In the context of the“dual carbon”goals,to address issues such as high energy consumption,high costs,and low power quality in the rapid development of electrified railways,this study focused on the China Railways Hi...In the context of the“dual carbon”goals,to address issues such as high energy consumption,high costs,and low power quality in the rapid development of electrified railways,this study focused on the China Railways High-Speed 5 Electric Multiple Unit and proposed a mathematical model and capacity optimization method for an onboard energy storage system using lithium batteries and supercapacitors as storage media.Firstly,considering the electrical characteristics,weight,and volume of the storage media,a mathematical model of the energy storage system was established.Secondly,to tackle problems related to energy consumption and power quality,an energy management strategy was proposed that comprehensively considers peak shaving and valley filling and power quality by controlling the charge/discharge thresholds of the storage system.Thecapacity optimization adopted a bilevel programming model,with the series/parallel number of storage modules as variables,considering constraints imposed by the Direct Current to Direct Current converter,train load,and space.An improved Particle Swarm Optimization algorithm and linear programming solver were used to solve specific cases.The results show that the proposed onboard energy storage system can effectively achieve energy savings,reduce consumption,and improve power qualitywhile meeting the load and space limitations of the train.展开更多
Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on co...Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on complex signal processing algorithms and lack multi-source data analysis.Driven by multi-source measurement data,including the axle box,the bogie frame and the carbody accelerations,this paper proposes a track irregularities monitoring network(TIMNet)based on deep learning methods.TIMNet uses the feature extraction capability of convolutional neural networks and the sequence map-ping capability of the long short-term memory model to explore the mapping relationship between vehicle accelerations and track irregularities.The particle swarm optimization algorithm is used to optimize the network parameters,so that both the vertical and lateral track irregularities can be accurately identified in the time and spatial domains.The effectiveness and superiority of the proposed TIMNet is analyzed under different simulation conditions using a vehicle dynamics model.Field tests are conducted to prove the availability of the proposed TIMNet in quantitatively monitoring vertical and lateral track irregularities.Furthermore,comparative tests show that the TIMNet has a better fitting degree and timeliness in monitoring track irregularities(vertical R2 of 0.91,lateral R2 of 0.84 and time cost of 10 ms),compared to other classical regression.The test also proves that the TIMNet has a better anti-interference ability than other regression models.展开更多
Railway infrastructure is a crucial asset for the mobility of people and goods.The increased traffic frequency imposes higher loads and speeds,leading to accelerated infrastructure degradation.Asset managers require t...Railway infrastructure is a crucial asset for the mobility of people and goods.The increased traffic frequency imposes higher loads and speeds,leading to accelerated infrastructure degradation.Asset managers require timely information regarding the current(diagnosis)and future(prognosis)condition of their assets to make informed decisions on maintenance and renewal actions.In recent years,in-service vehicles equipped with on-board monitoring(OBM)measuring devices,such as accelerometers,have been introduced on railroad networks,traversing the network almost daily.This article explores the application of state-of-the-art OBM-based track quality indicators for railway infrastructure condition assessment and prediction,primarily under the prism of track geometry quality.The results highlight the similarities and advantages of applying track quality indicators generated from OBM measurements(high frequency and relatively lower accuracy data)compared to those generated from higher precision,yet temporally sparser,data collected by traditional track recording vehicles(TRVs)for infrastructure management purposes.The findings demonstrate the performance of the two approaches,further revealing the value of OBM information for monitoring the track status degradation process.This work makes a case for the advantageous use of OBM data for railway infrastructure management,and attempts to aid understanding in the application of OBM techniques for engineers and operators.展开更多
