In this paper,a novel train positioning method considering satellite raw observation data was proposed,which aims to promote train positioning performance from an innovative perspective of the train satellite-based po...In this paper,a novel train positioning method considering satellite raw observation data was proposed,which aims to promote train positioning performance from an innovative perspective of the train satellite-based positioning error sources.The method focused on overcoming the abnormal observations in satellite observation data caused by railway environment rather than the positioning results.Specifically,the relative positioning experimental platform was built and the zero-baseline method was firstly employed to evaluate the carrier phase data quality,and then,GNSS combined observation models were adopted to construct the detection values,which were applied to judge abnormal-data through the dual-frequency observations.Further,ambiguity fixing optimization was investigated based on observation data selection in partly-blocked environments.The results show that the proposed method can effectively detect and address abnormal observations and improve positioning stability.Cycle slips and gross errors can be detected and identified based on dual-frequency global navigation satellite system data.After adopting the data selection strategy,the ambiguity fixing percentage was improved by 29.2%,and the standard deviation in the East,North,and Up components was enhanced by 12.7%,7.4%,and 12.5%,respectively.The proposed method can provide references for train positioning performance optimization in railway environments from the perspective of positioning error sources.展开更多
In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts ...In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts to carry out the bench press training in the microgravity environment. Firstly, a dynamic model of cable driven unit(CDU) was established whose accuracy was verified through the model identification. Secondly, to improve the accuracy and the speed of the active loading, an active loading hybrid force controller was proposed on the basis of the dynamic model of the CDU. Finally, the actual effect of the hybrid force controller was tested by simulations and experiments. The results suggest that the hybrid force controller can significantly improve the precision and the dynamic performance of the active loading with the maximum phase lag of the active loading being 9° and the maximum amplitude error being 2% at the frequency range of 10 Hz. The controller can meet the design requirements.展开更多
随着高速铁路迅猛发展,动车组列车运行自主化和健康管理智能化都面临更高的需求。列车网络控制系统作为动车组的“神经中枢”,承担传输车辆状态信息及控制信息等隐私数据的任务。列车重联场景下,列车之间网络数据传输更加复杂,面临实时...随着高速铁路迅猛发展,动车组列车运行自主化和健康管理智能化都面临更高的需求。列车网络控制系统作为动车组的“神经中枢”,承担传输车辆状态信息及控制信息等隐私数据的任务。列车重联场景下,列车之间网络数据传输更加复杂,面临实时性、安全性、可追溯、防篡改等一系列挑战。以列车网络控制系统中故障预测与健康管理(prognostics and health management, PHM)单元和无线传输单元的隐私数据共享传输为例,对PHM数据库进行共享扩充,提出一种基于联盟链的重联列车PHM数据库共享方案。列车网络控制系统为分布式架构,首先以单车PHM单元和无线传输单元作为联盟链节点建立单群组单机构联盟链,在此基础上,对于重联列车设计三群组双机构联盟链。同时,设计基于数据本地存储,验证方式上链的模式,并在网络架构中使用三级证书结构对节点进行身份验证。考虑两单元生成的隐私数据量大的需求,对PBFT算法的消息转发机制和Prepare包进行改进优化,有效减少冗余数据包数量,提高了网络效率。将改进算法后的联盟链进行测试,实验表明:仿真实验环境下,该算法改进后,节点共识成功率达到100%,每秒处理交易数单车系统下提高了18.2%,重联系统下提高了13.3%,平均出块时间在单车系统下平均缩短了29672.25ms,重联系统下平均缩短了72 993.25 ms。研究结果验证了联盟链系统在具备安全性的同时兼顾了高效性,表明联盟链在重联列车PHM数据库共享过程中应用具有极大的可行性,也为列车状态隐私信息安全可追溯提供了技术参考。展开更多
CTCS-3级(Chinese Train Control System-3)列控车载设备在保障列车安全和提高运行效率方面发挥着重要作用。车载接口设备实现车载列车自动防护(ATP)系统与地面设备、司机和列车的交互,然而它的故障在车载设备故障中占比高。为了确定故...CTCS-3级(Chinese Train Control System-3)列控车载设备在保障列车安全和提高运行效率方面发挥着重要作用。车载接口设备实现车载列车自动防护(ATP)系统与地面设备、司机和列车的交互,然而它的故障在车载设备故障中占比高。为了确定故障原因并保证行车安全,提出一种基于时序知识图谱补全的列控车载接口设备故障诊断方法。首先,采用引入时序的方式整合行车日志和故障统计数据,从而提取故障现象并对齐实体,构建时序知识图谱;其次,构建基于图谱补全的故障诊断网络,融合时序翻译(T-TransE)向量化算法、双向长短期记忆(Bi-LSTM)网络和自注意力(SA)机制提取时序特征;最后,使用某铁路局近几年的车载接口设备故障数据对T-TransE向量化模型进行预训练,选出效果最佳的时序引入方式。为验证所提方法的优越性以及数据结合方式的有效性,使用车载故障数据对不进行数据结合且不进行时序关系引入的故障诊断网络以及其他常见的故障诊断网络进行测试。实验结果表明,在同一语料的情况下,与其他故障诊断框架相比,基于时序知识图谱补全的故障诊断模型正确率最高,达到96.69%。展开更多
