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arXiv 2022年

作者： Wang, Xin Yan, Jing-Ke Cai, Jing-Ye Deng, Jian-Hua Qin, Qin Cheng, Yao School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610000 China State Key Laboratory of Rail Transit Vehicle System Southwest Jiaotong University Chengdu610000 China School of Marine Engineering Guilin University of Electronic Technology Guilin541000 China School of Computer and Information Security Guilin University of Electronic Technology Guilin541000 China

Single-image super-resolution (SISR) typically focuses on restoring various degraded low-resolution (LR) images to a single high-resolution (HR) image. However, during SISR tasks, it is often challenging for models to simultaneously maintain high quality and rapid sampling while preserving diversity in details and texture features. This challenge can lead to issues such as model collapse, lack of rich details and texture features in the reconstructed HR images, and excessive time consumption for model sampling. To address these problems, this paper proposes a Latent Feature-oriented Diffusion Probability Model (LDDPM). First, we designed a conditional encoder capable of effectively encoding LR images, reducing the solution space for model image reconstruction and thereby improving the quality of the reconstructed images. We then employed a normalized flow and multimodal adversarial training, learning from complex multimodal distributions, to model the denoising distribution. Doing so boosts the generative modeling capabilities within a minimal number of sampling steps. Experimental comparisons of our proposed model with existing SISR methods on mainstream datasets demonstrate that our model reconstructs more realistic HR images and achieves better performance on multiple evaluation metrics, providing a fresh perspective for tackling SISR tasks. © 2022, CC0.

关键词： Image reconstruction

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Influence of Trisodium Citrate on the Surface Properties of PEO Films Formed in Carbonate-Based Electrolytes on 7075 Aluminum Alloy

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Ceramics International 2025年

作者： Qian Xiao Chao Zhou Yao Wang Wenbin Yang Xinlong Liu Daoyun Chen Haohao Ding Zian Su Mi Luo Yibin Qi School of Electrical and Mechanical Engineering and Vehicle Engineering East China Jiaotong University Nanchang Jiangxi State Key Laboratory of Performance Monitoring Protecting of Rail Transit Infrastucture East China Jiaotong University Nanchang 330013 China Tribology Research Institute State Key Laboratory of Traction Power Southwest Jiaotong University Chengdu 610031 PR China

Ceramic coatings were fabricated on 7075 aluminum alloy via plasma electrolytic oxidation (PEO) in a carbonate-based electrolyte system incorporating varying concentrations of trisodium citrate. The effects of trisodium citrate concentration on the corrosion resistance and tribological properties of the coatings were systematically studied. The coatings’ crystalline phases, microstructural features, and elemental composition were systematically analyzed using X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS). Corrosion resistance and wear behavior were evaluated through electrochemical measurements, salt spray tests, and reciprocating friction and wear experiments. The results reveal that the incorporation of trisodium citrate enhances the coating thickness and, through chelation with Al 3+ ions, reduces the number of medium- and small-sized pores, thereby facilitating the formation of a smooth, micron-scale porous architecture. Although trisodium citrate had little effect on the phase composition, it significantly modified the coating microstructure, enhancing wear resistance and coating stability. At a trisodium citrate concentration of 5 g/L, the coating exhibited the most favorable wear resistance, with a wear rate of 1.37±0.195 × 10 -5 mm 3 ·N -1 ·m -1 ; notably, all PEO coatings demonstrated wear rates approximately 97% lower than that of the aluminum alloy substrate. The coating prepared with 4 g/L trisodium citrate achieved the maximum thickness and exhibited the highest corrosion resistance, reflected by a low corrosion current density of 1.29 ± 0.11×10 -7 A·cm -2 and a maximum polarisation resistance of 71.17±12.76×10 7 Ω/cm 2 , showing a slight improvement compared to the substrate.