There is a contradiction between high processing complexity and limited processing resources when turbo codes are used on the on-board processing(OBP)satellite platform.To solve this problem,this paper proposes a part...There is a contradiction between high processing complexity and limited processing resources when turbo codes are used on the on-board processing(OBP)satellite platform.To solve this problem,this paper proposes a partial iterative decode method for on-board application,in which satellite only carries out limited number of iteration according to the on-board processing resource limitation and the throughput capacity requirements.In this method,the soft information of parity bits,which is not obtained individually in conventional turbo decoder,is encoded and forwarded along with those of information bits.To save downlink transmit power,the soft information is limited and normalized before forwarding.The iteration number and limiter parameters are optimized with the help of EXIT chart and numerical analysis,respectively.Simulation results show that the proposed method can effectively decrease the complexity of onboard processing while achieve most of the decoding gain..展开更多
Digital sun sensor is one of the most important sensors used in the Attitude Determination System(ADS)of the satellite.Due to the harsh environmental conditions that exist in the space,various distortions may occur in...Digital sun sensor is one of the most important sensors used in the Attitude Determination System(ADS)of the satellite.Due to the harsh environmental conditions that exist in the space,various distortions may occur in the sun sensor optical system that lead to the reduced accuracy of this equipment.So,it is necessary to recalibrate the optical parameters of the aforementioned sensors.For this purpose,first a novel attitude independent error model is proposed for the SS-411 sun sensor that includes the central point of the CCD array,installation error,filter thickness and sensor misalignment.So,the mutual interfaces between the sensor parameters are considered in the developed model.In order to extract the sensor parameters,a nonlinear optimization technique called the Levenberg–Marquardt is applied to the developed model as a batch algorithm.In addition,the Extended Kalman Filter(EKF)and the Unscented Kalman Filter(UKF)have been utilized as sequential strategies.It will be shown that by considering a worst case of variation amount for sensor parameters,an accuracy improvement of about 17°is achieved by the developed calibration algorithms.Comparison between the developed algorithms represents that UKF has higher accuracy,shorter time convergence but higher computational load.展开更多
This study investigated the emission characteristics of ultra.fine particles based on test bench and on-board measurements. The bench test results showed the ultrafine particle number concentration of the diesel engin...This study investigated the emission characteristics of ultra.fine particles based on test bench and on-board measurements. The bench test results showed the ultrafine particle number concentration of the diesel engine to be in the range of （0.56-8.35）×10^8 cm^-3. The on-board measurement results illustrated that the ultra_fine particles were strongly correlated with changes in real-world driving cycles. The particle number concentration was down to 2.0 ×10^6 cm^-3 and 2.7 ×10^7 cm^-3 under decelerating and idling operations and as high as 5.0×10^8 cm^-3 under accelerating operation. It was also indicated that the particle number measured by the two methods increased with the growth of engine load at each engine speed in both cases. The particle number presented a ＂U＂ shaped distribution with changing speed at high engine load conditions, which implies that the particle number will reach its lowest level at medium engine speeds. The particle sizes of both measurements showed single mode distributions. The peak of particle size was located at about 50-80 nm in the accumulation mode particle range. Nucleation mode particles will significantly increase at low engine load operations like idling and decelerating caused by the high concentration of unburned organic compounds.展开更多
In the present paper, a physical model is proposed for reducing the problem of the drag reduction of an attached bow shock around the nose of a high-speed vehicle with on-board discharge, to the problem of a balance b...In the present paper, a physical model is proposed for reducing the problem of the drag reduction of an attached bow shock around the nose of a high-speed vehicle with on-board discharge, to the problem of a balance between the magnetic pressure and gas pressure of plane shock of a partially ionized gas consisting of the environmental gas around the nose of the vehicle and the on-board discharge-produced plasma. The relation between the shock strength and the discharge-induced magnetic pressure is studied by means of a set of one-fluid, hydromagnetic equations reformed for the present purpose, where the discharge-induced magnetic field consists of the electron current （produced by the discharge）-induced magnetic field and the partially ionized gas flow-induced one. A formula for the relation between the above parameters is derived. It shows that the discharge-induced magnetic pressure can minimize the shock strength, successfully explaining the two recent experimental observations on attached bow shock mitigation and elimination in a supersonic flow during on-board discharge [Phys. Plasmas 9 （2002） 721 and Phys. Plasmas 7 （2000） 1345]. In addition, the formula implies that the shock elimination leaves room for a layer of higher-density plasma rampart moving around the nose of the vehicle, being favourable to the plasma radar cloaking of the vehicle. The reason for it is expounded.展开更多
