High-speed trains operating in freezing rain are highly susceptible to severe ice accretion in the pantograph region,which compromises both power transmission efficiency and dynamic performance.To elucidate the underl...High-speed trains operating in freezing rain are highly susceptible to severe ice accretion in the pantograph region,which compromises both power transmission efficiency and dynamic performance.To elucidate the underlying mechanisms of this phenomenon,an Euler-Euler multiphase flow model was employed to simulate droplet impingement and collection on the pantograph surface,while a glaze-ice formation model incorporating wall film dynamics was used to capture the subsequent growth of ice.The effects of key parameters—including liquid water content,ambient temperature,train velocity,and droplet diameter—on the amount and morphology of ice were systematically investigated.The results show that ice accumulation intensifies with increasing liquid water content decreasing ambient temperature,and rising train speed.In contrast,larger droplet diameters reduce the overall ice mass but promote localized accretion on major structural elements.This behavior arises because larger droplets,with greater inertia,are less susceptible to entrainment by airflow into the pantograph's base region.During extended operation,substantial ice buildup develops on the pantograph head and upper and lower arms,severely impairing current collection from the overhead line and hindering the pantograph's lifting and lowering motions.展开更多
Ventilation systems are critical for improving the cabin environment in high-speed trains,and their interest has increased significantly.However,whether air supply non-verticality deteriorates the cabin air environmen...Ventilation systems are critical for improving the cabin environment in high-speed trains,and their interest has increased significantly.However,whether air supply non-verticality deteriorates the cabin air environment,and the flow mechanism behind it and the degree of deterioration are not known.This study first analyzes the interaction between deflection angle and cabin flow field characteristics and ventilation performance.The results revealed that the interior temperature and pollutant concentration decreased slightly with increasing deflection angle,but resulted in significant deterioration of thermal comfort and air quality.This is evidenced by an increase in both draught rate and non-uniformity coefficient,an increase in the number of measurement points that do not satisfy the micro-wind speed and temperature difference requirements by about 5% and 15%,respectively,and an increase in longitudinal penetration of pollutants by a factor of about 5 and the appearance of locking regions at the ends of cabin.The results also show that changing the deflection pattern only affects the region of deterioration and does not essentially improve this deterioration.This study can provide reference and help for the ventilation design of high-speed trains.展开更多
Purpose–Regarding that Ultraviolet radiation,pollutant adsorption,and environmental changes may be the main reasons for the aging and yellowing on windshield rubber in high-speed trains,countermeasures are proposed t...Purpose–Regarding that Ultraviolet radiation,pollutant adsorption,and environmental changes may be the main reasons for the aging and yellowing on windshield rubber in high-speed trains,countermeasures are proposed to solve the aging and yellowing of windshield rubber and reduce the adverse effects caused by rubber yellowing.Design/methodology/approach–Scanning electron microscopy(SEM)and energy dispersive spectroscopy(EDS)were used to test the yellowed windshield rubber.Aging tests,including UVaging,natural aging and salt spray aging,were conducted to analyze the effects of aging on the windshield rubber.Different cleaning agents were selected to soak the windshield rubber,and the quality,hardness,and surface appearance of the rubber samples were tested.Findings–After UV aging,antioxidants migrated to the surface of the windshield rubber,but due to oxidation failure,they could not capture free radicals,leading to continued oxidation reactions within the material and resulting in yellowing of the rubber in a short period of time.Originality/value–Cleaning agents have a minimal impact on windshield rubber,UV aging has the greatest impact and natural aging is a gradual and slow deterioration process.Through daily deep cleaning and maintenance with protective agents at regular intervals,the deterioration of windshield rubber yellowing in high-speed trains can be effectively suppressed.展开更多
High-Speed Trains (HSTs) have emerged as a mainstream mode of transportation in China, owing to their exceptional safety and efficiency. Ensuring the reliable operation of HSTs is of paramount economic and societal im...High-Speed Trains (HSTs) have emerged as a mainstream mode of transportation in China, owing to their exceptional safety and efficiency. Ensuring the reliable operation of HSTs is of paramount economic and societal importance. As critical rotating mechanical components of the transmission system, bearings make their fault diagnosis a topic of extensive attention. This paper provides a systematic review of image encoding-based bearing fault diagnosis methods tailored to the condition monitoring of HSTs. First, it categorizes the image encoding techniques applied in the field of bearing fault diagnosis. Then, a review of state-of-the-art studies has been presented, encompassing both monomodal image conversion and multimodal image fusion approaches. Finally, it highlights current challenges and proposes future research directions to advance intelligent fault diagnosis in HSTs, aiming to provide a valuable reference for researchers and engineers in the field of intelligent operation and maintenance.展开更多
The dynamic performance of high-speed trains is significantly influenced by sudden changes in aerodynamic loads(ADLs)when exiting a tunnel in a windy environment.Focusing on a double-track tunnel under construction in...The dynamic performance of high-speed trains is significantly influenced by sudden changes in aerodynamic loads(ADLs)when exiting a tunnel in a windy environment.Focusing on a double-track tunnel under construction in a mountain railway,we established an aerodynamic model involving a train exiting the tunnel,and verified it in the Fluent environment.Overset mesh technology was adopted to characterize the train’s movement.The flow field involving the train,tunnel,and crosswinds was simulated using the Reynolds-averaged turbulence model.Then,we built a comprehensive train-track coupled dynamic model considering the influences of ADLs,to investigate the vehicles’dynamic responses.The aerodynamics and dynamic behaviors of the train when affected by crosswinds with different velocities and directions are analyzed and discussed.The results show that the near-wall side crosswind leads to sharper variations in ADLs than the far-wall side crosswind.The leading vehicle suffers from more severe ADLs than other vehicles,which worsens the wheel-rail interaction and causes low-frequency vibration of the car body.When the crosswind velocity exceeds 20 m/s,significant wheel-rail impacts occur,and the running safety of the train worsens rapidly.展开更多
