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.

How to Deal with Revolutions in Train Control Systems

Train control systems ensure the safety of railways. This paper begins with a summary of the typical train control systems in Japan and Europe. Based on this summary, the author then raises the following question regarding current train control systems： What approach should be adopted in order to enhance the functionality, safety, and reliability of train control systems and assist in commercial operations on railways？ Next, the author provides a desirable architecture that is likely to assist with the development of new train control systems based on current information and communication technologies. A new unified train control system （UTCS） is proposed that is effective in enhancing the robustness and com- petitiveness of a train control system. The ultimate architecture of the UTCS will be only composed of essential elements such as point machines and level crossing control devices in the field. Finally, a pro- cessing method of the UTCS is discussed.

Increasing realism in modelling energy losses in railway vehicles and their impact to energy-efficient train control

The reduction of energy consumption is an increasingly important topic of the railway system.Energy-efficient train control(EETC)is one solution,which refers to mathematically computing when to accelerate,which cruising speed to hold,how long one should coast over a suitable space,and when to brake.Most approaches in literature and industry greatly simplify a lot of nonlinear effects,such that they ignore mostly the losses due to energy conversion in traction components and auxiliaries.To fill this research gap,a series of increasingly detailed nonlinear losses is described and modelled.We categorize an increasing detail in this representation as four levels.We study the impact of those levels of detail on the energy optimal speed trajectory.To do this,a standard approach based on dynamic programming is used,given constraints on total travel time.This evaluation of multiple test cases highlights the influence of the dynamic losses and the power consumption of auxiliary components on railway trajectories,also compared to multiple benchmarks.The results show how the losses can make up 50%of the total energy consumption for an exemplary trip.Ignoring them would though result in consistent but limited errors in the optimal trajectory.Overall,more complex trajectories can result in less energy consumption when including the complexity of nonlinear losses than when a simpler model is considered.Those effects are stronger when the trajectory includes many acceleration and braking phases.

Analyzing the Combination Effects of Repetitive Transcranial Magnetic Stimulation and Motor Control Training on Balance Function and Gait in Patients with Stroke-Induced Hemiplegia

Objective:To analyze the effects of repetitive transcranial magnetic stimulation combined with motor control training on the treatment of stroke-induced hemiplegia,specifically focusing on the impact on patients’balance function and gait.Methods:Fifty-two cases of hemiplegic stroke patients were randomly divided into two groups,26 in the control group and 26 in the observation group,using computer-generated random grouping.All participants underwent conventional treatment and rehabilitation training.In addition to these,the control group received repetitive transcranial magnetic pseudo-stimulation therapy+motor control training,while the observation group received repetitive transcranial magnetic stimulation therapy+motor control training.The balance function and gait parameters of both groups were compared before and after the interventions and assessed the satisfaction of the interventions in both groups.Results:Before the invention,there were no significant differences in balance function scores and each gait parameter between the two groups(P>0.05).However,after the intervention,the observation group showed higher balance function scores compared to the control group(P<0.05).The observation group also exhibited higher step speed and step frequency,longer step length,and a higher overall satisfaction level with the intervention compared to the control group(P<0.05).Conclusion:The combination of repetitive transcranial magnetic stimulation and motor control training in the treatment of stroke-induced hemiplegia has demonstrated positive effects.It not only improves the patient’s balance function and gait but also contributes to overall physical rehabilitation.

Formal verification of safety protocol in train control system

In order to satisfy the safety-critical requirements,the train control system(TCS) often employs a layered safety communication protocol to provide reliable services.However,both description and verification of the safety protocols may be formidable due to the system complexity.In this paper,interface automata(IA) are used to describe the safety service interface behaviors of safety communication protocol.A formal verification method is proposed to describe the safety communication protocols using IA and translate IA model into PROMELA model so that the protocols can be verified by the model checker SPIN.A case study of using this method to describe and verify a safety communication protocol is included.The verification results illustrate that the proposed method is effective to describe the safety protocols and verify deadlocks,livelocks and several mandatory consistency properties.A prototype of safety protocols is also developed based on the presented formally verifying method.