The conventional troubleshooting methods for high-speed railway on-board equipment, with over-reliance on personnel experience, is characterized by one-sidedness and low efficiency. In the process of high-speed train ...The conventional troubleshooting methods for high-speed railway on-board equipment, with over-reliance on personnel experience, is characterized by one-sidedness and low efficiency. In the process of high-speed train operation, numerous text-based onboard logs are recorded by on-board computers. Machine learning methods can help technicians make a correct judgment of fault types using the on-board log reasonably. Therefore, a fault classification model of on-board equipment based on attention capsule networks is proposed. This paper presents an empirical exploration of the application of a capsule network with dynamic routing in fault classification. A capsule network can encode the internal spatial part-whole relationship between various entities to identify the fault types. As the importance of each word in the on-board log and the dependencies between them have a significant impact on fault classification, an attention mechanism is incorporated into the capsule network to distill important information. Considering the imbalanced distribution of normal data and fault data in the on-board log, the focal loss function is introduced into the model to adjust the imbalanced data. The experiments are conducted on the on-board log of a railway bureau and compared with other baseline models. The experimental results demonstrate that our model outperforms the compared baseline methods, proving the superiority and competitiveness of our model.展开更多
On-board measurements of unit emissions of CO,HC,NOx and CO2 were conducted on 17 private cars powered by different types of fuels including gasoline,dual gasoline–liquefied petroleum gas（LPG）,gasoline,and diesel. ...On-board measurements of unit emissions of CO,HC,NOx and CO2 were conducted on 17 private cars powered by different types of fuels including gasoline,dual gasoline–liquefied petroleum gas（LPG）,gasoline,and diesel. The tests performed revealed the effect of LPG injection technology on unit emissions and made it possible to compare the measured emissions to the European Artemis emission model. A sequential multipoint injection LPG kit with no catalyst installed was found to be the most efficient pollutant reduction device for all of the pollutants,with the exception of the NOx. Specific test results for a sub-group of LPG vehicles revealed that LPG-fueled engines with no catalyst cannot compete with catalyzed gasoline and diesel engines. Vehicle age does not appear to be a determining parameter with regard to vehicle pollutant emissions. A fuel switch to LPG offers many advantages as far as pollutant emissions are concerned,due to LPG＇s intrinsic characteristics.However,these advantages are being rapidly offset by the strong development of both gasoline and diesel engine technologies and catalyst converters. The LPG＇s performance on a chassis dynamometer under real driving conditions was better than expected. The enforcement of pollutant emission standards in developing countries is an important step towards introducing clean technology and reducing vehicle emissions.展开更多
In this study,the particle size-resolved distribution from a China-3 certificated light-duty diesel vehicle was measured by using a portable emission measurement system（PEMS）.In order to examine the influences of ve...In this study,the particle size-resolved distribution from a China-3 certificated light-duty diesel vehicle was measured by using a portable emission measurement system（PEMS）.In order to examine the influences of vehicle specific power（VSP） and high-altitude operation,measurements were conducted at 8 constant speeds,which ranged from 10 to 80 km/hr at10 km/hr intervals,and two different high altitudes,namely 2200 and 3200 m.The results demonstrated that the numbers of particles in all size ranges decreased significantly as VSP increased when the test vehicle was running at lower speeds（〈 20 km/hr）,while at a moderate speed（between 30 and 60 km/hr）,the particle number was statistically insensitive to increase VSP.Under high-speed cruising conditions,the numbers of ultrafine particles and PM2.5were insensitive to changes in VSP,but the numbers of nanoparticles and PM10 surged considerably.An increase in the operational altitude of the test vehicle resulted in increased particle number emissions at low and high driving speeds;however,particle numbers obtained at moderate speeds decreased as altitude rose.When the test vehicle was running at moderate speeds,particle numbers measured at the two altitudes were very close,except for comparatively higher number concentrations of nanoparticles measured at 2200 m.展开更多