The interaction between the airflow and train influences the aerodynamic characteristics and dynamic performance of high-speed trains.This study focused on the fluid-solid coupling effect of airflow and HST,and propos...The interaction between the airflow and train influences the aerodynamic characteristics and dynamic performance of high-speed trains.This study focused on the fluid-solid coupling effect of airflow and HST,and proposed a co-simulation(CS)approach between computational fluid dynamics and multi-body dynamics.Firstly,the aerodynamic model was developed by employing overset mesh technology and the finite volume method,and the detailed train-track coupled dynamic model was established.Then the User Data Protocol was adopted to build data communication channels.Moreover,the proposed CS method was validated by comparison with a reported field test result.Finally,a case study of the HST exiting a tunnel subjected to crosswind was conducted to compare differences between CS and offline simulation(OS)methods.In terms of the presented case,the changing trends of aerodynamic forces and car-body displacements calculated by the two methods were similar.Differences mainly lie in aerodynamic moments and transient wheel-rail impacts.Maximum pitching and yawing moments on the head vehicle in the two methods differ by 21.1 kN∙m and 29.6 kN∙m,respectively.And wheel-rail impacts caused by sudden changes in aerodynamic loads are significantly severer in CS.Wheel-rail safety indices obtained by CS are slightly greater than those by OS.This research proposes a CS method for aerodynamic characteristics and dynamic performance of the HST in complex scenarios,which has superiority in computational efficiency and stability.展开更多
Currently,the design of high-temperature superconducting(HTS)maglev trains adopts a U-shaped track operation mode,and the height of the side track significantly impacts the train’s aerodynamic characteristics.In this...Currently,the design of high-temperature superconducting(HTS)maglev trains adopts a U-shaped track operation mode,and the height of the side track significantly impacts the train’s aerodynamic characteristics.In this study,we used computational fluid dynamics(CFD)methods,based on the 3D Reynolds-averaged Navier-Stokes(RANS)method and shear stress transport(SST)k-ωturbulence model,to deeply investigate the effects of the presence or absence of a U-shaped track and different side track heights(800,880,and 960 mm)on the pressure distribution,velocity distribution,and flow field structure of HTS maglev trains at a speed of 400 km/h under crosswinds.The numerical methods were verified using a scaled ICE-2 model wind tunnel test.First,the aerodynamic characteristics of the train under different wind direction angles with and without side tracks were studied.We found that the aerodynamic performance of the train is the most adverse when the wind direction angle is 90°.The presence of a U-shaped track can effectively reduce the lateral force,lift,and yawing moment of the train.The aerodynamic performance of the first suspension bogie at the bottom,which is the worst,will also be effectively improved.Next,the aerodynamic effects of different side track heights on the HTS maglev train were studied.An increase in side track height will reduce the lift and lateral force of the train,while the increase in drag is relatively small.Under the premise of ensuring passengers can conveniently alight,we found that a U-shaped track with a side track height of 960 mm has the best aerodynamic performance.The research findings offer a valuable reference for the engineering application and design of the track structure of HTS maglev train systems.展开更多
Virtual coupling is a novel technology that enables trains to run closely together without physical connections through communication and automation systems.The paper addresses an adaptive polynomial approximation alg...Virtual coupling is a novel technology that enables trains to run closely together without physical connections through communication and automation systems.The paper addresses an adaptive polynomial approximation algorithm for the cooperative control of high-speed trains(HSTs)under virtual coupling.It aims to solve the cooperative tracking control problem of HST formation operations under various scenarios,including known and unknown parameters.To enable the HST formation system to achieve cooperative operation while ensuring an appropriate spacing distance,the tracking errors of displacement and speed throughout the entire operation converge to zero.The proposed control strategy focuses on adopting polynomial approximation to handle unknown parameters,which are estimated via adaptive laws.Additionally,the unknown parameters of the HSTs are estimated online through adaptive laws.Experimental results verify the effectiveness of this method.展开更多
Purpose–This paper aims to analyze the transverse vibration characteristics of the high speed train window glass when passing through tunnel.Design/methodology/approach–The lateral vibration acceleration response of...Purpose–This paper aims to analyze the transverse vibration characteristics of the high speed train window glass when passing through tunnel.Design/methodology/approach–The lateral vibration acceleration response of glass chamber of high-speed train CR400BF-A on Beijing-Chengdu high-speed railway was tested at different speeds through the tunnel entrance,exit,tunnel interior,Tunnel Group and rendezvous time in the tunnel,the lateral distribution characteristics of vibration frequency and vibration power amplification coefficient of glass of high-speed train were analyzed.Findings–The results show that:The vibration of the high-speed train glass increases significantly during the tunnel,and the amplitude of vibration acceleration in the tunnel is significantly higher than outside the tunnel as the travel speed increases;the amplitude of lateral vibration acceleration of the glass of a high-speed train does not vary with changes in tunnel length and is not affected by the aerodynamic effects of the tunnel when traveling inside the tunnel,but its vibrations create noticeable fluctuations during variations when encountering oncoming traffic;The vibration characteristics of the high-speed train glass are forced harmonic vibrations,the excitation frequency does not vary with travel speed and travel position changes inside and outside the tunnel.The lateral vibration acceleration of the glass of a high-speed train is applied vertically and uniformly to the glass surface as an“inertial force”and creates a cyclic bending vibration stress that can easily lead to fatigue damage.Originality/value–The research results provide guidance for the prevention of glass failure in high-speed trains.展开更多
With technological advancements,high-speed rail has emerged as a prevalent mode of transportation.During travel,passengers exhibit a growing demand for streaming media services.However,the high-speed mobile networks e...With technological advancements,high-speed rail has emerged as a prevalent mode of transportation.During travel,passengers exhibit a growing demand for streaming media services.However,the high-speed mobile networks environment poses challenges,including frequent base station handoffs,which significantly degrade wireless network transmission performance.Improving transmission efficiency in high-speed mobile networks and optimizing spatiotemporal wireless resource allocation to enhance passengers’media experiences are key research priorities.To address these issues,we propose an Adaptive Cross-Layer Optimization Transmission Method with Environment Awareness(ACOTM-EA)tailored for high-speed rail streaming media.Within this framework,we develop a channel quality prediction model utilizing Kalman filtering and an algorithm to identify packet loss causes.Additionally,we introduce a proactive base station handoffstrategy to minimize handoffrelated disruptions and optimize resource distribution across adjacent base stations.Moreover,this study presents a wireless resource allocation approach based on an enhanced genetic algorithm,coupled with an adaptive bitrate selection mechanism,to maximize passenger Quality of Experience(QoE).To evaluate the proposed method,we designed a simulation experiment and compared ACOTM-EA with established algorithms.Results indicate that ACOTM-EA improves throughput by 11%and enhances passengers’media experience by 5%.展开更多
