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International Conference on Intelligent Transportation

作者： Haodong Li Jiateng Yin Tao Tang Andrea D'Ariano Mengxing You State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University Beijing China Department of Civi Computer Science and Aeronautical Technologies Engineering Roma Tre Universily Rome Italy Nanchang Rail Transit Group Co. Ltd. Jiangxi China

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Train platooning, which allows multiple train units to be virtually coupled into a platoon with very short following distances, has become an emerging technology in railway industry. Our study investigates the energy-efficient operation of train platoons to reduce the energy consumption of trains while satisfying time-varying passenger demands in practice. Specifically, we construct a mixed integer programming (MIP) model in order to simultaneously optimize the timetable and speed profiles of train platoons in an urban rail transit line. The aim of the developed MIP model is to minimize the total energy consumption of trains as well as the waiting time of traveling passengers, while satisfying the practical constraints, such as the train movement constraints, passenger loading constraints for different train platoons, etc. In order to solve the MIP model more efficiently, we develop a hybrid iterative algorithm that combines a Deep Q-Network (DQN) and an MIP solver, in which the DQN generates energy-efficient speed profiles for different types of platoons and the MIP solver then determines the optimal train schedule. Finally, we conduct real-world case studies on the Beijing subway Yizhuang line to verify the effectiveness of our approach. The results indicate that the energy-efficient operation of train platoons can achieve a better tradeoff between service quality and system energy consumption.

关键词： Couplings rails Energy consumption Schedules Optimization models Energy efficiency rail transportation Public transportation Optimization Load modeling

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Anticorrosive and Self-Cleaning Magnesium Alloys Mediated by Alumina

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SSRN 2024年

作者： Zang, Dongmian Shao, Ruijuan Chen, Junjie Xu, Baoshan Huang, Zhichao State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure East China Jiaotong University Nanchang330013 China School of Materials Science and Engineering East China Jiaotong University Nanchang330013 China

Passive roughened aluminum oxide coatings were constructed on AZ80 Mg alloy (AZ80) surface by a combination of in situ water bath assisted solution immersion process and heat treatment. Post-modification with polydimethylsiloxane using a vapor deposition technique, the superhydrophobic AZ80 surface was prepared, which exhibited ultralow adhesion and water contact angle hysteresis, as well as excellent thermostability and chemical durability. The electrochemical tests showed that the corrosion potential of the resulting superhydrophobic surface increased by 0.759 V, the corrosion current density decreased to 1.666% of the AZ80, indicating effective corrosion protection. Furthermore, sand was used as a contaminant particle in the self-cleaning test. After 8 s, all the sand particles were "captured" by the rolling water droplets and rolled off from the surface of the prepared superhydrophobic AZ80 achieving the lotus effect which is the ability of a highly rough surface for self-clean and extreme water repellence. © 2024, The Authors. All rights reserved.

关键词： Alumina

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ABSOLUTE DISPLACEMENT TRANSMISSIBILITY OF VIBRATION ISOLATOR WITH THE QUASI-ZERO STIFFNESS 1

ABSOLUTE DISPLACEMENT TRANSMISSIBILITY OF VIBRATION ISOLATOR...

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1st International Conference on Mechanical System Dynamics, ICMSD 2022

作者： Liu, Yanqi Xu, Longlong Song, Chunfang Wang, Xin Deng, Erjie Wang, Youhui Institute of Urban Safety and Environmental Science Beijing Academy of Science and Technology Beijing China School of Mechanic Engineering Jiangnan University Wuxi China State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure East China Jiaotong University Nanchang China