Rapid and precise location of the faults of on-board equipment of train control system is a significant factor to ensure reliable train operation.Text data of the fault tracking table of on-board equipment are taken a...Rapid and precise location of the faults of on-board equipment of train control system is a significant factor to ensure reliable train operation.Text data of the fault tracking table of on-board equipment are taken as samples,and an on-board equipment fault diagnosis model is designed based on the combination of convolutional neural network(CNN)and particle swarm optimization-support vector machines(PSO-SVM).Due to the characteristics of high dimensionality and sparseness of fault text data,CNN is used to achieve feature extraction.In order to decrease the influence of the imbalance of the fault sample data category on the classification accuracy,the PSO-SVM algorithm is introduced.The fully connected classification part of CNN is replaced by PSO-SVM,the extracted features are classified precisely,and the intelligent diagnosis of on-board equipment fault is implemented.According to the test analysis of the fault text data of on-board equipment recorded by a railway bureau and comparison with other models,the experimental results indicate that this model can obviously upgrade the evaluation indexes and can be used as an effective model for fault diagnosis for on-board equipment.展开更多
A problem of peak power in DC-electrified railway systems is mainly caused by train power demand during acceleration.If this power is reduced,substation peak power will be significantly decreased.This paper presents a...A problem of peak power in DC-electrified railway systems is mainly caused by train power demand during acceleration.If this power is reduced,substation peak power will be significantly decreased.This paper presents a study on optimal energy saving in DC-electrified railway with on-board energy storage system(OBESS) by using peak demand cutting strategy under different trip time controls.The proposed strategy uses OBESS to store recovered braking energy and find an appropriated time to deliver the stored energy back to the power network in such a way that peak power of every substations is reduced.Bangkok Mass Transit System(BTS)-Silom Line in Thailand is used to test and verify the proposed strategy.The results show that substation peak power is reduced by63.49% and net energy consumption is reduced by 15.56%using coasting and deceleration trip time control.展开更多
Modern satellite communication systems require on-board processing(OBP)for performance improvements,and SRAM-FPGAs are an attractive option for OBP implementation.However,SRAM-FPGAs are sensitive to radiation effects,...Modern satellite communication systems require on-board processing(OBP)for performance improvements,and SRAM-FPGAs are an attractive option for OBP implementation.However,SRAM-FPGAs are sensitive to radiation effects,among which single event upsets(SEUs)are important as they can lead to data corruption and system failure.This paper studies the fault tolerance capability of a SRAM-FPGA implemented Viterbi decoder to SEUs on the user memory.Analysis and fault injection experiments are conducted to verify that over 97%of the SEUs on user memory would not lead to output errors.To achieve a better reliability,selective protection schemes are then proposed to further improve the reliability of the decoder to SEUs on user memory with very small overhead.Although the results are obtained for a specific FPGA implementation,the developed reliability estimation model and the general conclusions still hold for other implementations.展开更多
This paper focuses on the time efficiency for machine vision and intelligent photogrammetry, especially high accuracy on-board real-time cloud detection method. With the development of technology, the data acquisition...This paper focuses on the time efficiency for machine vision and intelligent photogrammetry, especially high accuracy on-board real-time cloud detection method. With the development of technology, the data acquisition ability is growing continuously and the volume of raw data is increasing explosively. Meanwhile, because of the higher requirement of data accuracy, the computation load is also becoming heavier. This situation makes time efficiency extremely important. Moreover, the cloud cover rate of optical satellite imagery is up to approximately 50%, which is seriously restricting the applications of on-board intelligent photogrammetry services. To meet the on-board cloud detection requirements and offer valid input data to subsequent processing, this paper presents a stream-computing of high accuracy on-board real-time cloud detection solution which follows the “bottom-up” understanding strategy of machine vision and uses multiple embedded GPU with significant potential to be applied on-board. Without external memory, the data parallel pipeline system based on multiple processing modules of this solution could afford the “stream-in, processing, stream-out” real-time stream computing. In experiments, images of GF-2 satellite are used to validate the accuracy and performance of this approach, and the experimental results show that this solution could not only bring up cloud detection accuracy, but also match the on-board real-time processing requirements.展开更多