The integration of high-speed railway communication systems with 5G technology is widely recognized as a significant development.Due to the considerable mobility of trains and the complex nature of the environment,the...The integration of high-speed railway communication systems with 5G technology is widely recognized as a significant development.Due to the considerable mobility of trains and the complex nature of the environment,the wireless channel exhibits non-stationary characteristics and fast time-varying characteristics,which presents significant hurdles in terms of channel estimation.In addition,the use of massive MIMO technology in the context of 5G networks also leads to an increase in the complexity of estimation.To address the aforementioned issues,this paper presents a novel approach for channel estimation in high mobility scenarios using a reconstruction and recovery network.In this method,the time-frequency response of the channel is considered as a two-dimensional image.The Fast Super-Resolution Convolution Neural Network(FSRCNN)is used to first reconstruct channel images.Next,the Denoising Convolution Neural Network(DnCNN)is applied to reduce the channel noise and improve the accuracy of channel estimation.Simulation results show that the accuracy of the channel estimation model surpasses that of the standard channel estimation method,while also exhibiting reduced algorithmic complexity.展开更多
Demand-responsive transportation has been introduced in many cities around the world.However,whether it is applicable in the railway is still questionable,an exploration of passenger choice behavior between demandresp...Demand-responsive transportation has been introduced in many cities around the world.However,whether it is applicable in the railway is still questionable,an exploration of passenger choice behavior between demandresponsive trains and pre-scheduled trains is pivotal in addressing this issue.To delve into passengers’choice preferences when facing demand-responsive trains and to dissect the feasibility of implementing demandresponsive service in high-speed railways,the stated preference survey method is employed to investigate travel intention of passengers.Based on the survey data obtained in China,the heterogeneity of passengers is analyzed from three aspects:personal socio-economic characteristics,travel characteristics,and travel mode choice.Considering the situation that demand-responsive train cannot operate,the risk attributes are considered.To bolster the appeal of demand-responsive trains,personalized service product attributes are added.Mixed Logit mode,which takes into account the heterogeneous travel choice behavior of passengers,is developed,and Maximum Likelihood Estimation and the Monte Carlo method are used to calibrate model parameters.The willingness to pay in terms of different factors of passengers is determined.The results indicate that early arrival deviation time,late arrival deviation time,demand response time,and success rate of ticket purchase remarkable influence passengers’decision regarding demand-responsive train,with only the success rate of ticket purchase positively impacting train choice.Moreover,the significant difference in train ticket price is observed solely in the self-funded long distance scenario,while demand-responsive trains are found to be particularly appealing in self-funded short distance scenario.Through the Willingness To Pay(WTP)analysis,it is discovered that by shortening demand response time,enhancing the success rate of ticket purchase,and minimizing the deviation times of early arrival and late arrival of trains,the attractiveness of the demand-responsive train to passengers under three travel scenarios can be augmented.This study provides profound insights into the possibility of railway enterprises operating demand-responsive trains.展开更多
Typically,seat or floor acceleration is used to evaluate the ride comfort of a high-speed train.However,the dynamic performance of the human body significantly differs from that of the floor.Therefore,using the car bo...Typically,seat or floor acceleration is used to evaluate the ride comfort of a high-speed train.However,the dynamic performance of the human body significantly differs from that of the floor.Therefore,using the car body floor and seat accelerations to calculate the ride comfort index of a high-speed train may not reflect the true feelings of passengers.In this study,a 3D human-seat-vehicle-track coupling model was established to investigate the ride comfort of highspeed train passengers.The seated human model,which considers the longitudinal,lateral,vertical,pitching,yawing,and rolling motions,comprises the head,upper torso,lower torso,pelvis,thighs,and shanks.The model parameters were determined using multi-axis excitation measurement data based on a genetic algorithm.Subsequently,the applicability of the small-angle assumption and natural modes of the human model is analyzed.Using the coupling system model,the vibration characteristics of the human-seat interaction surface were analyzed.The ride comfort of the high-speed train and human body dynamic performance were analyzed under normal conditions,track geometric irregularities and train meeting conditions.The results showed that the passenger seats in the front and rear rows adjacent to the window had a higher acceleration value than the others.The human backrest and seat pad connection points have higher vibration amplitudes than the car body floor in the human-sensitive frequency range,indicating that using the acceleration values on the floor may underestimate the discomfort of passengers.The ride comfort of high-speed trains diminishes in the presence of track geometric irregularities and when trains pass each other.When the excitation frequency of track geometry irregularities approached the natural frequency of the human-seat-vehicle system,ride comfort in high-speed trains decreased significantly.Moreover,using seat acceleration to evaluate passenger ride comfort overlooks the vibration characteristics of the human body.The transient aerodynamic force generated when the train meets can cause a larger car body roll and lateral motion at 2 Hz,which,in turn,decreases the passenger ride comfort.This study presents a detailed human-seat-vehicle-track coupling system that can reflect a passenger’s dynamic performance under complex operating conditions.展开更多
High-speed trains often use temperature sensors to monitor the motion state of bearings.However,the temperature of bearings can be affected by factors such as weather and faults.Therefore,it is necessary to analyze in...High-speed trains often use temperature sensors to monitor the motion state of bearings.However,the temperature of bearings can be affected by factors such as weather and faults.Therefore,it is necessary to analyze in detail the relationship between the bearing temperature and influencing factors.In this study,a dynamics model of the axle box bearing of high-speed trains is established.The model can obtain the contact force between the rollers and raceway and its change law when the bearing contains outer-ring,inner-ring,and rolling-element faults.Based on the model,a thermal network method is introduced to study the temperature field distribution of the axle box bearings of high-speed trains.In this model,the heat generation,conduction,and dispersion of the isothermal nodes can be solved.The results show that the temperature of the contact point between the outer-ring raceway and rolling-elements is the highest.The relationships between the node temperature and the speed,fault type,and fault size are analyzed,finding that the higher the speed,the higher the node temperature.Under different fault types,the node temperature first increases and then decreases as the fault size increases.The effectiveness of the model is demonstrated using the actual temperature data of a high-speed train.This study proposes a thermal network model that can predict the temperature of each component of the bearings on a high-speed train under various speed and fault conditions.展开更多