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Fast and regularized reconstruction of building façades from street-view images using binary integer programming

arXiv

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arXiv 2020年

作者： Hu, Han Wang, Libin Zhang, Mier Ding, Yulin Zhu, Qing State Key Laboratory of Rail Transit Engineering Informatization China Railway First Survey and Design Institute Co. Ltd. Xian China Faculty of Geosciences and Environmental Engineering Southwest Jiaotong University Chengdu China

Regularized arrangement of primitives on building façades to aligned locations and consistent sizes is important towards structured reconstruction of urban environment. Mixed integer linear programing was used to solve the problem, however, it is extreamly time consuming even for state-of-the-art commercial solvers. Aiming to alleviate this issue, we cast the problem into binary integer programming, which omits the requirements for real value parameters and is more efficient to be solved . Firstly, the bounding boxes of the primitives are detected using the YOLOv3 architecture in real-time. Secondly, the coordinates of the upper left corners and the sizes of the bounding boxes are automatically clustered in a binary integer programming optimization, which jointly considers the geometric fitness, regularity and additional constraints;this step does not require a priori knowledge, such as the number of clusters or pre-defined grammars. Finally, the regularized bounding boxes can be directly used to guide the façade reconstruction in an interactive envinronment. Experimental evaluations have revealed that the accuracies for the extraction of primitives are above 0.82, which is sufficient for the following 3D reconstruction. The proposed approach only takes about 10% to 20% of the runtime than previous approach and reduces the diversity of the bounding boxes to about 20% to 50%. Copyright © 2020, The Authors. All rights reserved.

关键词： Facades

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Durable superhydrophobic self-cleaning surfaces mediated by alumina for corrosion resistance of Mg alloys

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Colloids and Surfaces A: Physicochemical and engineering Aspects 2025年 722卷

作者： Ruijuan Shao Junjie Chen Baoshan Xu Yunhao Zhao Ke Zhou Xiaowei Xun Fan Zhang Zhichao Huang Dongmian Zang State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure East China Jiaotong University Nanchang 330013 PR China School of Materials Science and Engineering East China Jiaotong University Nanchang 330013 PR China

This study introduces a highly efficient two-step methodology for crafting a durable superhydrophobic coating on AZ80 magnesium alloy (AZ80). The process initiates with an in-situ water bath-assisted solution immersion, followed by heat treatment to form a robust, passivated, and textured alumina film. The engineered rough intermediary layer is then conformally encapsulated with polydimethylsiloxane (PDMS) via vapor deposition, yielding a superhydrophobic surface with exceptional substrate adhesion, outstanding mechanochemical stability, long-term durability, and self-cleaning efficacy. Electrochemical testing demonstrated that the corrosion current density of the fabricated highly robust superhydrophobic AZ80 alloy was significantly diminished to 1.666 % of the value measured for the untreated AZ80. Specifically, it decreased from an initial 1.811 × 10⁻⁴ A·cm⁻² to 3.017 × 10⁻⁶ A·cm⁻², clearly indicating the provision of highly effective corrosion protection.

关键词： Corrosion resistant coatings

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Fault Diagnosis of railway Turnout Based on Random Forests 4th

Fault Diagnosis of Railway Turnout Based on Random Forests

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4th International Conference on Electrical and Information Technologies for rail Transportation, EITRT 2019

作者： Zhang, Huiyue Wang, Zhipeng Wang, Ning Long, Jing Tao, Tao State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China National Engineering Laboratory for System Safety and Operation Assurance of Urban Rail Transit Beijing Jiaotong University Guangdong China Beijing Research Center of Urban Traffic Information Sensing and Service Technologies Beijing Jiaotong University Beijing China