The harsh space radiation environment compromises the reliability of an on-board switching fabric by leading to cross-point and switching element(SE)faults.Different from traditional faulttolerant switching fabrics on...The harsh space radiation environment compromises the reliability of an on-board switching fabric by leading to cross-point and switching element(SE)faults.Different from traditional faulttolerant switching fabrics only taking crosspoint faults into account,a novel Input and Output Parallel Clos network,referred to as the(p_1,p_2)-IOPClos,is proposed to tolerate both cross-point and SE faults.In the(p_1,p_2)-IOPClos,there are p_1 and p_2 expanded parallel switching planes in the input and output stages,respectively.The multiple input/output switching planes are interconnected through the middle stage to provide multiple paths in each stage by which the network throughput can be increased remarkably.Furthermore,the network reliability of the(p_1,p_2)-IOPClos under the above both kinds of faults is analyzed.The corresponding implementation cost is also presented along with the network size.Both theoretical analysis and numerical results indicate that the(p_1,p_2)-IOPClos outperforms traditional Clos-type networks at reliability,while has less implementation cost than the multi-plane Clos network.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
To make the on-board computer system more dependable and real-time in a satellite, an algorithm of the fault-tolerant scheduling in the on-board computer system with high priority recovery is proposed in this paper. T...To make the on-board computer system more dependable and real-time in a satellite, an algorithm of the fault-tolerant scheduling in the on-board computer system with high priority recovery is proposed in this paper. This algorithm can schedule the on-board fault-tolerant tasks in real time. Due to the use of dependability cost, the overhead of scheduling the fault-tolerant tasks can be reduced. The mechanism of the high priority recovery will improve the response to recovery tasks. The fault-tolerant scheduling model is presented simulation results validate the correctness and feasibility of the proposed algorithm.展开更多
As a result of the exponential growing rate of worldwide Internet usage, satellite systems are required to support broadband Internet applications. The transmission control protocol （TCP） which is widely used in the...As a result of the exponential growing rate of worldwide Internet usage, satellite systems are required to support broadband Internet applications. The transmission control protocol （TCP） which is widely used in the Internet, performs very well on wired networks. However, in the case of satellite channels, clue to the delay and transmission errors, TCP performance degrades significantly and bandwidth of satellite links can not be fully utilized. To improve the TCP performance, a new idea of placing a TCP spoofing proxy in the satellite is considered. A Novel Satellite Transport Protocol （NSTP） which takes advantage of the special properties of the satellite channel is also proposed. By using simulation, as compared with traditional TCPs, the on-board spoofing proxy integrated with the special transport protocol can significantly enhance throughput performance on the high BER satellite link, the time needed to transfer files and the bandwidth used in reverse path are sharply reduced.展开更多
To make full use of expanded maneuverability and increased range,adaptive constrained on-board guidance technology is the key capability for a glide vehicle with a double-pulse rocket engine,especially under the requi...To make full use of expanded maneuverability and increased range,adaptive constrained on-board guidance technology is the key capability for a glide vehicle with a double-pulse rocket engine,especially under the requirements of desired target changing and on-line reconfigurable control and guidance.Based on the rapid footprint analysis,whether the new target is within the current footprint area is firstly judged.If not,the rocket engine ignites by the logic obtained from the analysis of optimal flight range by the method of hp-adaptive Gauss pseudospectral method(hp-GPM).Then,an on-board trajectory generation method based on powered quasi-equilibrium glide condition(QEGC)and linear quadratic regulator(LQR)method is used to guide the vehicle to the new target.The effectiveness of the guidance method consisted of powered on-board trajectory generation,LQR trajectory tracking,footprint calculation,and ignition time determination is indicated by some simulation examples.展开更多