Fault detection and isolation of high-speed train suspension systems is of critical importance to guarantee train running safety. Firstly, the existing methods concerning fault detection or isolation of train suspensi...Fault detection and isolation of high-speed train suspension systems is of critical importance to guarantee train running safety. Firstly, the existing methods concerning fault detection or isolation of train suspension systems are briefly reviewed and divided into two categories, i.e., model-based and data-driven approaches. The advantages and disadvantages of these two categories of approaches are briefly summarized. Secondly, a 1D convolution network-based fault diagnostic method for highspeed train suspension systems is designed. To improve the robustness of the method, a Gaussian white noise strategy(GWN-strategy) for immunity to track irregularities and an edge sample training strategy(EST-strategy) for immunity to wheel wear are proposed. The whole network is called GWN-EST-1 DCNN method. Thirdly, to show the performance of this method, a multibody dynamics simulation model of a high-speed train is built to generate the lateral acceleration of a bogie frame corresponding to different track irregularities, wheel profiles, and secondary suspension faults. The simulated signals are then inputted into the diagnostic network, and the results show the correctness and superiority of the GWN-EST-1DCNN method. Finally,the 1DCNN method is further validated using tracking data of a CRH3 train running on a high-speed railway line.展开更多
The on-board diagnosis network is the nervous system of high-speed Maglev trains, connecting all controller sensors, and corresponding devices to realize the information acquisition and control. In order to study the ...The on-board diagnosis network is the nervous system of high-speed Maglev trains, connecting all controller sensors, and corresponding devices to realize the information acquisition and control. In order to study the on-board diagnosis network＇s security and reliability, a simulation model for the on-board diagnosis network of high-speed Maglev trains with the optimal network engineering tool （OPNET） was built to analyze the network＇s performance, such as response error and bit error rate on the network load, throughput, and node-state response. The simulation model was verified with an actual on-board diagnosis network structure. The results show that the model results obtained are in good agreement with actual system performance and can be used to achieve actual communication network optimization and control algorithms.展开更多
High-speed train communication system is a typical high-mobility wireless communication network. Resource allocation problem has a great impact on the system performance. However, conventional resource allocation appr...High-speed train communication system is a typical high-mobility wireless communication network. Resource allocation problem has a great impact on the system performance. However, conventional resource allocation approaches in cellular network cannot be directly applied to this kind of special communication environment. A multidomain resource allocation strategy was proposed in the orthogonal frequency-division multiple access(OFDMA) of high-speed. By analyzing the effect of Doppler shift, sub-channels, antennas, time slots and power were jointly considered to maximize the energy efficiency under the constraint of total transmission power. For the purpose of reducing the computational complexity, noisy chaotic neural network algorithm was used to solve the above optimization problem. Simulation results showed that the proposed resource allocation method had a better performance than the traditional strategy.展开更多
The China's high-speed railway is experiencing a rapid growth.Its operating mileage and the number of operating trains will exceed 45 000 km and 1500 trains by 2015,respectively.During the long range and constant ...The China's high-speed railway is experiencing a rapid growth.Its operating mileage and the number of operating trains will exceed 45 000 km and 1500 trains by 2015,respectively.During the long range and constant high-speed operation,the high-speed trains have extremely complex and varied work conditions.Such a situation creates a huge demand for high-speed train on-board monitoring.In this paper,architecture for high-speed train on-board monitoring sensor network is proposed.This architecture is designed to achieve the goals of reliable sensing,scalable data transporting,and easy management.The three design goals are realized separately.The reliable sensing is achieved by deploying redundant sensor nodes in the same components.Then a hierarchal transporting scheme is involved to meet the second goal.Finally,an electronic-tag based addressing method is introduced to solve the management problem.展开更多
Based on the discrete time method, an effective movement control model is designed for a group of high- speed trains on a rail network. The purpose of the model is to investigate the specific traffic characteristics o...Based on the discrete time method, an effective movement control model is designed for a group of high- speed trains on a rail network. The purpose of the model is to investigate the specific traffic characteristics of high-speed trains under the interruption of stochastic irregular events. In the model, the high-speed rail traffic system is supposed to be equipped with the moving-block signalling system to guarantee maximum traversing capacity of the railway. To keep the safety of trains＇ movements, some operational strategies are proposed to control the movements of trains in the model, including traction operation, braking operation, and entering-station operation. The numerical simulations show that the designed model can well describe the movements of high-speed trains on the rail network. The research results can provide the useful information not only for investigating the propagation features of relevant delays under the irregular disturbance but also for rerouting and reseheduling trains on the rail network.展开更多
Data-driven methods are widely considered for fault diagnosis in complex systems.However,in practice,the between-class imbalance due to limited faulty samples may deteriorate their classification performance.To addres...Data-driven methods are widely considered for fault diagnosis in complex systems.However,in practice,the between-class imbalance due to limited faulty samples may deteriorate their classification performance.To address this issue,synthetic minority methods for enhancing data have been proved to be effective in many applications.Generative adversarial networks(GANs),capable of automatic features extraction,can also be adopted for augmenting the faulty samples.However,the monitoring data of a complex system may include not only continuous signals but also discrete/categorical signals.Since the current GAN methods still have some challenges in handling such heterogeneous monitoring data,a Mixed Dual Discriminator GAN(noted as M-D2GAN)is proposed in this work.In order to render the expanded fault samples more aligned with the real situation and improve the accuracy and robustness of the fault diagnosis model,different types of variables are generated in different ways,including floating-point,integer,categorical,and hierarchical.For effectively considering the class imbalance problem,proper modifications are made to the GAN model,where a normal class discriminator is added.A practical case study concerning the braking system of a high-speed train is carried out to verify the effectiveness of the proposed framework.Compared to the classic GAN,the proposed framework achieves better results with respect to F-measure and G-mean metrics.展开更多
基金Natural Science Foundation of Shandong Province(Grant No.ZR2022ME180)the National Natural Science Foundation of China(Grant No.51705267).