基金Project(52272339)supported by the National Natural Science Foundation of ChinaProject(2023YFB390730303)supported by the National Key Research and Development Program of China+2 种基金Project(L2023G004)supported by the Science and Technology Research and Development Program of China State Railway Group Co.,Ltd.Project(QZKFKT2023-005)supported by the State Key Laboratory of Heavy-duty and Express High-power Electric Locomotive,ChinaProject(2022JZZ05)supported by the Open Foundation of MOE Key Laboratory of Engineering Structures of Heavy Haul Railway(Central South University),China。
文摘In this paper,a novel train positioning method considering satellite raw observation data was proposed,which aims to promote train positioning performance from an innovative perspective of the train satellite-based positioning error sources.The method focused on overcoming the abnormal observations in satellite observation data caused by railway environment rather than the positioning results.Specifically,the relative positioning experimental platform was built and the zero-baseline method was firstly employed to evaluate the carrier phase data quality,and then,GNSS combined observation models were adopted to construct the detection values,which were applied to judge abnormal-data through the dual-frequency observations.Further,ambiguity fixing optimization was investigated based on observation data selection in partly-blocked environments.The results show that the proposed method can effectively detect and address abnormal observations and improve positioning stability.Cycle slips and gross errors can be detected and identified based on dual-frequency global navigation satellite system data.After adopting the data selection strategy,the ambiguity fixing percentage was improved by 29.2%,and the standard deviation in the East,North,and Up components was enhanced by 12.7%,7.4%,and 12.5%,respectively.The proposed method can provide references for train positioning performance optimization in railway environments from the perspective of positioning error sources.
基金Project(61175128) supported by the National Natural Science Foundation of ChinaProject(2008AA040203) supported by the National High Technology Research and Development Program of ChinaProject(QC2010009) supported by the Natural Science Foundation of Heilongjiang Province,China
文摘In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts to carry out the bench press training in the microgravity environment. Firstly, a dynamic model of cable driven unit(CDU) was established whose accuracy was verified through the model identification. Secondly, to improve the accuracy and the speed of the active loading, an active loading hybrid force controller was proposed on the basis of the dynamic model of the CDU. Finally, the actual effect of the hybrid force controller was tested by simulations and experiments. The results suggest that the hybrid force controller can significantly improve the precision and the dynamic performance of the active loading with the maximum phase lag of the active loading being 9° and the maximum amplitude error being 2% at the frequency range of 10 Hz. The controller can meet the design requirements.
文摘随着高速铁路迅猛发展,动车组列车运行自主化和健康管理智能化都面临更高的需求。列车网络控制系统作为动车组的“神经中枢”,承担传输车辆状态信息及控制信息等隐私数据的任务。列车重联场景下,列车之间网络数据传输更加复杂,面临实时性、安全性、可追溯、防篡改等一系列挑战。以列车网络控制系统中故障预测与健康管理(prognostics and health management, PHM)单元和无线传输单元的隐私数据共享传输为例,对PHM数据库进行共享扩充,提出一种基于联盟链的重联列车PHM数据库共享方案。列车网络控制系统为分布式架构,首先以单车PHM单元和无线传输单元作为联盟链节点建立单群组单机构联盟链,在此基础上,对于重联列车设计三群组双机构联盟链。同时,设计基于数据本地存储,验证方式上链的模式,并在网络架构中使用三级证书结构对节点进行身份验证。考虑两单元生成的隐私数据量大的需求,对PBFT算法的消息转发机制和Prepare包进行改进优化,有效减少冗余数据包数量,提高了网络效率。将改进算法后的联盟链进行测试,实验表明:仿真实验环境下,该算法改进后,节点共识成功率达到100%,每秒处理交易数单车系统下提高了18.2%,重联系统下提高了13.3%,平均出块时间在单车系统下平均缩短了29672.25ms,重联系统下平均缩短了72 993.25 ms。研究结果验证了联盟链系统在具备安全性的同时兼顾了高效性,表明联盟链在重联列车PHM数据库共享过程中应用具有极大的可行性,也为列车状态隐私信息安全可追溯提供了技术参考。
文摘CTCS-3级(Chinese Train Control System-3)列控车载设备在保障列车安全和提高运行效率方面发挥着重要作用。车载接口设备实现车载列车自动防护(ATP)系统与地面设备、司机和列车的交互,然而它的故障在车载设备故障中占比高。为了确定故障原因并保证行车安全,提出一种基于时序知识图谱补全的列控车载接口设备故障诊断方法。首先,采用引入时序的方式整合行车日志和故障统计数据,从而提取故障现象并对齐实体,构建时序知识图谱;其次,构建基于图谱补全的故障诊断网络,融合时序翻译(T-TransE)向量化算法、双向长短期记忆(Bi-LSTM)网络和自注意力(SA)机制提取时序特征;最后,使用某铁路局近几年的车载接口设备故障数据对T-TransE向量化模型进行预训练,选出效果最佳的时序引入方式。为验证所提方法的优越性以及数据结合方式的有效性,使用车载故障数据对不进行数据结合且不进行时序关系引入的故障诊断网络以及其他常见的故障诊断网络进行测试。实验结果表明,在同一语料的情况下,与其他故障诊断框架相比,基于时序知识图谱补全的故障诊断模型正确率最高,达到96.69%。