The present analytical review is devoted to the current problem of thermodynamic stability and related thermodynamic characteristics of the following graphene layers systems: 1) double-side hydrogenated graphene of co...The present analytical review is devoted to the current problem of thermodynamic stability and related thermodynamic characteristics of the following graphene layers systems: 1) double-side hydrogenated graphene of composition CH (theoretical graphane) (Sofo et al. 2007) and experimental graphane (Elias et al. 2009);2) theoretical single-side hydrogenated graphene of composition CH;3) theoretical single-side hydrogenated graphene of composition C2H (graphone);4) experimental hydrogenated epitaxial graphene, bilayer graphene and a few layers of graphene on SiO2 or other substrates;5) experimental and theoretical single-external side hydrogenated single-walled carbon nanotubes, and experimental hydrofullerene C60H36;6) experimental single-internal side hydrogenated (up to C2H or CH composition) graphene nanoblisters with intercalated high pressure H2 gas inside them, formed on a surface of highly oriented pyrolytic graphite or epitaxial graphene under the atomic hydrogen treatment;and 7) experimental hydrogenated graphite nanofibers-multigraphene with intercalated solid H2 nano-regions of high density inside them, relevant to solving the problem of hydrogen on-board storage (Nechaev 2011-2012).展开更多
基金funded by the National Natural Science Foundation of China(52167013)the Key Program of Natural Science Foundation of Gansu Province(24JRRA225)Natural Science Foundation of Gansu Province(23JRRA891).
文摘In the context of the“dual carbon”goals,to address issues such as high energy consumption,high costs,and low power quality in the rapid development of electrified railways,this study focused on the China Railways High-Speed 5 Electric Multiple Unit and proposed a mathematical model and capacity optimization method for an onboard energy storage system using lithium batteries and supercapacitors as storage media.Firstly,considering the electrical characteristics,weight,and volume of the storage media,a mathematical model of the energy storage system was established.Secondly,to tackle problems related to energy consumption and power quality,an energy management strategy was proposed that comprehensively considers peak shaving and valley filling and power quality by controlling the charge/discharge thresholds of the storage system.Thecapacity optimization adopted a bilevel programming model,with the series/parallel number of storage modules as variables,considering constraints imposed by the Direct Current to Direct Current converter,train load,and space.An improved Particle Swarm Optimization algorithm and linear programming solver were used to solve specific cases.The results show that the proposed onboard energy storage system can effectively achieve energy savings,reduce consumption,and improve power qualitywhile meeting the load and space limitations of the train.
基金supported by the Sichuan Science and Technology Program(Nos.2024JDRC0100 and 2023YFQ0091)the National Natural Science Foundation of China(Nos.U21A20167 and 52475138)the Scientific Research Foundation of the State Key Laboratory of Rail Transit Vehicle System(No.2024RVL-T08).
文摘Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on complex signal processing algorithms and lack multi-source data analysis.Driven by multi-source measurement data,including the axle box,the bogie frame and the carbody accelerations,this paper proposes a track irregularities monitoring network(TIMNet)based on deep learning methods.TIMNet uses the feature extraction capability of convolutional neural networks and the sequence map-ping capability of the long short-term memory model to explore the mapping relationship between vehicle accelerations and track irregularities.The particle swarm optimization algorithm is used to optimize the network parameters,so that both the vertical and lateral track irregularities can be accurately identified in the time and spatial domains.The effectiveness and superiority of the proposed TIMNet is analyzed under different simulation conditions using a vehicle dynamics model.Field tests are conducted to prove the availability of the proposed TIMNet in quantitatively monitoring vertical and lateral track irregularities.Furthermore,comparative tests show that the TIMNet has a better fitting degree and timeliness in monitoring track irregularities(vertical R2 of 0.91,lateral R2 of 0.84 and time cost of 10 ms),compared to other classical regression.The test also proves that the TIMNet has a better anti-interference ability than other regression models.