ISBN: (数字)9781839537837

ISBN: (纸本)9781839537837

A vibration isolator with quasi-zero stiffness (QZS) is proposed, which is composed of positive stiffness mechanism and negative stiffness mechanism in parallel. Considering the nonlinear stiffness and nonlinear damping, the equation of motion is derived and further solved by the average method. Subsequently, the amplitude-frequency equation relationship and the expression of absolute displacement transmissibility (ADT) are deduced. Then, the effects of nonlinear coefficient, excitation amplitude, horizontal and vertical damping on dynamic response characteristics and ADT are analyzed. The results indicate that there are many ways to reduce the peak value of ADT, such as increasing vertical and horizontal damping, reducing the nonlinear coefficient or excitation amplitude. In addition, by decreasing the nonlinear coefficient or excitation amplitude can minish initial vibration isolation frequency. The higher vertical and horizontal damping may expand the isolation frequency bandwidth. The low frequency vibration isolation performance of the vibration isolation system of the horizontal spring with decreasing stiffness is better than that with increasing stiffness. Contrasted by the equivalent linear system, the QZS isolation system possesses the advantages of smaller transmissibility peak, lower initial frequency of vibration isolation and larger isolation frequency bandwidth. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Stiffness

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One Master Data Identification Method Based on Stacking Integration

One Master Data Identification Method Based on Stacking Inte...

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Digital Society and Intelligent Systems (DSInS), International Conference on

作者： Xiaojun Wu Yubo Dong Sheng Yuan Xiaochun Ren Wei Wang Cheng Zhang School of Software Engineering Xi’an Jiaotong University Xi’an China State Key Laboratory of Rail Transit Engineering Informatization (FSDI) Xi’an China

ISBN: (纸本)9781665406314

In the existing master data identification process, there are several problems, such as slow demand response and lack of targets, after the construction of information systems. One master data identification method based on stacking integration is proposed in this paper. Considering the characteristics of master data and the available elements in the conceptual design stage, seven master data identifiable metrics are selected. Master data recognition result belongs to either the positive class or the negative one, which can be converted into so-called Binary Classification problem. In order to identify the characteristics of different attributes within the indicator, the first step is to learn with specific learners, the second step is to stack and integrate the results of each learner, and the last and third step is to obtain the results of identification. The experiments use both the self-built dataset and the Titanic dataset. The results show that this method can reach the expectations. The feasibility and validity of the method are verified as well.

关键词： Measurement Stacking Demand response Object recognition Task analysis Intelligent systems Information systems

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Short-Term Wind Farm Cluster Power Point-Interval Prediction Based on Graph Spatio-Temporal Features and S-Stacking Combined Reconstruction

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SSRN 2023年

作者： Qu, Zhijian Hu, Wenbo Hou, Xinxing Huang, Shixun State Key Laboratory of Performance MonitoringProtecting of Rail Transit Infrastructure East China Jiaotong University China School of Electrical Engineering East China Jiaotong University Nanchang30013 China

Wind energy is becoming increasingly competitive;existing research on wind power forecasting has neglected the importance of interval forecasting using clusters of wind farms to capture spatial characteristics and the objective selection of forecasting sub-learners, leading to increased uncertainty and risk in system operation. This paper proposes a new "decomposition-aggregation-multi-model parallel prediction" method. The data set is pre-processed by a decomposition-aggregation strategy and spatial feature extraction, and then a Stacking model with multiple parallel sub-learners selected by bootstrap method is used for point and interval forecasting. Experiments and discussions are conducted based on fifteen-minute resolution wind power data from a cluster dataset of a wind farm in northwest China. The experimental results indicate that the method achieves higher accuracy and reliability in both point prediction and interval prediction than other comparative models, with a root mean square error value of 7.47 and an average F value of 1.572, which can provide a reliable reference for power generation planning from wind farm clusters. © 2023, The Authors. All rights reserved.

关键词： Deep learning

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轴重和频率对激光修复316L不锈钢涂层在铁路车轮踏面制动中摩擦学性能的影响

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表面工程与再制造 2024年第2期24卷 51-52页

作者： Li, Shiyu Yang, Chunhui Xiao, Qian Yang, Wenbin Wang, Yao State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure East China Jiaotong University Nanchang 330013 China jxralph@*** (Q.X.) School of Mechatronics and Vehicle Engineering East China Jiaotong University Nanchang 330013 China wy_jxnc_ecjtu@*** State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure East China Jiaotong University Nanchang 330013 China jxralph@*** (Q.X.) School of Mechatronics and Vehicle Engineering East China Jiaotong University Nanchang 330013 China wy_jxnc_ecjtu@*** Railway Industry Key Laboratory of Intelligent Operation and Maintenance of Rolling Stock East China Jiaotong University Nanchang 330013 China School of Mechatronics and Vehicle Engineering East China Jiaotong University Nanchang 330013 China wy_jxnc_ecjtu@***