文摘High-speed trains operating in freezing rain are highly susceptible to severe ice accretion in the pantograph region,which compromises both power transmission efficiency and dynamic performance.To elucidate the underlying mechanisms of this phenomenon,an Euler-Euler multiphase flow model was employed to simulate droplet impingement and collection on the pantograph surface,while a glaze-ice formation model incorporating wall film dynamics was used to capture the subsequent growth of ice.The effects of key parameters—including liquid water content,ambient temperature,train velocity,and droplet diameter—on the amount and morphology of ice were systematically investigated.The results show that ice accumulation intensifies with increasing liquid water content decreasing ambient temperature,and rising train speed.In contrast,larger droplet diameters reduce the overall ice mass but promote localized accretion on major structural elements.This behavior arises because larger droplets,with greater inertia,are less susceptible to entrainment by airflow into the pantograph's base region.During extended operation,substantial ice buildup develops on the pantograph head and upper and lower arms,severely impairing current collection from the overhead line and hindering the pantograph's lifting and lowering motions.
基金Project(12372049)supported by the National Natural Science Foundation of ChinaProject(2682023ZTPY036)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(2023TPL-T06)supported by the Independent Project of State Key Laboratory of Rail Transit Vehicle System,China。
文摘Ventilation systems are critical for improving the cabin environment in high-speed trains,and their interest has increased significantly.However,whether air supply non-verticality deteriorates the cabin air environment,and the flow mechanism behind it and the degree of deterioration are not known.This study first analyzes the interaction between deflection angle and cabin flow field characteristics and ventilation performance.The results revealed that the interior temperature and pollutant concentration decreased slightly with increasing deflection angle,but resulted in significant deterioration of thermal comfort and air quality.This is evidenced by an increase in both draught rate and non-uniformity coefficient,an increase in the number of measurement points that do not satisfy the micro-wind speed and temperature difference requirements by about 5% and 15%,respectively,and an increase in longitudinal penetration of pollutants by a factor of about 5 and the appearance of locking regions at the ends of cabin.The results also show that changing the deflection pattern only affects the region of deterioration and does not essentially improve this deterioration.This study can provide reference and help for the ventilation design of high-speed trains.
文摘Purpose–Regarding that Ultraviolet radiation,pollutant adsorption,and environmental changes may be the main reasons for the aging and yellowing on windshield rubber in high-speed trains,countermeasures are proposed to solve the aging and yellowing of windshield rubber and reduce the adverse effects caused by rubber yellowing.Design/methodology/approach–Scanning electron microscopy(SEM)and energy dispersive spectroscopy(EDS)were used to test the yellowed windshield rubber.Aging tests,including UVaging,natural aging and salt spray aging,were conducted to analyze the effects of aging on the windshield rubber.Different cleaning agents were selected to soak the windshield rubber,and the quality,hardness,and surface appearance of the rubber samples were tested.Findings–After UV aging,antioxidants migrated to the surface of the windshield rubber,but due to oxidation failure,they could not capture free radicals,leading to continued oxidation reactions within the material and resulting in yellowing of the rubber in a short period of time.Originality/value–Cleaning agents have a minimal impact on windshield rubber,UV aging has the greatest impact and natural aging is a gradual and slow deterioration process.Through daily deep cleaning and maintenance with protective agents at regular intervals,the deterioration of windshield rubber yellowing in high-speed trains can be effectively suppressed.
基金supported by the Fundamental Research Funds for the Central Universities(No.2024JBZX027)the National Natural Science Foundation of China(No.52375078).
文摘High-Speed Trains (HSTs) have emerged as a mainstream mode of transportation in China, owing to their exceptional safety and efficiency. Ensuring the reliable operation of HSTs is of paramount economic and societal importance. As critical rotating mechanical components of the transmission system, bearings make their fault diagnosis a topic of extensive attention. This paper provides a systematic review of image encoding-based bearing fault diagnosis methods tailored to the condition monitoring of HSTs. First, it categorizes the image encoding techniques applied in the field of bearing fault diagnosis. Then, a review of state-of-the-art studies has been presented, encompassing both monomodal image conversion and multimodal image fusion approaches. Finally, it highlights current challenges and proposes future research directions to advance intelligent fault diagnosis in HSTs, aiming to provide a valuable reference for researchers and engineers in the field of intelligent operation and maintenance.
基金National Natural Science Foundation of China(No.52388102)New Cornerstone Science Foundation through the Xplorer Prize.
文摘The dynamic performance of high-speed trains is significantly influenced by sudden changes in aerodynamic loads(ADLs)when exiting a tunnel in a windy environment.Focusing on a double-track tunnel under construction in a mountain railway,we established an aerodynamic model involving a train exiting the tunnel,and verified it in the Fluent environment.Overset mesh technology was adopted to characterize the train’s movement.The flow field involving the train,tunnel,and crosswinds was simulated using the Reynolds-averaged turbulence model.Then,we built a comprehensive train-track coupled dynamic model considering the influences of ADLs,to investigate the vehicles’dynamic responses.The aerodynamics and dynamic behaviors of the train when affected by crosswinds with different velocities and directions are analyzed and discussed.The results show that the near-wall side crosswind leads to sharper variations in ADLs than the far-wall side crosswind.The leading vehicle suffers from more severe ADLs than other vehicles,which worsens the wheel-rail interaction and causes low-frequency vibration of the car body.When the crosswind velocity exceeds 20 m/s,significant wheel-rail impacts occur,and the running safety of the train worsens rapidly.
基金Supported by the Sichuan Science and Technology Program(Grant No.2023ZDZX0008)the National Natural Science Foundation of China(Grant No.52388102)the New Cornerstone Science Foundation through the XPLORER PRIZE.