ISBN: (纸本)9789811528651

The turnout is a key component of the railway infrastructure systems and is considered as a critical issue about the train operation safety. Therefore, the fault diagnosis research of the turnout is important. However, the existing methods of the fault diagnosis for the railway turnout have the problems such as low efficiency, inability to meet timeliness, and insufficient accuracy. To solve these problems, this paper presents a fault diagnosis method based on random forests. The random forests algorithm builds many CART decision tree classifiers, and introduces two random procedures: i.e., random samples and random features, to enhance the diversity of each decision tree classifier. The final classification result is obtained by majority voting method, which improves the execution speed and classification accuracy. In this paper, a case study is also presented by using the electric power data of the S700K switch machine, and the random forests classification model is constructed. The result shows that the random forests algorithm can accurately and quickly give the diagnosis results for the status of the railway turnout. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Failure analysis

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Convolutional neural network-attention-gate recurrent unit-attention hybrid framework for spindle thermal error modeling with joint feature analysis under complex variable speed conditions

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engineering Applications of Artificial Intelligence 2025年 156卷

作者： Sen Mu Guoqiang Fu Yue Zheng Xi Wang Caijiang Lu Jianzhong Fu School of Mechanical Engineering Southwest Jiaotong University Chengdu 610031 China Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province Chengdu 610031 China The Intelligent Manufacturing Longcheng Laboratory Changzhou 213164 China The State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou 310027 China

Deep learning-based spindle thermal error modeling and compensation methods can effectively enhance manufacturing precision. The complex variable working conditions and thermal hysteresis effects in machine tool machining bring significant challenges for high-precision thermal error modeling. To address this issue, a hybrid structure network based on the feature extraction capability of Convolutional Neural Network (CNN) and the thermal hysteresis effect resolution capability of deep Gate Recurrent Unit (GRU) is established. A dual-layer attention mechanism is introduced to enhance spatial features and temporal features for improving the model's robustness and accuracy. First, complex variable working conditions result in complexity and nonlinearity of data. CNN is employed to extract spatial features due to its powerful feature extraction capability. A self-attention mechanism is introduced after CNN block to further filter important features. Due to the influence of thermal hysteresis effects, a deep GRU block is established to extract temporal features. A channel attention mechanism is introduced as the final layer of the network to achieve feature selection across different temperature channels. Second, features extracted by two attention mechanism layers are visualized and analyzed using t-distributed stochastic neighbor embedding (t-SNE) algorithm to explain the effectiveness of the dual-layer attention mechanism structure. The probability density distribution of the predicted results is calculated by kernel density estimation. Model performance is analyzed from the perspective of data distribution. Finally, the proposed model is compared with advanced methods under complex working conditions on two machine tools. The effectiveness of the proposed model is further validated through actual cutting compensation.

关键词： Deep learning Dual-attention mechanism Joint feature analysis Real cutting compensation Spindle thermal error modeling

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An Easy-implemented Optimization Method of Trajectory Planning Based on Polynomial Interpolation

An Easy-implemented Optimization Method of Trajectory Planni...

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第40届中国控制会议

作者： Guangrong Chen Ming Ma Sheng Guo Bowen Hou Junzheng Wang Robotics Research Center Beijing Jiaotong University Beijing Engineering and Technology Research Center of Rail Transit Line Safety and Disaster Prevention State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

Firstly,the forward kinematics and inverse kinematics of a five axis manipulator are ***,an easyimplemented optimization method of trajectory planning based on seventh order polynomial interpolation is *** proposed optimization method can capture the time optimal trajectory,while the actuators specifications including speed,acceleration of motor can be guaranteed as ***,simulation results validate the effectiveness and efficiency of proposed optimization *** research provides an insight for the application of trajectory optimization on the controller with low computing capability and real-time requirement.

