Dynamic analysis of axle box bearings on the high-speed train caused by wheel-rail excitation

To explore the impact of wheel-rail excitation on the dynamic performance of axle box bearings,a dynamic model of the high-speed train including axle box bearings is developed.Subsequently,the dynamic response characteristics of the axle box bearing are examined.The investigation focuses on the acceleration characteristics of bearing vibration under excitation of track irregularities and wheel flats.In addition,experiments on both normal and faulty bearings are conducted separately,and the correctness of the model and some conclusions are verified.According to the research,track irregularity is unfavorable for bearing fault detection based on resonance demodulation.Under the same speed conditions,the acceleration peak of bearing is inversely proportional to the length of the wheel flat and directly proportional to its depth.The paper will contribute to a deeper understanding of the dynamic performance of axle box bearings.

Torque effect on vibration behavior of high-speed train gearbox under internal and external excitations

The high-speed train transmission system,experiencing both the internal excitation originating from gear meshing and the external excitation originating from the wheel-rail interaction,exhibits complex dynamic behavior in the actual service environment.This paper focuses on the gearbox in the high-speed train to carry out the bench test,in which various operat-ing conditions(torques and rotation speeds)were set up and the excitation condition covering both internal and external was created.Acceleration responses on multiple positions of the gearbox were acquired in the test and the vibration behavior of the gearbox was studied.Meanwhile,a stochastic excitation modal test was also carried out on the test bench under different torques,and the modal parameter of the gearbox was identified.Finally,the sweep frequency response of the gearbox under gear meshing excitation was analyzed through dynamic modeling.The results showed that the torque has an attenuating effect on the amplitude of gear meshing frequency on the gearbox,and the effect of external excitation on the gearbox vibration cannot be ignored,especially under the rated operating condition.It was also found that the torque affects the modal param-eter of the gearbox significantly.The torque has a great effect on both the gear meshing stiffness and the bearing stiffness in the transmission system,which is the inherent reason for the changed modal characteristics observed in the modal test and affects the vibration behavior of the gearbox consequently.

Attack-Resilient Distributed Cooperative Control of Virtually Coupled High-Speed Trains via Topology Reconfiguration

Dear Editor,This letter addresses the resilient distributed cooperative control problem of a virtually coupled train convoy under stochastic disturbances and cyber attacks.The main purpose is to achieve distributed coordination of virtually coupled high-speed trains with the prescribed inter-train distance and same cruise velocity.

Influences of the Fresh Air Volume on the Removal of Cough-Released Droplets in a Passenger Car of a High-Speed Train Using CFD

The spread and removal of pollution sources,namely,cough-released droplets in three different areas(front,middle,and rear areas)of a fully-loaded passenger car in a high-speed train under different fresh air flow volume were studied using computational fluid dynamics(CFD)method.In addition,the structure of indoor flow fields was also analysed.The results show that the large eddies are more stable and flow faster in the air supply under Mode 2(fresh air volume:2200m3/h)compared to Mode 1(fresh air volume:1100m3/h).By analysing the spreading process of droplets sprayed at different locations in the passenger car and with different particle sizes,the removal trends for droplets are found to be similar under the two air supply modes.However,when increasing the fresh air flow volume,the droplets in the middle and front areas of the passenger car are removed faster.When the droplets had dispersed for 60s,Mode 2 exhibited a removal rate approximately 1%–3%higher than Mode 1 for small and medium-sized droplets with diameters of 10 and 50μm.While those in the rear area,the situation is reversed,with Mode 1 slightly surpassing Mode 2 by 1%–3%.For large droplets with a diameter of 100μm,both modes achieved a removal rate of over 96%in all three regions at the 60 s.The results can provide guidance for air supply modes of passenger cars of high-speed trains,thus suppressing the spread of virus-carrying droplets and reducing the risk of viral infection among passengers.