文摘The interaction between the airflow and train influences the aerodynamic characteristics and dynamic performance of high-speed trains.This study focused on the fluid-solid coupling effect of airflow and HST,and proposed a co-simulation(CS)approach between computational fluid dynamics and multi-body dynamics.Firstly,the aerodynamic model was developed by employing overset mesh technology and the finite volume method,and the detailed train-track coupled dynamic model was established.Then the User Data Protocol was adopted to build data communication channels.Moreover,the proposed CS method was validated by comparison with a reported field test result.Finally,a case study of the HST exiting a tunnel subjected to crosswind was conducted to compare differences between CS and offline simulation(OS)methods.In terms of the presented case,the changing trends of aerodynamic forces and car-body displacements calculated by the two methods were similar.Differences mainly lie in aerodynamic moments and transient wheel-rail impacts.Maximum pitching and yawing moments on the head vehicle in the two methods differ by 21.1 kN∙m and 29.6 kN∙m,respectively.And wheel-rail impacts caused by sudden changes in aerodynamic loads are significantly severer in CS.Wheel-rail safety indices obtained by CS are slightly greater than those by OS.This research proposes a CS method for aerodynamic characteristics and dynamic performance of the HST in complex scenarios,which has superiority in computational efficiency and stability.
基金supported by the National Natural Science Foundation of China(No.U23A20681)the S&T Program of Hebei Province,China(No.23567602H).
文摘Currently,the design of high-temperature superconducting(HTS)maglev trains adopts a U-shaped track operation mode,and the height of the side track significantly impacts the train’s aerodynamic characteristics.In this study,we used computational fluid dynamics(CFD)methods,based on the 3D Reynolds-averaged Navier-Stokes(RANS)method and shear stress transport(SST)k-ωturbulence model,to deeply investigate the effects of the presence or absence of a U-shaped track and different side track heights(800,880,and 960 mm)on the pressure distribution,velocity distribution,and flow field structure of HTS maglev trains at a speed of 400 km/h under crosswinds.The numerical methods were verified using a scaled ICE-2 model wind tunnel test.First,the aerodynamic characteristics of the train under different wind direction angles with and without side tracks were studied.We found that the aerodynamic performance of the train is the most adverse when the wind direction angle is 90°.The presence of a U-shaped track can effectively reduce the lateral force,lift,and yawing moment of the train.The aerodynamic performance of the first suspension bogie at the bottom,which is the worst,will also be effectively improved.Next,the aerodynamic effects of different side track heights on the HTS maglev train were studied.An increase in side track height will reduce the lift and lateral force of the train,while the increase in drag is relatively small.Under the premise of ensuring passengers can conveniently alight,we found that a U-shaped track with a side track height of 960 mm has the best aerodynamic performance.The research findings offer a valuable reference for the engineering application and design of the track structure of HTS maglev train systems.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.62203246 and 62003127)Shandong Provincial Natural Science Foundation(Grant No.ZR2024QF041)the Natural Science Foundation of Hebei Province(Grant No.F2023202060)。
文摘Virtual coupling is a novel technology that enables trains to run closely together without physical connections through communication and automation systems.The paper addresses an adaptive polynomial approximation algorithm for the cooperative control of high-speed trains(HSTs)under virtual coupling.It aims to solve the cooperative tracking control problem of HST formation operations under various scenarios,including known and unknown parameters.To enable the HST formation system to achieve cooperative operation while ensuring an appropriate spacing distance,the tracking errors of displacement and speed throughout the entire operation converge to zero.The proposed control strategy focuses on adopting polynomial approximation to handle unknown parameters,which are estimated via adaptive laws.Additionally,the unknown parameters of the HSTs are estimated online through adaptive laws.Experimental results verify the effectiveness of this method.
基金supported by grants from the National Key Research and Development Program(Grant Nos.2023YFC3806205).
文摘Purpose–This paper aims to analyze the transverse vibration characteristics of the high speed train window glass when passing through tunnel.Design/methodology/approach–The lateral vibration acceleration response of glass chamber of high-speed train CR400BF-A on Beijing-Chengdu high-speed railway was tested at different speeds through the tunnel entrance,exit,tunnel interior,Tunnel Group and rendezvous time in the tunnel,the lateral distribution characteristics of vibration frequency and vibration power amplification coefficient of glass of high-speed train were analyzed.Findings–The results show that:The vibration of the high-speed train glass increases significantly during the tunnel,and the amplitude of vibration acceleration in the tunnel is significantly higher than outside the tunnel as the travel speed increases;the amplitude of lateral vibration acceleration of the glass of a high-speed train does not vary with changes in tunnel length and is not affected by the aerodynamic effects of the tunnel when traveling inside the tunnel,but its vibrations create noticeable fluctuations during variations when encountering oncoming traffic;The vibration characteristics of the high-speed train glass are forced harmonic vibrations,the excitation frequency does not vary with travel speed and travel position changes inside and outside the tunnel.The lateral vibration acceleration of the glass of a high-speed train is applied vertically and uniformly to the glass surface as an“inertial force”and creates a cyclic bending vibration stress that can easily lead to fatigue damage.Originality/value–The research results provide guidance for the prevention of glass failure in high-speed trains.
基金substantially supported by the National Natural Science Foundation of China under Grant No.62002263in part by Tianjin Municipal Education Commission Research Program Project under 2022KJ012Tianjin Science and Technology Program Projects:24YDTPJC00630.
文摘With technological advancements,high-speed rail has emerged as a prevalent mode of transportation.During travel,passengers exhibit a growing demand for streaming media services.However,the high-speed mobile networks environment poses challenges,including frequent base station handoffs,which significantly degrade wireless network transmission performance.Improving transmission efficiency in high-speed mobile networks and optimizing spatiotemporal wireless resource allocation to enhance passengers’media experiences are key research priorities.To address these issues,we propose an Adaptive Cross-Layer Optimization Transmission Method with Environment Awareness(ACOTM-EA)tailored for high-speed rail streaming media.Within this framework,we develop a channel quality prediction model utilizing Kalman filtering and an algorithm to identify packet loss causes.Additionally,we introduce a proactive base station handoffstrategy to minimize handoffrelated disruptions and optimize resource distribution across adjacent base stations.Moreover,this study presents a wireless resource allocation approach based on an enhanced genetic algorithm,coupled with an adaptive bitrate selection mechanism,to maximize passenger Quality of Experience(QoE).To evaluate the proposed method,we designed a simulation experiment and compared ACOTM-EA with established algorithms.Results indicate that ACOTM-EA improves throughput by 11%and enhances passengers’media experience by 5%.