Real Time Control System for Metro Railways Using PLC & SCADA

This paper proposes to adopt SCADA and PLC technology for the improvement of the performance of real time signaling&train control systems in metro railways.The main concern of this paper is to minimize the failure in automated metro railways system operator and integrate the information coming from Operational Control Centre(OCC),traction SCADA system,traction power control,and power supply system.This work presents a simulated prototype of an automated metro train system operator that uses PLC and SCADA for the real time monitoring and control of the metro railway systems.Here,SCADA is used for the visualization of an automated process operation and then the whole opera-tion is regulated with the help of PLC.The PLC used in this process is OMRON(NX1P2-9024DT1)and OMRON’s Sysmac studio programming software is used for developing the ladder logic of PLC.The metro railways system has deployed infrastructure based on SCADA from the power supply system,and each station’s traction power control is connected to the OCC remotely which commands all of the stations and has the highest command priority.An alarm is triggered in the event of an emergency or system congestion.This proposed system overcomes the drawbacks of the current centralized automatic train control(CATC)system.This system provides prominent benefits like augmenting services which may enhance a network’s full load capacity and networkflexibility,which help in easy modification in the existing program at any time.

Modeling and simulation for train control system using cellular automata

Train control system plays a key role in railway traffic. Its function is to manage and control the train movement on railway networks. In our previous works, based on the cellular automata (CA) model, we proposed several models and algorithms for simulating the train movement under different control system conditions. However, these models are only suitable for some simple traffic conditions. Some basic fac- tors, which are important for train movement, are not considered. In this paper, we extend these models and algorithms and give a unified formula. Using the pro- posed method, we analyze and discuss the space-time diagram of railway traffic flow and the trajectories of the train movement. The numerical simulation and analytical results demonstrate that the unified CA model is an effective tool for simulating the train control system.

Optimal control strategy for energy saving in trains under the four-aspect fixed autoblock system

This paper deals with both the leading train and the following train in a train tracking under a four-aspect fixed autoblock system in order to study the optimum operating strategy for energy saving. After analyzing the working principle of the four-aspect fixed autoblock system, an energy-saving control model is created based on the dynamics equation of the Wains. In addition to safety, energy consumption and time error are the main concerns of the model. Based on this model, dynamic speed constraints of the following train are proposed, defined by the leading gain dynamically. At the same time, the static speed constraints defined by the line conditions are also taken into account. The parallel genetic algorithm is used to search the optimum operating strategy. In order to simplify the solving process, the external punishment function is adopted to transform this problem with constraints to the one without constraints. By using the real number coding and the strategy of dividing ramps into three parts, the convergence of GA is accelerated and the length of chromosomes is shortened. The simulation result from a four-aspect fixed autoblock system simulation platform shows that the method can reduce the energy consumption effectively in the premise of ensuring safety and punctuality.

Dependability analysis of the data communication system in train control system

Communication based train control (CBTC) system is based on mobile communication and overcomes fixed blocks in order to increase track utilization and train safety. The data communication system (DCS) between trains and wayside equipment is a crucial factor for the safe and efficient operation of CBTC system. The dependability under various transmission conditions needs to be modeled and evaluated. In this paper,a stochastic reward net (SRN) model for DCS based IEEE 802.11 standard was developed,which captures all relevant failure and failure recovery behavior system aspects in a concise way. We compared the reliability,availability for DCS with and without access point (AP) and antenna redundant configuration. We also quantitatively evaluated and compared the frame loss probability for three DCS configurations with different train velocities and train numbers in one radio cell. Fixed-point iteration was adopted to simplify the analysis. Numerical results showed the significant improvement of the reliability,availability and the frame loss probability index for the full redundant configuration.