Measured load spectra of the bearing in high-speed train gearbox under different gear meshing conditions

The load spectrum is a crucial factor for assess-ing the fatigue reliability of in-service rolling element bear-ings in transmission systems.For a bearing in a high-speed train gearbox,a measurement technique based on strain detection of bearing outer ring was used to instrument the bearing and determine the time histories of the distributed load in the bearing under different gear meshing conditions.Accordingly,the load spectrum of the total radial load car-ried by the bearing was compiled.The mean value and class interval of the obtained load spectrum were found to vary non-monotonously with the speed and torque of gear mesh-ing,which was considered to be caused by the vibration of the shaft and the bearing cage.As the realistic service load input of bearing life assessment,the measured load spectrum under different gear meshing conditions can be used to pre-dict gearbox bearing life realistically based on the damage-equivalent principle and actual operating conditions.

Research Progress of Aerodynamic Multi-Objective Optimization on High-Speed Train Nose Shape

The aerodynamic optimization design of high-speed trains(HSTs)is crucial for energy conservation,environmental preservation,operational safety,and speeding up.This study aims to review the current state and progress of the aerodynamic multi-objective optimization of HSTs.First,the study explores the impact of train nose shape parameters on aerodynamic performance.The parameterization methods involved in the aerodynamic multiobjective optimization ofHSTs are summarized and classified as shape-based and disturbance-based parameterizationmethods.Meanwhile,the advantages and limitations of each parameterizationmethod,aswell as the applicable scope,are briefly discussed.In addition,the NSGA-II algorithm,particle swarm optimization algorithm,standard genetic algorithm,and other commonly used multi-objective optimization algorithms and the improvements in the field of aerodynamic optimization for HSTs are summarized.Second,this study investigates the aerodynamic multi-objective optimization technology for HSTs using the surrogate model,focusing on the Kriging surrogate models,neural network,and support vector regression.Moreover,the construction methods of surrogate models are summarized,and the influence of different sample infill criteria on the efficiency ofmulti-objective optimization is analyzed.Meanwhile,advanced aerodynamic optimization methods in the field of aircraft have been briefly introduced to guide research on the aerodynamic optimization of HSTs.Finally,based on the summary of the research progress of the aerodynamicmulti-objective optimization ofHSTs,future research directions are proposed,such as intelligent recognition technology of characteristic parameters,collaborative optimization of multiple operating environments,and sample infill criterion of the surrogate model.

Disturbance observer-based fuzzy fault-tolerant control for high-speed trains with multiple disturbances

The fault-tolerant control problem is investigated for high-speed trains with actuator faults and multiple disturbances.Based on the novel train model resulting from the Takagi–Sugeno fuzzy theory, a sliding-mode fault-tolerant control strategy is proposed. The norm bounded disturbances which are composed of interactive forces among adjacent carriages and basis running resistances are rearranged by the fuzzy linearity technique. The modeled disturbances described as an exogenous system are compensated for by a disturbance observer. Moreover, a sliding mode surface is constructed, which can transform the stabilization problem of position and velocity into the stabilization problem of position errors and velocity errors, i.e., the tracking problem of position and velocity. Based on the parallel distributed compensation method and the disturbance observer, the fault-tolerant controller is solved. The Lyapunov theory is used to prove the stability of the closed-loop system. The feasibility and effectiveness of the proposed fault-tolerant control strategy are illustrated by simulation results.

A trailer car dynamics model considering brake rigging of a high-speed train and its application

Brake systems are essential for the speed regulation or braking of a high-speed train.The vehicle dynamic performance under braking condition is complex and directly affects the reliability and running safety.To reveal the vehicle dynamic behaviour in braking process,a comprehensive trailer car dynamics model(TCDM)considering brake systems is established in this paper.The dynamic interactions between the brake system and the other connected components are achieved using the brake disc-pad frictions,brake suspension systems,and wheel-rail interactions.The force and motion transmission from the brake system to the wheel-rail interface is performed by the proposed TCDM excited by track irregularity.In addition,the validity of TCDM is verified by experimental test results.On this basis,the dynamic behaviour of the coupled system is simulated and discussed.The findings indicate that the braking force significantly affects vehicle dynamic behaviour including the wheel-rail forces,suspension forces,wheelset torsional vibration,etc.The dynamic interactions within the brake system are also significantly affected by the vehicle vibration due to track irregularity.Besides,the developed TCDM can be further employed to the dynamic assessment of such a coupled mechanical system under different braking conditions.

