High-speed Train Operation Research Articles

Study on Comprehensive Optimization of Electric Multiple Unit Trains Passing Station Route and Rolling Stock Scheduling

In order to overcome the contradiction between the rolling stock scheduling problem of EMU at a macro level and the problem of EMU train passing station route at a micro level in some special cases, this paper comprehensively optimizes the electric multiple unit train passing station route and rolling stock scheduling. By taking the operation of the Chinese high-speed railway EMU trains as the actual background and using the actual situation that the first-level inspection and repair cycle time is twice the cycle of a high-speed railway train timetable, based on the establishment of a 48-hour continuous network, a 0-1 type integer linear programming model is constructed. While obtaining the rolling stock scheduling of EMU trains, the EMU train passing station route scheme is obtained. The experimental results show that, compared with solving the problem in two stages, the comprehensive optimization according to the method in this paper can better ensure the feasibility of the passing station route scheme and provide decision support for the actual operation.

Investigation of ice and snow accumulations on the bogie areas of high-speed trains using ice wind tunnel experiments

Accumulated snow and ice will severely influence the safe operation of high-speed trains in snowy weather, where the snow and ice in the bogie region are the main concerned problems that contribute to such issues. The work presented in this paper initiated experimental studied snow and ice accumulation on the running bogies of the high-speed trains to clarify the snow and ice accumulation process and causes. Two original and two optimized cases with protective schemes combined with electoral heating and an air-flow deflector under the customized train body were adopted to carry out the snow and ice wind tunnel experiments in the Icing-snowing Wind Tunnel (ISWT) of Central South University (CSU). The distributions and mass of the snow and ice were analysed, and the preliminary conclusions were drawn: the leeward side and the depressions of the bogies accumulated a layer of snow, and the melt water sprayed by the rotating brake discs flew everywhere, which contributed to rapidly growing icicles on the bogies and train body during the experiments. Deflectors, protective sleeves and different kinds of heating methods were adopted according to the original cases to optimized where they should be placed, they were capable of reducing the snow and ice mass by 62.9% and 50.4% from the original trailer and motor bogie, respectively. Thus, the optimized schemes were confirmed to be effective to show great application potential to reduce mass and increase running safety for high-speed trains in winter in cold regions.

A hybrid damping control strategy for high-speed trains running on existing tracks

With the rapid development of railways in China, effective coordination of the operation of high-speed trains on existing tracks can bring significant economic benefits to railway transportation. However, high-speed trains running on existing tracks will have to cope with larger track irregularities and navigate smaller curve radii, potentially increasing their vibrations. In order to improve the quality of operation of high-speed trains on existing railways, a self-adjusting hybrid damping control (SAHDC) strategy utilizing a fuzzy controller is adopted in this study. A secondary lateral magnetorheological damper (MRD) is controlled to balance the vibration between the car body, bogie, and wheelset. The MRD behavior is described using a viscoelastic-plastic (VEP) model and nonlinear autoregressive exogenous (NARX) inverse model. A dynamical vehicle model with 50 DOFs is constructed and simulated under different existing track conditions. The results show that the SAHDC can guarantee the required ride quality of the car body, while reducing the vibration of the bogie frame and wheelsets as much as possible during travel on straight and curved tracks and suppressing derailment on turnouts.

Analysis and prediction of double-carriage train wheel wear based on SIMPACK and neural networks

Wheel and rail wear seriously affects the safety and reliability of train operations. In this study single-carriage and double-carriage models considering the connecting unit of a high-speed train are developed to investigate the normal forces, lateral forces, and lateral displacements of wheelsets. Based on the results from these models, the Archard wear model is employed to predict the wheel wear. In addition, based on the daily measured data, a nonlinear autoregulatory (NAR) model and a wavelet neural network (WNN) model are developed to predict the wheel wear over a longer time period. The simulation results show that, compared with the single-carriage model, the normal forces, lateral forces, and lateral displacements of the wheelsets close to the connecting unit in the double-carriage model increase to a certain extent dependent on the speed. The wheel wear predictions show that the wheel wear on the wheelsets near the connecting unit is slightly larger than on the wheelsets far from the connecting unit. Based on the mean square error, the NAR model has somewhat better performance in the wheel wear prediction than the WNN model. The research results represent an important contribution to the maintenance and safe operation of high-speed trains.