Effect of Combined Low-frequency Repetitive Transcranial Magnetic Stimulation and Virtual Reality Training on Upper Limb Function in Subacute Stroke:a Double-blind Randomized Controlled Trail

The effect of combined low-frequency repetitive transcranial magnetic stimulation（LF r TMS） and virtual reality（VR） training in patients after stroke was assessed. In a double-blind randomized controlled trial, 112 patients with hemiplegia after stroke were randomly divided into two groups： experimental and control. In experimental group, the patients received LF r TMS and VR training treatment, and those in control group received sham r TMS and VR training treatment. Participants in both groups received therapy of 6 days per week for 4 weeks. The primary endpoint including the upper limb motor function test of Fugl-meyer assessment（U-FMA） and wolf motor function test（WMFT）, and the secondary endpoint including modified Barthel index（MBI） and 36-item Short Form Health Survey Questionnaire（SF-36） were assessed before and 4 weeks after treatment. Totally, 108 subjects completed the study（55 in experimental group and 53 in control group respectively）. After 4-week treatment, the U-FMA scores [mean difference of 13.2, 95% confidence interval（CI） 3.6 to 22.7, P〈0.01], WMFT scores（mean difference of 2.9, 95% CI 2.7 to 12.3, P〈0.01）, and MBI scores（mean difference 16.1, 95% CI 3.8 to 9.4, P〈0.05） were significantly increased in the experimental group as compared with the control group. The results suggested the combined use of LF r TMS with VR training could effectively improve the upper limb function, the living activity, and the quality of life in patients with hemiplegia following subacute stroke, which may provide a better rehabilitation treatment for subacute stroke.

Modelling and Simulation for Train Movement Control Using Car-Following Strategy

Based on optimM velocity car-following model, in this paper, we propose a new railway tramc model for describing the process of train movement control. In the proposed model, we give an improved form of the optimal velocity function V^opt, which is considered as the desired velocity function for train movement control under different control conditions. In order to test the proposed model, we simulate and analyze the trajectories of train movements, moreover, discuss the relationship curves between the train allowable velocity and the site of objective point in detail. Analysis results indicate that the proposed model can well capture some realistic futures of train movement control.

Hybrid force control of astronaut rehabilitative training robot under active loading mode

In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts to carry out the bench press training in the microgravity environment. Firstly, a dynamic model of cable driven unit(CDU) was established whose accuracy was verified through the model identification. Secondly, to improve the accuracy and the speed of the active loading, an active loading hybrid force controller was proposed on the basis of the dynamic model of the CDU. Finally, the actual effect of the hybrid force controller was tested by simulations and experiments. The results suggest that the hybrid force controller can significantly improve the precision and the dynamic performance of the active loading with the maximum phase lag of the active loading being 9° and the maximum amplitude error being 2% at the frequency range of 10 Hz. The controller can meet the design requirements.

Antiskid Control of Railway Train Braking Based on Adhesion Creep Behavior

In modern trains wheelset skidding leads to the deterioration of braking behavior,the degradation of comfort,as well as a boost in system hazards.Because of the nonlinearity and unknown characteristics of wheelset adhesion,simplifications are widely adopted in the modeling process of conventional antiskid controllers.Therefore,conventional antiskid controllers usually cannot perform satisfactorily.In this paper,systematic computer simulation and field tests for railway antiskid control system are introduced.The operating principal of antiskid control system is explained,which is fundamental to the simulation of antiskid brakes,and the simulation model is introduced,which incorporates both the adhesion creep curve and a pneumatic submodel of antiskid control system.In addition,the characteristics of adhesion curves and the simulation target are also provided.Using DHSplus,the pneumatic submodel is created to analyze the performance of the different control strategies of antiskid valves.Then the system simulation is realized by combining the kinematical characteristics of railway trains and the pneumatic submodel.The simulation is performed iteratively to obtain the optimized design of the antiskid control system.The design result is incorporated in the hardware design of the antiskid control system and is evaluated in the field tests in Shanghai Subway Line 1.Judging by the antiskid efficiency,the antiskid braking performance observed in the field tests shows the superiority of the optimized design.Therefore,the proposed simulation method,especially in view of its ease of application,appears to be a useful one for designing railway antiskid control systems.