基金funded in part by the National Natural Science Foundation of China(62261024 and U2001213)in part by National Key Research and Development Project(2020YFB1807204)+2 种基金in part by Science and Technology Project of Education Department of Jiangxi Province(GJJ214606 and GJJ2205201)in part by Key Laboratory of Universal Wireless Communications(BUPT),Ministry of Education,P.R.China(KFKT-2022101)in part by the Jiangxi Provincial Natural Science Foundation(20212BAB212001)。
文摘The integration of high-speed railway communication systems with 5G technology is widely recognized as a significant development.Due to the considerable mobility of trains and the complex nature of the environment,the wireless channel exhibits non-stationary characteristics and fast time-varying characteristics,which presents significant hurdles in terms of channel estimation.In addition,the use of massive MIMO technology in the context of 5G networks also leads to an increase in the complexity of estimation.To address the aforementioned issues,this paper presents a novel approach for channel estimation in high mobility scenarios using a reconstruction and recovery network.In this method,the time-frequency response of the channel is considered as a two-dimensional image.The Fast Super-Resolution Convolution Neural Network(FSRCNN)is used to first reconstruct channel images.Next,the Denoising Convolution Neural Network(DnCNN)is applied to reduce the channel noise and improve the accuracy of channel estimation.Simulation results show that the accuracy of the channel estimation model surpasses that of the standard channel estimation method,while also exhibiting reduced algorithmic complexity.
基金supported by the National Natural Science Foundation of China(No.72471023,71971019)the Fundamental Research Funds for the Central Universities(No.2024QYBS025).
文摘Demand-responsive transportation has been introduced in many cities around the world.However,whether it is applicable in the railway is still questionable,an exploration of passenger choice behavior between demandresponsive trains and pre-scheduled trains is pivotal in addressing this issue.To delve into passengers’choice preferences when facing demand-responsive trains and to dissect the feasibility of implementing demandresponsive service in high-speed railways,the stated preference survey method is employed to investigate travel intention of passengers.Based on the survey data obtained in China,the heterogeneity of passengers is analyzed from three aspects:personal socio-economic characteristics,travel characteristics,and travel mode choice.Considering the situation that demand-responsive train cannot operate,the risk attributes are considered.To bolster the appeal of demand-responsive trains,personalized service product attributes are added.Mixed Logit mode,which takes into account the heterogeneous travel choice behavior of passengers,is developed,and Maximum Likelihood Estimation and the Monte Carlo method are used to calibrate model parameters.The willingness to pay in terms of different factors of passengers is determined.The results indicate that early arrival deviation time,late arrival deviation time,demand response time,and success rate of ticket purchase remarkable influence passengers’decision regarding demand-responsive train,with only the success rate of ticket purchase positively impacting train choice.Moreover,the significant difference in train ticket price is observed solely in the self-funded long distance scenario,while demand-responsive trains are found to be particularly appealing in self-funded short distance scenario.Through the Willingness To Pay(WTP)analysis,it is discovered that by shortening demand response time,enhancing the success rate of ticket purchase,and minimizing the deviation times of early arrival and late arrival of trains,the attractiveness of the demand-responsive train to passengers under three travel scenarios can be augmented.This study provides profound insights into the possibility of railway enterprises operating demand-responsive trains.
基金Supported by National Natural Science Foundation of China(Grant No.U1934203)Research and Development Project of Science and Technology of China Railway Corporation(Grant No.P2023T002)。
文摘Typically,seat or floor acceleration is used to evaluate the ride comfort of a high-speed train.However,the dynamic performance of the human body significantly differs from that of the floor.Therefore,using the car body floor and seat accelerations to calculate the ride comfort index of a high-speed train may not reflect the true feelings of passengers.In this study,a 3D human-seat-vehicle-track coupling model was established to investigate the ride comfort of highspeed train passengers.The seated human model,which considers the longitudinal,lateral,vertical,pitching,yawing,and rolling motions,comprises the head,upper torso,lower torso,pelvis,thighs,and shanks.The model parameters were determined using multi-axis excitation measurement data based on a genetic algorithm.Subsequently,the applicability of the small-angle assumption and natural modes of the human model is analyzed.Using the coupling system model,the vibration characteristics of the human-seat interaction surface were analyzed.The ride comfort of the high-speed train and human body dynamic performance were analyzed under normal conditions,track geometric irregularities and train meeting conditions.The results showed that the passenger seats in the front and rear rows adjacent to the window had a higher acceleration value than the others.The human backrest and seat pad connection points have higher vibration amplitudes than the car body floor in the human-sensitive frequency range,indicating that using the acceleration values on the floor may underestimate the discomfort of passengers.The ride comfort of high-speed trains diminishes in the presence of track geometric irregularities and when trains pass each other.When the excitation frequency of track geometry irregularities approached the natural frequency of the human-seat-vehicle system,ride comfort in high-speed trains decreased significantly.Moreover,using seat acceleration to evaluate passenger ride comfort overlooks the vibration characteristics of the human body.The transient aerodynamic force generated when the train meets can cause a larger car body roll and lateral motion at 2 Hz,which,in turn,decreases the passenger ride comfort.This study presents a detailed human-seat-vehicle-track coupling system that can reflect a passenger’s dynamic performance under complex operating conditions.
基金National Key R&D Program(Grant No.2020YFB2007700),National Natural Science Foundation of China(Grant Nos.11790282,12032017,12002221 and 11872256)S&T Program of Hebei(Grant No.20310803D)+1 种基金Natural Science Foundation of Hebei Province(Grant No.A2020210028)State Foundation for Studying Abroad.
文摘High-speed trains often use temperature sensors to monitor the motion state of bearings.However,the temperature of bearings can be affected by factors such as weather and faults.Therefore,it is necessary to analyze in detail the relationship between the bearing temperature and influencing factors.In this study,a dynamics model of the axle box bearing of high-speed trains is established.The model can obtain the contact force between the rollers and raceway and its change law when the bearing contains outer-ring,inner-ring,and rolling-element faults.Based on the model,a thermal network method is introduced to study the temperature field distribution of the axle box bearings of high-speed trains.In this model,the heat generation,conduction,and dispersion of the isothermal nodes can be solved.The results show that the temperature of the contact point between the outer-ring raceway and rolling-elements is the highest.The relationships between the node temperature and the speed,fault type,and fault size are analyzed,finding that the higher the speed,the higher the node temperature.Under different fault types,the node temperature first increases and then decreases as the fault size increases.The effectiveness of the model is demonstrated using the actual temperature data of a high-speed train.This study proposes a thermal network model that can predict the temperature of each component of the bearings on a high-speed train under various speed and fault conditions.