High-Accuracy and Adaptive Fault Diagnosis of High-Speed Train Bogie Using Dense-Squeeze Network

As one of the most important systems of high-speed train (HST), bogie system matters when it comes to the safety and reliability of HST operation. In order to strengthen feature propagation and alleviate vanishing gradients problems in training deep-learning networks, a novel Dense-Squeeze Network based on one-dimensional convolutional neural networks (1D-CNN) is proposed for bogie fault diagnosis. On the one hand, dense blocks are capable of facilitating feature reuse and increasing the depth of feature propagation. On the other hand, the squeeze operation automatically measures the importance level of each feature channel, and then enhance the useful features and suppress the useless features for the current task. The experimental results tested by the HST model CRH380 A at different speeds verify the effectiveness of the proposed method, and the accuracy of fault diagnosis converges to 99.66%. Compared with other deep-learning-based methods, such as 1D-CNN, Long Short-Term Memory (LSTM) and DenseNet, the superiority of the proposed scheme is demonstrated clearly.

Aerodynamic simulation of effects of one- and two-side windbreak walls on a moving train running on a double track railway line subjected to strong crosswind

High-speed railway lines are widely distributed worldwide. The surrounding wind environment of such railway lines is complex, which significantly affects the safety of high-speed train operations. Using a combination of the computational fluid dynamics method of improved delayed detached eddy simulation and sliding grid technology, the effects of one- and two-side windbreak walls on the unsteady aerodynamic performance of a high-speed train running under a crosswind on a double-track railway line with an embankment and the flow-field characteristics around the train were systematically studied. The grid independence and numerical methods used in this study were verified. The results showed that when the windbreak wall was absent, the aerodynamic performance of the train running on the upstream railway line was the poorest, while the train running on the downstream railway line exhibited large aerodynamic fluctuations. The windbreak wall significantly reduced the aerodynamic force and its fluctuation; the one- and two-side windbreak walls had different effects on the unsteady aerodynamic performance of trains running on the upstream and downstream railway lines under a crosswind. The one-side windbreak wall could restrain the aerodynamic fluctuation of the train more and is thus preferred from the perspective of construction effort and cost.

Railway Track Recognition Based on Radar Cross-Section Statistical Characterization Using mmWave Radar

The track settlement has a great influence on the safe operation of high-speed trains. The existing track settlement measurement approach requires sophisticated or expensive equipments, and the real-time performance is limited. To address the issue, an ultra-high resolution track settlement detection method is proposed by using millimeter wave radar based on frequency modulated continuous wave (FMCW). Firstly, by constructing the RCS statistical feature data set of multiple objects in the track settlement measurement environment, a directed acyclic graph-support vector machine (DAG-SVM) based method is designed to solve the problem of track recognition in multi-object scenes. Then, the adaptive chirp-z-transform (ACZT) algorithm is used to estimate the distance between the radar and the track surface, which realizes automatic real-time track settlement detection. An experimental platform has been constructed to verify the effectiveness of the proposed method. The experimental results show that the accuracy of track classification and identification is at least 95%, and the accuracy of track settlement measurement exceeds 0.5 mm, which completely meets the accuracy requirements of the railway system.

Simulation Method of High-Speed Railway Train Operation Based on Cellular Automata

Simulation Method of High-Speed Railway Train Operation Based on Cellular Automata

Fault Injection Strategies for Air Brake System of High-speed Train with AMESim/Simulink Co-simulation

Electro-pneumatic braking is the main braking mode of high-speed trains. The study on the fault of the air brake system is the key to diagnosing the occurrence of faults and realizing the safe operation of high-speed trains. Because the existing trains runing normally for a long time, it is difficult to obtain the fault data. Besides, the severity of simulating the real fault is hard to control and the cost is high. Therefore, this paper first analyzes the working principle and builds the simulation model of the air brake system of a high-speed train based on AMESim and Simulink. Then, according to the typical fault mechanism of the air brake system, the typical fault models are established and the injection and simulation of several typical faults are realized by using the fault injection method of model switching and signal conditioning. The simulation results are compared with the fault curves in literature, and the accuracy of the simulation results is verified. This paper provides data and verification support for the fault diagnosis study of the air brake system of high-speed trains. The normal and fault data of the air brake system can be downloaded at https://github.com/CSU-IILab/BS-FIB.git

Simulation on adjacent line mutual interference of high-speed railway track circuit