研究复杂制动环境对修复熔覆层服役性能的影响,对提高列车轮轨系统抵御极端恶劣环境的能力具有重要意义。本文针对火车车轮踏面局部损伤问题,利用激光熔覆修复技术在损伤处制备316L不锈钢涂层。采用MS-HT1000高温磨损试验机进行磨损实... 详细信息

研究复杂制动环境对修复熔覆层服役性能的影响,对提高列车轮轨系统抵御极端恶劣环境的能力具有重要意义。本文针对火车车轮踏面局部损伤问题,利用激光熔覆修复技术在损伤处制备316L不锈钢涂层。采用MS-HT1000高温磨损试验机进行磨损实验。然后,分析不同制动条件对修复试样在室温和高温下摩擦磨损性能的影响。

关键词：激光修复铁路车轮局部损伤磨损实验车轮踏面磨损试验机服役性能踏面制动

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High-Temperature Superconducting Magnetic Levitation with the Halbach Array and V-Shaped Combined Permanent Magnet Guideway

SSRN

引用

SSRN 2024年

作者： Gao, Lingfeng Deng, Zigang Hu, Xianhong Zhou, Xucheng Zhang, Weihua D’Ovidio, Gino Applied Superconductivity Laboratory State Key Laboratory of Rail Transit Vehicle System Southwest Jiaotong University Chengdu610031 China School of Mechanics and Aerospace Engineering Southwest Jiaotong University Chengdu610031 China Civil Construction-Architectural and Environmental Engineering University of L’Aquila Italy

The permanent magnet guideways (PMGs), serving as the sole magnetic field source for high-temperature superconducting (HTS) pinning maglev system, exerts a profound influence on the levitation performance of HTS bulks through its magnetic field distribution. To improve the levitation performance of HTS maglev systems, experiments to measure levitation and guidance forces were conducted using the 165 m test line PMG completed by Southwest Jiaotong University in 2021. Additionally, finite element simulation models were developed. Subsequently, utilizing this simulation model as a foundation, a V-shaped Halbach array PMG was designed by combining a Halbach array with a ‘V’ structure. Subsequently, the V-shaped PMG underwent simulation optimization with the goal of maximizing the levitation force. The optimized V-shaped PMG, when compared to the test line PMG with the same cross-sectional area, exhibits significant improvements. Under the zero field cooling (ZFC) condition with a 15 mm lateral displacement, the levitation force experienced a 39.1% increase at the working height (WH), while the guidance force showed a substantial 274.9% improvement. Similarly, under the field cooling (FC) condition with a 15 mm lateral displacement, there was a 43.6% increase in levitation force and a 186.1% increase in guidance force. This data unequivocally demonstrates the considerable application potential of the V-shaped PMG when compared with the test line PMG. © 2024, The Authors. All rights reserved.

关键词： Magnetic levitation

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Research on Variable Turns Ratio CT Based on MOSFET Power Electronic AC Switch 7

Research on Variable Turns Ratio CT Based on MOSFET Power El...

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7th IEEE International Conference on Power and Renewable Energy, ICPRE 2022

作者： Liu, Jun Lin, Tao Liu, Annan Chen, Yumeng Peng, Weifa East China Jiaotong University State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure Seae Nanchang China East China Jiaotong University School of Electrical and Automation Engineering Nanchang China East China Jiaotong University School of Tianyou Nanchang China

ISBN: (数字)9781665450638

ISBN: (纸本)9781665450638

It is difficult to design the backward converter when energy harvesting current transformer (CT) works within a wide range of the primary voltage. It reduces the range of the secondary of CT by variable turns ratio technology within a wide range of the primary voltage. Thus, variable turns ratio technology enhances the practicability and flexibility of CT. After sampling and analyzing the secondary of CT, the secondary turns can be adjusted automatically by controlling the AC switches which are connected with the secondary winding. MOSFETs are used to construct the AC switch. It reduces the cost and control difficulty by optimizing the AC structure and drive circuit. The scheme can be applied to other types of transformers with automatic turns ratio. © 2022 IEEE.