Vibration-based bearing fault diagnosis of high-speed trains:A literature review

Due to the advantages of comfort and safety,high-speed trains are gradually becoming the mainstream public transport in China.Since the operating speed and mileage of high-speed trains have achieved rapid growth,it is more and more urgent to ensure their reliability and safety.As an important component in the bogies of highspeed trains,the health state of the bearing directly affects the operational safety of the trains.It is therefore necessary to diagnoze the faults of bearings in the bogies of high-speed trains as early as possible.In this paper,the bearing fault diagnostic methods for high-speed trains have been systematically summarized with their challenges and perspectives.First,it briefly introduces the structure of bearings in the bogies as well as the fault characteristic frequencies.Then,a brief review of the research on vibration-based signal processing methods and machine learning methods has been provided.Finally,the challenges and future developments of vibrationbased bearing fault diagnostic methods for high-speed trains have been analyzed.

Research on fatigue evaluation method of high-speed train axle based on axle box acceleration

As a key safety component of the high-speed train, fatigue fracture of the axle would lead to major accidents such as derailment or overturning. The complexity of the axle dynamic stress test seriously enhances the difficulty of axle fatigue damage analysis. In this paper, the dynamic stress test of the high-speed train axle was carried out,the axle box acceleration was monitored on-track during the test, and the relationship between the axle stress spectrum and acceleration was analyzed on-track. The results show that the relationships between the axle equivalent stresses and the Root Mean Square(RMS) values of the axle box vertical acceleration and lateral acceleration exhibit a strong joint probability density distribution. The concept of the virtual surface density of wheel-rail contact is also proposed to realize the purpose of using axle box acceleration to deduce axle equivalent force. The results quantify the relationship between axle box acceleration and axle equivalent force, provide a new method for predicting the axle damage using the acceleration RMS values, and open up a new approach for structural health monitoring of high-speed train axles.

High-speed train cooperativecontrol based on fractional-ordersliding mode adaptive algorithm

Purpose–This study aims to propose an adaptive fractional-order sliding mode controller to solve the problem of train speed tracking control and position interval control under disturbance environment in moving block system,so as to improve the tracking efficiency and collision avoidance performance.Design/methodology/approach–The mathematical model of information interaction between trains is established based on algebraic graph theory,so that the train can obtain the state information of adjacent trains,and then realize the distributed cooperative control of each train.In the controller design,the sliding mode control and fractional calculus are combined to avoid the discontinuous switching phenomenon,so as to suppress the chattering of sliding mode control,and a parameter adaptive law is constructed to approximate the time-varying operating resistance coefficient.Findings–The simulation results show that compared with proportional integral derivative(PID)control and ordinary sliding mode control,the control accuracy of the proposed algorithm in terms of speed is,respectively,improved by 25%and 75%.The error frequency and fluctuation range of the proposed algorithm are reduced in the position error control,the error value tends to 0,and the operation trend tends to be consistent.Therefore,the control method can improve the control accuracy of the system and prove that it has strong immunity.Originality/value–The algorithm can reduce the influence of external interference in the actual operating environment,realize efficient and stable tracking of trains,and ensure the safety of train control.

Virtual sample generation for model-based prognostics and health management of on-board high-speed train control system

In view of class imbalance in data-driven modeling for Prognostics and Health Management(PHM),existing classification methods may fail in generating effective fault prediction models for the on-board high-speed train control equipment.A virtual sample generation solution based on Generative Adversarial Network(GAN)is proposed to overcome this shortcoming.Aiming at augmenting the sample classes with the imbalanced data problem,the GAN-based virtual sample generation strategy is embedded into the establishment of fault prediction models.Under the PHM framework of the on-board train control system,the virtual sample generation principle and the detailed procedures are presented.With the enhanced class-balancing mechanism and the designed sample augmentation logic,the PHM scheme of the on-board train control equipment has powerful data condition adaptability and can effectively predict the fault probability and life cycle status.Practical data from a specific type of on-board train control system is employed for the validation of the presented solution.The comparative results indicate that GAN-based sample augmentation is capable of achieving a desirable sample balancing level and enhancing the performance of correspondingly derived fault prediction models for the Condition-based Maintenance(CBM)operations.