As the density of the high-speed railway network continues to increase, the problem of electromagnetic interference on adjacent lines has become increasingly prominent. This paper focuses on the electromagnetic interference of adjacent lines caused by rail and line in the signal transmission process of the high-speed rail track circuit. Firstly, complete the establishment of the four-terminal network model of the ZPW-2000A track circuit system and the cab signal entry current crosstalk model, calculation of interference voltage under different parallel length of signal frequency. Then the interference factors and coupling mechanism of adjacent lines are analysed to realize calculation of interference amount. Finally, according to the sensitivity index of the cab signal, the maximum parallel length of adjacent sections is given respect, and the interference protection suggestions of adjacent lines are put forward. The research work of this paper provides a theoretical basis for suppressing the interference of adjacent lines and guarantees the safe and efficient operation of high-speed trains.

Оцінка залишкового ресурсу контактного проводу електрофікованих залізничних доріг

Since the current state of the contact network of electrified railways in Ukraine does not meet the requirements for ensuring the reliable operation of high-speed trains, the article proposes to improve the quality of service (control and repair) of the contact network in order to timely identify problem areas, thus contributing to the prevention of accidents on the railway. The arti-cle is devoted to solving the problem of determining the residual life of the contact wire (CW) of electrified railways. The article analyzes the types of CW wear and defines the main defining parameters. It is proposed to use the residual height of the section and the area of the worn part of the CW section as the determining main parameters of the wear. The permissible degree of CW wear has also been established. On the basis of the experimental data, the residual life of the CW was determined. In the paper, there are proposed and developed criteria for assessing the residual life of the CW that allow reducing operating costs by increasing the overhaul inter-val. It is offered to use a probabilistic-physical approach to assess the real technical condition and predict the residual life of products when there are no failure statistics. Within the frame-work of the probabilistic-physical approach, a probabilistic model (DM-distribution of failures) is involved in the assessment of durability, the parameters of which have a physical interpreta-tion – the average rate of change of the determining parameter (validity criterion) and the coef-ficient of variation of the generalized degradation process. In addition, the article provides sev-eral examples of residual life calculations that demonstrate the use of two probabilistic-physical methods for estimating the residual life of the CW, namely, the ones based on the results of controlled operation and the statistics of failures and recovery of the CW. The obtained calcu-lated data correspond to the current recommendations for the average frequency of the current repair of the CW sections.

Auxiliary Stopping Area Layout Method for High-Speed Maglev considering Multiple Speed Profiles and Bidirectional Operation

Auxiliary stopping area (ASA) is the key guarantee for high-speed maglev train operation safety. Aiming at the layout of the ASA along the track, this article constructs an optimized model of ASA layout and proposes a solving algorithm based on the single target genetic algorithm by analyzing the influence factors of ASA layout. The result of the numerical experiment shows that the proposed method could fulfill the requirements of the maglev train operation safety and efficiency and optimize the cost of the ASA layout while taking the complex line situation, train tracking operation, and bidirectional operation on a single line into account.

Research on probability statistics of train running safety indices based on pseudo-excitation method

In order to explore the random nature of high-speed railway train operation safety indices, the pseudo-excitation method, extreme value theory, and non-stationary harmonic superposition theory are used in this paper to study the statistics of train operation safety indices. The pseudo-excitation load formulation for track irregularity is obtained by the pseudo-excitation method, and the resulting non-stationary random vibration problem is transformed into a deterministic time history problem. The pseudo-excitation method is used to establish the dynamic equations of motion, and the separation iteration method is used to solve the equations, so as to obtain the power spectral density of the wheel-rail interaction forces. The wheel-rail interaction forces are obtained by using a modulation function and the harmonic superposition method. By fitting an extreme value distribution, the maximum values of the train running safety indices are explored. The proposed numerical approach is validated experimentally using the data from a 24.6 m long simply supported concrete bridge by studying the extreme value distributions of driving safety indices. Additional numerical simulation are conducted for varying train speeds and bridge spans. The results show that the Gumbel distribution can fit the extreme value of driving safety parameters for different speeds and different bridge span lengths. It is observed that the higher the speed, the sharper the extreme value distribution of train running safety indices, and the larger the train running safety index values corresponding to 99.87% confidence level. The corresponding extreme values at the 99.87% confidence level are greater than the maximum value of each time-domain sample.