Control and Management in Athletic Training of the Russian National Teams

The article presents wide experience in controlling athletic training aimed at preparation of the Russian national teams for major international competitions. Experimental part of the study has been carried out in the course of training camps and competitions since 2010. Forty Russian national teams in 15 winter and 3 summer Olympic sports participated in the research. Theoretical concepts set forth in the works of Anthony Stafford Beer made a basis of a system of control and management developed for the Russian national winter sports teams. In particular, a five-level system was applied to control athletic training. The authors point out that a system of control over athletic training in elite sport teams should take into account a few important issues： （1） each sport, team and athlete has distinctive features; （2） various aspects of athletic training and their interrelation must be aimed at raising effectiveness of training according to individual training plans; （3） coaches and sport managers must be provided with real-time information necessary for development of long-term and short-term training plans and their timely correction.

Study on key technologies of GNSS-based train state perception for traincentric railway signaling

The application of Global Navigation Satellite Systems(GNSSs)in the intelligent railway systems is rapidly developing all over the world.With the GNSs-based train positioning and moving state perception,the autonomy and flexibility of a novel train control system can be greatly enhanced over the existing solutions relying on the track-side facilities.Considering the safety critical features of the railway signaling applications,the GNSS stand-alone mode may not be sufficient to satisfy the practical requirements.In this paper,the key technologies for applying GNSS in novel train-centric railway signaling systems are investigated,including the multi-sensor data fusion,Virtual Balise(VB)capturing and messaging,train integrity monitoring and system performance evaluation.According to the practical characteristics of the novel train control system under the moving block mode,the details of the key technologies are introduced.Field demonstration results of a novel train control system using the presented technologies under the practical railway operation conditions are presented to illustrate the achievable performance feature of autonomous train state perception using BeiDou Navigation Satellite System(BDS)and related solutions.It reveals the great potentials of these key technologies in the next generation train control system and other GNSS-based railway implementations.

基于车车通信列控系统的城市轨道交通列车运行效率分析

[目的]城市轨道交通T2T(车车通信)列控系统是一种新型的信号系统,其通过资源化管理方式对轨旁设备进行管控。为了验证该系统的优越性,需对该系统下的列车运行效率进行分析。[方法]针对T2T列控系统,基于资源管理层面和安全防护原理的特点,在折返工况下,将原本由联锁控制的双动道岔转变为两个单动道岔,并基于列车精确自定位实现ATP(列车自动防护),提高了岔区线路资源的使用能力;在区间和车站追踪工况下,通过前后车对于车速、加速度、所处线路位置等信息的实时互传,利用相对速度安全防护原理进一步缩小了列车的追踪间隔。通过上述两方面的技术革新,结合城市轨道交通线路的实际数据,对站后交叉渡线折返、站前单渡线折返、区间与车站追踪等运营场景进行了模拟仿真计算,确定了T2T列控系统的折返能力和区间追踪能力。[结果及结论]相较传统的CBTC(基于通信的列车控制系统),T2T列控系统在折返能力、追踪能力等方面均有着显著提升,更加适应于超大运量的城市轨道交通线路;T2T列控系统架构简单,轨旁设备少,尤其适合城市轨道交通的大修改造项目。

A train timetable rescheduling approach based on multi-train tracking optimization of high-speed railways

Purpose–This paper aims to propose a train timetable rescheduling(TTR)approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information in the high-speed railway signaling system.Design/methodology/approach–Firstly,a single-train trajectory optimization(STTO)model is constructed based on train dynamics and operating conditions.The train kinematics parameters,including acceleration,speed and time at each position,are calculated to predict the arrival times in the train timetable.A STTO algorithm is developed to optimize a single-train time-efficient driving strategy.Then,a TTR approach based on multi-train tracking optimization(TTR-MTTO)is proposed with mutual information.The constraints of temporary speed restriction(TSR)and end of authority are decoupled to calculate the tracking trajectory of the backward tracking train.The multi-train trajectories at each position are optimized to generate a timeefficient train timetable.Findings–The numerical experiment is performed on the Beijing-Tianjin high-speed railway line and CR400AF.The STTO algorithm predicts the train’s planned arrival time to calculate the total train delay(TTD).As for the TSR scenario,the proposed TTR-MTTO can reduce TTD by 60.60%compared with the traditional TTR approach with dispatchers’experience.Moreover,TTR-MTTO can optimize a time-efficient train timetable to help dispatchers reschedule trains more reasonably.Originality/value–With the cooperative relationship and mutual information between train rescheduling and control,the proposed TTR-MTTO approach can automatically generate a time-efficient train timetable to reduce the total train delay and the work intensity of dispatchers.