关键词： Trajectory planning Optimization method Polynomial interpolation Manipulator

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Energy recovery characteristics analysis of permanent magnet electrodynamic wheel Maglev vehicle system based on heat-electricity energy conversion strategy under static suspension condition

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Energy 2025年 330卷

作者： Le Liang Zhengyan Li Baojian Zhang Peng Pang Zigang Deng National Laboratory of Rail Transit Southwest Jiaotong University Chengdu Sichuan 610031 China Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle Ministry of Education Southwest Jiaotong University Chengdu Sichuan 610031 China School of Information Science and Technology Southwest Jiaotong University Chengdu 610031 China State Key Laboratory of Rail Transit Vehicle System Southwest Jiaotong University Chengdu Sichuan 610031 China School of Electrical Engineering Southwest Jiaotong University Chengdu Sichuan 610031 China

In this paper, a heat-electricity energy conversion strategy based on thermoelectric theory in permanent magnet electrodynamic wheel (PMEDW) magnetic levitation (Maglev) vehicle system is proposed and tested for the first time. The PMEDW-Maglev vehicle is based on electromagnetic induction interaction principle between PMEDW and conductor plate, to generate levitation force and propulsion force. Hence, the PMEDW-Maglev vehicle is a new concept with levitation-propulsion multifunctional integrated design, to supply the faster, greener, smarter highway transportation mode. But, the temperature rise in conductor plate may cause the levitation failure and reduce the system operation stability. Hence, considering energy effective conservation and utilization, the thermoelectric theory based heat-electricity energy conversion strategy is proposed in this paper, to utilize the heat generated by temperature rise and improve system operation performance. The operation performance of PMEDW-Maglev prototype vehicle with the heat-electricity energy conversion strategy is tested by the experiment. It can be found from the experimental results that, the proposed heat-electricity energy conversion strategy can operate as expected. The levitation force and temperature rise cooling ratio in conductor plate can be improved by more than 47 % and 12 %, respectively, besides, the heat can be converted into electricity energy and stored in battery unit (more than 280 J). The significance of this work is that the proposed heat-electricity energy conversion strategy can offer a performance enhancement and energy self consistency design method for the future PMEDW-Maglev vehicle system.

关键词： Energy conservation Energy system self consistency Heat-electricity energy conversion PMEDW- Maglev vehicle

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A Novel Fractional Order Impedance Control and Its Performance Analysis

A Novel Fractional Order Impedance Control and Its Performan...

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第33届中国控制与决策会议

作者： Guangrong Chen Huafeng Lu Bowen Hou Sheng Guo Junzheng Wang Robotics Research Center Beijing Jiaotong University Beijing Engineering and Technology Research Center of Rail Transit Line Safety and Disaster Prevention State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

In traditional impedance control model,the contact force can be reduced ***,there exists a tracking error at the stable state due to the existence of stiffness,which is not conducive to tackle tasks based on high performance position control for ***,this paper proposes a novel dynamic interaction model:fractional order impedance control,to address this ***,an integral item is added into the traditional impedance model to eliminate the tracking ***,the idea of fractional order is introduced to make the orders of inertia,damping,and stiffness change from integers to fractions to achieve more significant compliant ***,simulation results validate the advantages of proposed fractional order impedance control and it can be also employed to absorb/increase,hold/keep,and dissipate/decrease system energy to achieve jumping,bouncing and friendly contact,***,stability analysis and three criterions of choosing and tuning 6 classic parameters in the proposed fractional order impedance control are both given out.

关键词： Dynamic interaction Compliance control Fractional order Impedance control Performance analysis

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Author Correction: Origin and tuning of bandgap in chiral phononic crystals

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Communications Physics 2024年第1期7卷 1页

作者： Wei Ding Rui Zhang Tianning Chen Dewen Yu Jian Zhu Shuai Qu Liwei Dong Yaowen Yang Badreddine Assouar School of Mechanical Engineering and State Key Laboratory of Strength & Vibration of Mechanical Structures Xi’an Jiaotong University Xi’an 710049 Shaanxi China School of Civil and Environmental Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore Singapore Train and Track Research Institute State Key Laboratory of Rail Transit Vehicle System Southwest Jiaotong University Chengdu 610031 China Institute of Rail Transit Tongji University Shanghai 201804 China Université de Lorraine CNRS Institut Jean Lamour F-54000 Nancy France

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