ENSURING TRAIN SAFETY ON HIGH-SPEED RAIL-HIGHWAY

Modern high-speed trains in normal operation develop speeds of up to 350-400 km / h, and in tests they can even accelerate to 560-580 km/h. Due to the speed of service and high speed of movement, they seriously compete with other modes of transport, while maintaining such a property of all trains as low cost of transportation with a large volume of passenger traffic. For the first time the regular movement of high-speed trains began in 1964 in Japan under the Shinkansen project. In 1981, VSNT trains began to run in France, and soon most of Western Europe, including even the island of Great Britain, became connected by a single high-speed rail network. At the beginning of the XXI century, China became the world leader in the development of a network of high-speed lines, as well as the operator of the first regular high-speed maglev.In Russia, the regular operation of high-speed trains "Sapsan", on common tracks with conventional trains, began at the end of 2009. Since 2013, the idea of building the first specialized high-speed railway Moscow-Kazan (cargo-passenger) for the national high-speed traffic system has been discussed.Most of the high-speed trains carry passengers, but there are varieties designed for the transport of goods. For example, the French service La Poste has used special TGV electric trains for 30 years, which served to transport mail and parcels (their operation was completed in June 2015 due to the decrease in the volume of mailings in recent years).

A wind hazard warning system for safe and efficient operation of high-speed trains

Operation safety and efficiency of high-speed trains are prone to strong winds. This study proposes a wind hazard warning system to predict wind speed and provide warning for safe and efficient operation of trains, and shows the implementation to the Lanzhou-Xinjiang High-Speed Railway. The system is composed of monitoring, remote and central processing, and execution modules. The system uses field monitoring data to predict wind speed and analyze responses of trains. Wind speed is predicted through integrating three models based on artificial neural networks and the predictions are incorporated into operation control for high speed trains under wind load. The results show that the proposed predictive model is capable of predicting wind speed, and the system is capable of providing reasonable warning for high-speed trains. It is anticipated that the system will improve the operation and management of high-speed trains for high safety and efficiency.

Notch-based speed trajectory optimisation for high-speed railway automatic train operation

Automatic train operation (ATO) systems are fast becoming one of the key components of the intelligent high-speed railway (HSR). Designing an effective optimal speed trajectory for ATO is critical to guide the high-speed train (HST) to operate with high service quality in a more energy-efficient way. In many advanced HSR systems, the traction/braking systems would provide multiple notches to satisfy the traction/braking demands. This paper modelled the applied force as a controlled variable based on the selection of notch to realise a notch-based train speed trajectory optimisation model to be solved by mixed integer linear programming (MILP). A notch selection model with flexible vertical relaxation was proposed to allow the traction/braking efforts to change dynamically along with the selected notch by introducing a series of binary variables. Two case studies were proposed in this paper where Case study 1 was conducted to investigate the impact of the dynamic notch selection on train operations, and the optimal result indicates that the applied force can be flexibly adjusted corresponding to different notches following a similar operation sequence determined by optimal train control theory. Moreover, in addition to the maximum traction/braking notches and coasting, medium notches with appropriate vertical relaxation would be applied in accordance with the specific traction/braking demands to make the model feasible. In Case study 2, a comprehensive numerical example with the parameters of CRH380AL HST demonstrates the robustness of the model to deal with the varying speed limit and gradient in a real-world scenario. The notch-based model is able to obtain a more realistic optimal strategy containing dynamic notch selection and speed trajectory with an increase (1.622%) in energy consumption by comparing the results of the proposed model and the non-notch model.

Comparative study on the use of acoustic emission and vibration analyses for the bearing fault diagnosis of high-speed trains

A wheel set bearing is an important supporting component of a high-speed train. Its quality and performance directly determine the overall safety of the train. Therefore, monitoring a wheel set bearing’s conditions for an early fault diagnosis is vital to ensure the safe operation of high-speed trains. However, the collected signals are often contaminated by environmental noise, transmission path, and signal attenuation because of the complexity of high-speed train systems and poor operation conditions, making it difficult to extract the early fault features of the wheel set bearing accurately. Vibration monitoring is most widely used for bearing fault diagnosis, with the acoustic emission (AE) technology emerging as a powerful tool. This article reports a comparison between vibration and AE technology in terms of their applicability for diagnosing naturally degraded wheel set bearings. In addition, a novel fault diagnosis method based on the optimized maximum second-order cyclostationarity blind deconvolution (CYCBD) and chirp Z-transform (CZT) is proposed to diagnose early composite fault defects in a wheel set bearing. The optimization CYCBD is adopted to enhance the fault-induced impact response and eliminate the interference of environmental noise, transmission path, and signal attenuation. CZT is used to improve the frequency resolution and match the fault features accurately under a limited data length condition. Moreover, the efficiency of the proposed method is verified by the simulated bearing signal and the real datasets. The results show that the proposed method is effective in the detection of wheel set bearing faults compared with the minimum entropy deconvolution (MED) and maximum correlated kurtosis deconvolution (MCKD) methods. This research is also the first to compare the effectiveness of applying AE and vibration technologies to diagnose a naturally degraded high-speed train bearing, particularly close to actual line operation conditions.