Adaptive Robust Control for a Lower Limbs Rehabilitation Robot Running Under Passive Training Mode

This paper focuses on the problem of the adaptive robust control of a lower limbs rehabilitation robot(LLRR) that is a nonlinear system running under passive training mode. In reality, uncertainties including modeling error, initial condition deviation, friction force and other unknown external disturbances always exist in a LLRR system. So, it is necessary to consider the uncertainties in the unilateral man-machine dynamical model of the LLRR we described. In the dynamical model, uncertainties are(possibly fast) time-varying and bounded. However, the bounds are unknown. Based on the dynamical model, we design an adaptive robust control with an adaptive law that is leakagetype based and on the framework of Udwadia-Kalaba theory to compensate for the uncertainties and to realize tracking control of the LLRR. Furthermore, the effectiveness of designed control is shown with numerical simulations.

速度350km/h高速铁路长大下坡地段闭塞分区设置方法研究

通过分析长大下坡道闭塞分区长度对CTCS-3级和后备CTCS-2级列控系统的影响,指出二者对闭塞分区长度的需求完全相反,并针对CTCS-3级列控系统的行车许可回缩、速度突降等问题的产生原因进行分析。阐述坡度、闭塞分区长度与不同列控模式下列车运行速度、追踪间隔时间等要素之间的关系,制定闭塞分区设置的基本原则。检算典型坡度下闭塞分区长度设置的合理区间范围及相应追踪间隔时间,指出坡度超过-30‰后将无法兼顾不同列控等级下的运行速度。设计模拟退火算法,根据闭塞分区设置原则及闭塞分区取值规律,给出压缩求解空间、提高求解效率的方法。以郑万高速铁路长大下坡地段为例,对闭塞分区设置进行优化,在不考虑其他约束的前提下,与设计院优化方案相比,本求解优化方案在确保CTCS-3级控车模式下允许速度可达350 km/h的同时,将CTCS-2级控车模式下的允许速度提高30 km/h,追踪间隔时间压缩23 s。

列车大小交路通信协同运行自适应控制方法

针对列车运输能力与客流时空分布不匹配的问题,提出列车灵活编组方案和短编组小间隔自适应控制方法。首先,根据新型列控系统的特点,设计列车自适应闭环控制框架,构建列车最小追踪间隔模型,提出大小交路列车在小交路通信协同运行的编组方案。其次,根据列车编组方案短编组小间隔控制需求,基于深度确定性策略梯度(Deep Deterministic Policy Gradient,DDPG)算法设计列车自适应控制模型,模型中通过设置奖励函数实现列车多目标控制,通过设计神经网络输出列车最优控制策略。然后,利用Matlab/Simulink仿真平台,以上海地铁2号线2A-2A列车通信协同运行为例,设置其追踪间隔为10 s,搭建加入随机阻力扰动的列车自适应控制模型并进行训练。研究结果表明:列车停车误差为0.1 m,准时误差为0.2 s,协同速度差小于2 km/h,区间最小追踪间隔为180.6 m,满足列车精准停车、速度协同和间隔安全性要求。针对DDPG算法估值过高而导致列车运行速度波动的问题,将神经网络中的Critic网络进行改进,改进后训练仿真表明:列车停车误差为0.03 m,准时误差为0.1 s,协同速度差小于2 km/h,区间最小追踪间隔为181.1 m,列车停车精度和间隔安全性均有提高,且速度波动相对平稳。最后,为验证该控制方法的实时性和安全性,假设前车在意外情况下减速停车,经仿真验证:后车停车误差为1.3 s,停车间隔为220.8 m,满足实时性和安全性的要求。研究成果可为城市轨道交通提供一种灵活匹配客流量的行车编组方案,为新型列控系统列车短编组小间隔运行提供一种安全高效的自适应控制方法。