关键词： Timing circuits

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Integrating dynamic simulation knowledge and domain adversarial neural network for state recognition of high-speed train axlebox bearings

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IEEE Sensors Journal 2025年

作者： Pan, Yanlong Yi, Cai Liao, Xiaokang Lin, Yunzhi Yan, Lei Lin, Jianhui Southwest Jiaotong University State Key Laboratory of Rail Transit Vehicle System Chengdu610000 China Xihua University School of Mechanical Engineering Chengdu610031 China China Railway Construction Electrification Bureau Group Beijing100043 China Southwest Jiaotong University School of Mechanical Engineering Chengdu610031 China

Transfer learning helps address the issue of limited fault samples in real high-speed trains by transferring domain knowledge. However, most existing transfer learning approaches rely heavily on well-labeled source domain samples and do not account for the varying quality of these samples, treating all samples with equal importance. To tackle this problem, this paper proposes a high-speed train axlebox bearing state recognition method with the integration of dynamic simulation knowledge and domain adversarial neural network, named PKEFD. Firstly, an axlebox-vehicle-track coupled dynamics model with explicit physical meaning is used to generate labeled bearing data, and the data is further expanded using amplitude scaling to cover more working conditions. Subsequently, the joint maximum mean discrepancy loss term is incorporated into the domain adversarial neural network to align domain data with varying distributions. Additionally, weights are assigned to each source domain sample based on the discriminative difficulty determined by the domain discriminator, which helps to suppress interference in the source domain abnormal samples. The dilated convolution module is embedded into the network to enhance multi-scale fault feature learning. Finally, using the simulation dynamics model dataset and the constant/variable speed experimental dataset, we designed transfer tasks involving single and multi-source domains across different equipment and working conditions. The test results demonstrate the proposed method's good stability and generalization capabilities. © 2001-2012 IEEE.

关键词： Drive axles

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An IMU Error Correction Method Based on Multithreshold ZV Detection and SRCKF

An IMU Error Correction Method Based on Multithreshold ZV De...

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2023 International Conference on Cyber-Physical Social Intelligence, ICCSI 2023

作者： Luo, Jialiang Chen, Shichao Lv, Yisheng Sun, Wenqiao Yang, Fan Xu, Ruijie Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems China Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited The State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Transportation and Economics Research Institute Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Rail Transit Shan Dong JiaoTong University The State Key Laboratory for Management and Control of Complex System Jinan China The Hong Kong Polytechnic University Department of Aeronautical and Aviation Engineering Hong Kong Hong Kong

ISBN: (纸本)9798350312492

With the rapid development and widespread application of Inertial Measurement Units (IMUs), IMU-based human localization has become critically important in environments lacking Global Navigation Satellite Systems (GNSS) signals. Methods such as UWB/WIFI and other anchor-based localization have been employed to enhance the positioning accuracy. However, these methods are susceptible to the environmental interference and increased costs. In contrast, SINS-based localization methods eliminate reliance on the external data. However, this method can suffer from drift errors due to cumulative integration errors. Inertial navigation error correction techniques like Zero Detection Update Technology (ZUPT) provide potential solutions to address drift errors. This paper proposes an error correction method based on the multithreshold zero-velocity detection and Square Root Cubature Kalman Filter (SRCKF) updates. Compared to the single fixed threshold detection, the multi-threshold zero-velocity detection reduces the likelihood of missed zero velocity detection and false alarms, providing accurate time intervals for error correction. Experimental results demonstrate that the SRCKF-based algorithm reduces position deviation to approximately 0.3146 meters, corresponding to an error ratio of1.14%. The proposed method enables cost-effective and accurate pedestrian localization, driving advancements in the field. © 2023 IEEE.

关键词： Cost effectiveness

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