Dynamic Response of High-Speed Train-Track-Bridge Coupling System Subjected to Simultaneous Wind and Rain

The Lanzhou-Xinjiang High-speed Railway runs through a region of over 500[Formula: see text]km that is amenable to frequent winds. The strong wind and rainfall pose a great threat to the safe operation of high-speed trains. To tackle the aforementioned climate challenges, this paper investigates the dynamic response of the high-speed train-track-bridge coupling system under the simultaneous action of winds and rains for the safe operation of trains. Specifically, there are four main objectives: (1) to develop a finite element model to analyze the dynamic response of the train-track-bridge system in windy and raining conditions; (2) to investigate the aerodynamic loads posed to the train-track-bridge system by winds and rains; (3) to evaluate the effects of wind speed and rainfall intensity on the train-track-bridge system; and (4) to assess the safety of trains at different train speeds and under various wind-rain conditions. To this end, this paper first establishes a train-track-bridge model via ANSYS and SIMPACK co-simulation and the aerodynamics models of the high-speed train and bridge through FLUENT to form a safety analysis system for high-speed trains running on the bridge under the wind-rain conditions. Then, the response of the train-track-bridge system under different wind speeds and rainfall intensities is studied. The results show that the effects of winds and rains are coupled. The rule of variation for the train dynamic response with respect to various wind and rain conditions is established, with practical suggestions provided for control of the safe operation of high-speed trains.

Research on High-Speed Railway Freight Train Organization Method considering Different Transportation Product Demands

The sustained and stable growth of China’s market economy promotes the continuous improvement of transportation demand and puts forward higher requirements for transportation products. At present, as a new product, high-speed rail freight has played an important role in cold chain logistics and high-value-added transportation, which is of great significance to effectively reduce the pollution caused by road transportation and further promote the sustainable development of economy and logistics industry. In the previous study, we studied the organization optimization method of high-speed rail freight train operation scheme and the compilation method of high-speed rail freight train diagram based on the overall demand of freight transportation but did not consider the influence of different high-speed rail freight transportation products on the organization scheme. Therefore, in order to ensure the sustainable development of high-speed rail freight business, based on the demand of high-speed freight products (the freight product for short in the following text), this paper focuses on the optimization method of high-speed rail freight train organization scheme considering different demands. A two-stage freight demand analysis method considering customers’ choice intention and actual supply capacity was designed, comprehensively considering the relationship between operation cost and income, and a model based on different products in order to meet the needs of large-scale case solving was established. In addition, a column generation algorithm was designed. The computational results are encouraging and demonstrate the effectiveness of the model and solution method.

Pixel frequency based railroad surface flaw detection using active infrared thermography for Structural Health Monitoring

With rapid increase in operation and development of high-speed trains, inspection of railroad surface flaws has become an important aspect for safe and reliable operation of rail network. Non-destructive testing using active infrared thermography has been useful in determining the structural health of different structures with additional benefit of robustness in overall inspection system. This study is based on detection of artificial surface flaws on an in-service railroad. Transverse and longitudinal flaws of various dimensions were machined on rough and smooth rail surface. The railroad surface was thermally stimulated to a temperature equivalent to practical conditions. Emitted radiations from rail surface were captured by an infrared camera to detect cracks. Results show a comparison between the surface flaws on rough and smooth rail surface. Subsequently, raw infrared images were post-processed by statistical image improvement to quantitatively analyse the results. Significant change in the frequency distribution of pixel intensity is observed as the flaw size and depth changes giving a clear quantification of crack topology. A comprehensive and inexpensive solution for damage diagnosis will be offered to railway authorities for Structural Health Monitoring (SHM) and NDT by the proposed framework.