Prediction of high-speed train delay propagation based on causal text information

The delay-causing text data contain valuable information such as the specific reasons for the delay,location and time of the disturbance,which can provide an efficient support for the prediction of train delays and improve the guidance of train control efficiency.Based on the train operation data and delay-causing data of the Wuhan-Guangzhou high-speed railway,the relevant algorithms in the natural language processing field are used to process the delay-causing text data.It also integrates the train operatingenvironment information and delay-causing text information so as to develop a cause-based train delay propagation prediction model.The Word2vec model is first used to vectorize the delay-causing text description after word segmentation.The mean model or the term frequency-inverse document frequency-weighted model is then used to generate the delay-causing sentence vector based on the original word vector.Afterward,the train operating-environment features and delay-causing sentence vector are input into the extreme gradient boosting(XGBoost)regression algorithm to develop a delay propagation prediction model.In this work,4 text feature processing methods and 8 regression algorithms are considered.The results demonstrate that the XGBoost regression algorithm has the highest prediction accuracy using the test features processed by the continuous bag of words and the mean models.Compared with the prediction model that only considers the train-operating-environment features,the results show that the prediction accuracy of the model is significantly improved with multi-ple regression algorithms after integrating the delay-causing feature.

A Numerical Study of the Aerodynamic Characteristics of a High-Speed Train under the Effect of Crosswind and Rain

The performances of high-speed trains in the presence of coupling effects with crosswind and rain have attracted great attention in recent years.The objective of the present paper was to investigate the aerodynamic characteristics of a high-speed train under such conditions in the framework of an Eulerian-Lagrangian approach.An aerodynamic model of a high-speed train was first set up,and the side force coefficient obtained from numerical simulation was compared with that provided by wind tunnel experiments to verify the accuracy of the approach.Then,the effects of the yaw angle,the resultant wind speed,and the rainfall rate on aerodynamic coefficients were analyzed.The results indicate that the aerodynamic coefficients grow almost linearly with the rainfall rate,and increase with a decrease in the resultant wind speed.Due to the impact of raindrops on the train surface and the airflow,the pressure coefficients of windward and leeward side of the train become larger with the increase of the rainfall rate.Raindrops can accelerate the airflow and suppress the vortices detachment.Moreover,the flow velocity in regions surrounding the train increases with an increase in the rainfall rate.

Studyon Evaluation Methods for Lateral Stability of High-Speed Trains

Taking a high-speed train in China as an example,using computer simulation technology and comparing with the test data,the three current methods including linear stability analysis method,nonlinear stability analysis method and the field testing criterion are studied to evaluate stability of high-speed trains.A new stability evaluation method is proposed which can be used to evaluate lateral stability of high-speed vehicle based on the codes of UIC 515and UIC 518.From the viewpoint of taking the most unfavorable track conditions into account and improving the safety margin,the new method uses the root mean square of bogie lateral acceleration as a criterion to evaluate the lateral stability of high-speed trains.Numerical example shows that the proposed method not only considers the forced vibration caused by track irregularities in the actual practice,but also takes the instability self-excited vibration into account,so it can realize early warning of bogie slight unstable oscillation,meanwhile the method itself does not involve complex algorithms which has the possibility of engineering applications.