基金supported by the National Nature Science Foundation of China(No.71871188)the Fundamental Research Funds for the Central Universities(No.2682021CX051)supported by China Scholarship Council(No.201707000113)。
文摘Fault detection and isolation of high-speed train suspension systems is of critical importance to guarantee train running safety. Firstly, the existing methods concerning fault detection or isolation of train suspension systems are briefly reviewed and divided into two categories, i.e., model-based and data-driven approaches. The advantages and disadvantages of these two categories of approaches are briefly summarized. Secondly, a 1D convolution network-based fault diagnostic method for highspeed train suspension systems is designed. To improve the robustness of the method, a Gaussian white noise strategy(GWN-strategy) for immunity to track irregularities and an edge sample training strategy(EST-strategy) for immunity to wheel wear are proposed. The whole network is called GWN-EST-1 DCNN method. Thirdly, to show the performance of this method, a multibody dynamics simulation model of a high-speed train is built to generate the lateral acceleration of a bogie frame corresponding to different track irregularities, wheel profiles, and secondary suspension faults. The simulated signals are then inputted into the diagnostic network, and the results show the correctness and superiority of the GWN-EST-1DCNN method. Finally,the 1DCNN method is further validated using tracking data of a CRH3 train running on a high-speed railway line.
基金supported by the National Natural Science Foundation of China (No. 51007074)the Program for New Century Excellent Talents in University(NECT-08-0825)+1 种基金the Research and Development Project of the National Railway Ministry (2011J016-B)The basic research universities special fund operations(SWJTU11CX141)
文摘The on-board diagnosis network is the nervous system of high-speed Maglev trains, connecting all controller sensors, and corresponding devices to realize the information acquisition and control. In order to study the on-board diagnosis network＇s security and reliability, a simulation model for the on-board diagnosis network of high-speed Maglev trains with the optimal network engineering tool （OPNET） was built to analyze the network＇s performance, such as response error and bit error rate on the network load, throughput, and node-state response. The simulation model was verified with an actual on-board diagnosis network structure. The results show that the model results obtained are in good agreement with actual system performance and can be used to achieve actual communication network optimization and control algorithms.
基金Supported by the National Natural Science Foundation of China(No.61302080)Scientific Research Starting Foundation of Fuzhou University(No.022572)Science and Technology Development Foundation of Fuzhou University(No.2013-XY-27)
文摘High-speed train communication system is a typical high-mobility wireless communication network. Resource allocation problem has a great impact on the system performance. However, conventional resource allocation approaches in cellular network cannot be directly applied to this kind of special communication environment. A multidomain resource allocation strategy was proposed in the orthogonal frequency-division multiple access(OFDMA) of high-speed. By analyzing the effect of Doppler shift, sub-channels, antennas, time slots and power were jointly considered to maximize the energy efficiency under the constraint of total transmission power. For the purpose of reducing the computational complexity, noisy chaotic neural network algorithm was used to solve the above optimization problem. Simulation results showed that the proposed resource allocation method had a better performance than the traditional strategy.
基金Project supported by the National Key Technology R&D Program(No.2011BAG05B00)the National Natural Science Foundation of China(No.61070155)
文摘The China's high-speed railway is experiencing a rapid growth.Its operating mileage and the number of operating trains will exceed 45 000 km and 1500 trains by 2015,respectively.During the long range and constant high-speed operation,the high-speed trains have extremely complex and varied work conditions.Such a situation creates a huge demand for high-speed train on-board monitoring.In this paper,architecture for high-speed train on-board monitoring sensor network is proposed.This architecture is designed to achieve the goals of reliable sensing,scalable data transporting,and easy management.The three design goals are realized separately.The reliable sensing is achieved by deploying redundant sensor nodes in the same components.Then a hierarchal transporting scheme is involved to meet the second goal.Finally,an electronic-tag based addressing method is introduced to solve the management problem.
基金Supported by the National Natural Science Foundation of China under Grant No. 70901006Research Foundation of Beijing Jiaotong University under Grant Nos. 2011JBM158, 2011JBM162Research Foundation of State Key Laboratory of Rail Traffic Control and Safety under Grant Nos. RCS2009ZT001, RCS2010ZZ001
文摘Based on the discrete time method, an effective movement control model is designed for a group of high- speed trains on a rail network. The purpose of the model is to investigate the specific traffic characteristics of high-speed trains under the interruption of stochastic irregular events. In the model, the high-speed rail traffic system is supposed to be equipped with the moving-block signalling system to guarantee maximum traversing capacity of the railway. To keep the safety of trains＇ movements, some operational strategies are proposed to control the movements of trains in the model, including traction operation, braking operation, and entering-station operation. The numerical simulations show that the designed model can well describe the movements of high-speed trains on the rail network. The research results can provide the useful information not only for investigating the propagation features of relevant delays under the irregular disturbance but also for rerouting and reseheduling trains on the rail network.
文摘Data-driven methods are widely considered for fault diagnosis in complex systems.However,in practice,the between-class imbalance due to limited faulty samples may deteriorate their classification performance.To address this issue,synthetic minority methods for enhancing data have been proved to be effective in many applications.Generative adversarial networks(GANs),capable of automatic features extraction,can also be adopted for augmenting the faulty samples.However,the monitoring data of a complex system may include not only continuous signals but also discrete/categorical signals.Since the current GAN methods still have some challenges in handling such heterogeneous monitoring data,a Mixed Dual Discriminator GAN(noted as M-D2GAN)is proposed in this work.In order to render the expanded fault samples more aligned with the real situation and improve the accuracy and robustness of the fault diagnosis model,different types of variables are generated in different ways,including floating-point,integer,categorical,and hierarchical.For effectively considering the class imbalance problem,proper modifications are made to the GAN model,where a normal class discriminator is added.A practical case study concerning the braking system of a high-speed train is carried out to verify the effectiveness of the proposed framework.Compared to the classic GAN,the proposed framework achieves better results with respect to F-measure and G-mean metrics.
