be paid to the dynamic response characteristics of cobot during the design process to make the cobot more flexible.In this paper,a new method for designing the drive train parameters of cobot is proposed.Firstly,based on the analysis of factors influencing the load capacity and dynamic response characteristics,design criteria for both aspects are established for cobot with all optimization design criteria normalized within the design domain.Secondly,with the cobot in the horizontal pose,the motor design scheme is discretized and it takes the joint motor diameter and gearbox speed ratio as optimization design variables.Finally,all the discrete values of the optimization objectives are obtained through the enumeration method and the Pareto front is used to select the optimal solution through multi-objective optimization.Base on the cobot design method proposed in this paper,a six-axis cobot is designed and compared with the commercial cobot.The result shows that the load capacity of the designed cobot in this paper reaches 8.4 kg,surpassing the 5 kg load capacity commercial cobot which is used as a benchmark.The minimum resonance frequency of the joints is 42.70 Hz.展开更多
Purpose–In recent years,the rapid advancement of artificial intelligence(AI)has exerted profound impacts on and provided strong impetus to numerous fields in the industrial sector.Within the railway industry,AI has d...Purpose–In recent years,the rapid advancement of artificial intelligence(AI)has exerted profound impacts on and provided strong impetus to numerous fields in the industrial sector.Within the railway industry,AI has driven continuous upgrading and optimization of intelligent train control technology,thanks to its enhanced computational capabilities derived from advanced algorithms and models,as well as its role in improving safety performance.Integrating AI technology more extensively into train autonomous driving and control has thus become an inevitable trend in the global development of railways.Design/methodology/approach–This paper,therefore,conducts a comprehensive analysis of the development progress and current status of AI technology applications in the field of train driving and control on a global scale.It systematically sorts out and analyzes the advantages of various AI technologies and the positive impacts they bring to the upgrading of train control technology,elucidates the feasibility and future prospects of applying a range of emerging AI technologies from the perspective of technical theory and provides guidance for the intelligent development of this field from a practical perspective.Findings–The application of AI technology in the train driving and control field is still in its infancy.While a large number of AI technologies have been widely adopted,there remains significant room for further optimization and improvement of these technologies.Additionally,a variety of AI technologies that have been applied in other industrial sectors but not yet widely implemented in training autonomous driving and control have demonstrated tremendous development potential.Originality/value–The research findings provide references and guidance for advancing train control technology,promoting the digital transformation of railways,accelerating the overall optimization and upgrading of railway industry technologies,and facilitating the accelerated development of global railways.展开更多
列车司机驾驶仿真子系统是构建完备的列控仿真系统与功能测试环境的基础部分,该子系统有助于提高整个仿真与测试系统的真实性和可操作性。本文针对司机驾驶仿真子系统,从功能需求、列车速度模型建立、软件仿真等方面对该子系统进行分析...列车司机驾驶仿真子系统是构建完备的列控仿真系统与功能测试环境的基础部分,该子系统有助于提高整个仿真与测试系统的真实性和可操作性。本文针对司机驾驶仿真子系统,从功能需求、列车速度模型建立、软件仿真等方面对该子系统进行分析,引入AV8R-01型摇杆及SST辅助编程技术,利用Visual Studio 2010编程环境实现了该子系统。本文利用较低成本的硬件平台辅以软件界面代替传统的驾驶实物平台,在CTCS仿真测试与司机培训等仿真平台搭建过程中既节省了成本,又能够起到驾驶仿真的作用。展开更多
基金This research was supported by the National Natural Science Foundation of China （Major Program） （Grant Nos. 51190102 and 51207045）.
文摘A new hierarchical parameter estimation method for doubly fed induction generator （DFIG） and drive train system in a wind turbine generator （WTG） is proposed in this paper. Firstly, the parameters of the DFIG and the drive train are estimated locally under different types of disturbances. Secondly, a coordination estimation method is further applied to identify the parameters of the DFIG and the drive train simultaneously with the purpose of attaining the global optimal estimation results. The main benefit of the proposed scheme is the improved estimation accuracy. Estimation results confirm the applicability of the proposed estimation technique.
基金Supported by National Key Research and Development Program of China (Grant Nos.2022YFB4703000,2019YFB1309900)。
文摘Automation advancements prompts the extensive integration of collaborative robot(cobot)across a range of industries.Compared to the commonly used design approach of increasing the payload-to-weight ratio of cobot to enhance load capacity,equal attention should be paid to the dynamic response characteristics of cobot during the design process to make the cobot more flexible.In this paper,a new method for designing the drive train parameters of cobot is proposed.Firstly,based on the analysis of factors influencing the load capacity and dynamic response characteristics,design criteria for both aspects are established for cobot with all optimization design criteria normalized within the design domain.Secondly,with the cobot in the horizontal pose,the motor design scheme is discretized and it takes the joint motor diameter and gearbox speed ratio as optimization design variables.Finally,all the discrete values of the optimization objectives are obtained through the enumeration method and the Pareto front is used to select the optimal solution through multi-objective optimization.Base on the cobot design method proposed in this paper,a six-axis cobot is designed and compared with the commercial cobot.The result shows that the load capacity of the designed cobot in this paper reaches 8.4 kg,surpassing the 5 kg load capacity commercial cobot which is used as a benchmark.The minimum resonance frequency of the joints is 42.70 Hz.
文摘Purpose–In recent years,the rapid advancement of artificial intelligence(AI)has exerted profound impacts on and provided strong impetus to numerous fields in the industrial sector.Within the railway industry,AI has driven continuous upgrading and optimization of intelligent train control technology,thanks to its enhanced computational capabilities derived from advanced algorithms and models,as well as its role in improving safety performance.Integrating AI technology more extensively into train autonomous driving and control has thus become an inevitable trend in the global development of railways.Design/methodology/approach–This paper,therefore,conducts a comprehensive analysis of the development progress and current status of AI technology applications in the field of train driving and control on a global scale.It systematically sorts out and analyzes the advantages of various AI technologies and the positive impacts they bring to the upgrading of train control technology,elucidates the feasibility and future prospects of applying a range of emerging AI technologies from the perspective of technical theory and provides guidance for the intelligent development of this field from a practical perspective.Findings–The application of AI technology in the train driving and control field is still in its infancy.While a large number of AI technologies have been widely adopted,there remains significant room for further optimization and improvement of these technologies.Additionally,a variety of AI technologies that have been applied in other industrial sectors but not yet widely implemented in training autonomous driving and control have demonstrated tremendous development potential.Originality/value–The research findings provide references and guidance for advancing train control technology,promoting the digital transformation of railways,accelerating the overall optimization and upgrading of railway industry technologies,and facilitating the accelerated development of global railways.
文摘列车司机驾驶仿真子系统是构建完备的列控仿真系统与功能测试环境的基础部分,该子系统有助于提高整个仿真与测试系统的真实性和可操作性。本文针对司机驾驶仿真子系统,从功能需求、列车速度模型建立、软件仿真等方面对该子系统进行分析,引入AV8R-01型摇杆及SST辅助编程技术,利用Visual Studio 2010编程环境实现了该子系统。本文利用较低成本的硬件平台辅以软件界面代替传统的驾驶实物平台,在CTCS仿真测试与司机培训等仿真平台搭建过程中既节省了成本,又能够起到驾驶仿真的作用。