An Investigation into the Effects of the Reynolds Number on High-Speed Trains Using a Low Temperature Wind Tunnel Test Facility

A series of tests have been conducted using a Cryogenic Wind Tunnel to study the effect of Reynolds number(Re)on the aerodynamic force and surface pressure experienced by a high speed train.The test Reynolds number has been varied from 1 million to 10 million,which is the highest Reynolds number a wind tunnel has ever achieved for a train test.According to our results,the drag coefficient of the leading car decreases with higher Reynolds number for yaw angles up to 30º.The drag force coefficient drops about 0.06 when Re is raised from 1 million to 10 million.The side force is caused by the high pressure at the windward side and the low pressure generated by the vortex at the lee side.Both pressure distributions are not appreciably affected by Reynolds number changes at yaw angles up to 30°.The lift force coefficient increases with higher Re,though the change is small.At a yaw angle of zero the down force coefficient is reduced by a scale factor of about 0.03 when the Reynolds number is raised over the considered range.At higher yaw angles the lift force coefficient is reduced about 0.1.Similar to the side force coefficient,the rolling moment coefficient does not change much with Re.The magnitude of the pitching moment coefficient increases with higher Re.This indicates that the load on the front bogie is higher at higher Reynolds numbers.The yawing moment coefficient increases with Re.This effect is more evident at higher yaw angles.The yawing moment coefficient increases by about 6%when Re is raised from 1 million to 10 million.The influence of Re on the rolling moment coefficient around the leeward rail is relatively smaller.It increases by about 2%over the considered range of Re.

Analysis of the Temperature Characteristics of High-speed Train Bearings Based on a Dynamics Model and Thermal Network Method

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.

Establishment of Dynamic Model for Axle Box Bearing of High-Speed Trains Under Variable Speed Conditions

In this study,a dynamic model for the bearing rotor system of a high-speed train under variable speed conditions is established.In contrast to previous studies,the contact stress is simplifed in the proposed model and the compensation balance excitation caused by the rotor mass eccentricity considered.The angle iteration method is used to overcome the challenge posed by the inability to determine the roller space position during bearing rotation.The simulation results show that the model accurately describes the dynamics of bearings under varying speed profles that contain acceleration,deceleration,and speed oscillation stages.The order ratio spectrum of the bearing vibration signal indicates that both the single and multiple frequencies in the simulation results are consistent with the theoretical results.Experiments on bearings with outer and inner ring faults under various operating conditions are performed to verify the developed model.

Numerical Investigation of the Deposition Characteristics of Snow on the Bogie of a High-Speed Train

To investigate the deposition distribution of snow particles in the bogie surfaces of a high-speed train,a snow particle deposition model,based on the critical capture velocity and the critical shear velocity,was elaborated.Simulations based on the unsteady Reynolds-Averaged Navier-Stokes(RANS)approach coupled with Discrete Phase Model(DPM)were used to analyze the motion of snow particles.The results show that the cross beam of the bogie frame,the anti-snake damper,the intermediate brake clamps in the rear wheels,the traction rod and the anti-rolling torsion bar are prone to accumulate snow.The accumulation mass relating to the vertical surface in the rear region,horizontal surface in the front region and the corner area of the bogie is high.The average snow accumulation mass for each component ordered from high to low is as follow:traction rod,frame,bolster,brake clamp 2,anti-rolling torsion bar,brake clamp 1,transverse damper,axle box 2,axle box 1,air spring,anti-snake damper,tread cleaning device.The snow accumulation mass on the front components of the bogie is more significant than that relating to the rear components.Particularly,the average snow accumulation mass of rear brake clamp 2 and axle box 2 is about twice as high as that of the front brake clamp 1 and axle box 1.

Fatigue Characterization on a Cast Aluminum Beam of a High-Speed Train Through Numerical Simulation and Experiments

The cast aluminum beam is a key structure for carrying the body-hung traction motor of a high-speed train;its fatigue property is fundamental for predicting the residual life and service mileage of the structure.To characterize the structural fatigue property,a finite element-based method is developed to compute the stress concentration factor,which is used to obtain the structural fatigue strength reduction factors.A full-scale fatigue test on the cast aluminum beam is designed and implemented for up to ten million cycles,and the corresponding finite element model of the beam is validated using the measured data of the gauges.The results show that the maximum stress concentration occurs at the fillet of the supporting seat,where the structural fatigue strength reduction factor is 2.45 and the calculated fatigue limit is 35.4 MPa.Moreover,no surface cracks are detected using the liquid penetrant test.Both the experimental and simulation results indicate that the cast aluminum beam can satisfy the service life requirements under the designed loading conditions.