基金supported financially by the project OMISM from the ETH Zurich Mobility Initiative。
文摘Railway infrastructure is a crucial asset for the mobility of people and goods.The increased traffic frequency imposes higher loads and speeds,leading to accelerated infrastructure degradation.Asset managers require timely information regarding the current(diagnosis)and future(prognosis)condition of their assets to make informed decisions on maintenance and renewal actions.In recent years,in-service vehicles equipped with on-board monitoring(OBM)measuring devices,such as accelerometers,have been introduced on railroad networks,traversing the network almost daily.This article explores the application of state-of-the-art OBM-based track quality indicators for railway infrastructure condition assessment and prediction,primarily under the prism of track geometry quality.The results highlight the similarities and advantages of applying track quality indicators generated from OBM measurements(high frequency and relatively lower accuracy data)compared to those generated from higher precision,yet temporally sparser,data collected by traditional track recording vehicles(TRVs)for infrastructure management purposes.The findings demonstrate the performance of the two approaches,further revealing the value of OBM information for monitoring the track status degradation process.This work makes a case for the advantageous use of OBM data for railway infrastructure management,and attempts to aid understanding in the application of OBM techniques for engineers and operators.
基金supported by National High Technology Research and Development Program(863 Program,2012AA01A502)National Natural Science Foundation of China (41206031)National Basic Research Program(2012CB316000)
文摘There is a contradiction between high processing complexity and limited processing resources when turbo codes are used on the on-board processing(OBP)satellite platform.To solve this problem,this paper proposes a partial iterative decode method for on-board application,in which satellite only carries out limited number of iteration according to the on-board processing resource limitation and the throughput capacity requirements.In this method,the soft information of parity bits,which is not obtained individually in conventional turbo decoder,is encoded and forwarded along with those of information bits.To save downlink transmit power,the soft information is limited and normalized before forwarding.The iteration number and limiter parameters are optimized with the help of EXIT chart and numerical analysis,respectively.Simulation results show that the proposed method can effectively decrease the complexity of onboard processing while achieve most of the decoding gain..
文摘Digital sun sensor is one of the most important sensors used in the Attitude Determination System(ADS)of the satellite.Due to the harsh environmental conditions that exist in the space,various distortions may occur in the sun sensor optical system that lead to the reduced accuracy of this equipment.So,it is necessary to recalibrate the optical parameters of the aforementioned sensors.For this purpose,first a novel attitude independent error model is proposed for the SS-411 sun sensor that includes the central point of the CCD array,installation error,filter thickness and sensor misalignment.So,the mutual interfaces between the sensor parameters are considered in the developed model.In order to extract the sensor parameters,a nonlinear optimization technique called the Levenberg–Marquardt is applied to the developed model as a batch algorithm.In addition,the Extended Kalman Filter(EKF)and the Unscented Kalman Filter(UKF)have been utilized as sequential strategies.It will be shown that by considering a worst case of variation amount for sensor parameters,an accuracy improvement of about 17°is achieved by the developed calibration algorithms.Comparison between the developed algorithms represents that UKF has higher accuracy,shorter time convergence but higher computational load.
基金supported the Instantaneous Emission and Environmental Impact study on Vehicle Alternative Fuel(No.10231201902)the Project of Study and Demonstration of Real Time On-Road Vehicle Emission and Pollution Warning (No.10231201700) from the Shanghai Science and Technology Commission
文摘This study investigated the emission characteristics of ultra.fine particles based on test bench and on-board measurements. The bench test results showed the ultrafine particle number concentration of the diesel engine to be in the range of （0.56-8.35）×10^8 cm^-3. The on-board measurement results illustrated that the ultra_fine particles were strongly correlated with changes in real-world driving cycles. The particle number concentration was down to 2.0 ×10^6 cm^-3 and 2.7 ×10^7 cm^-3 under decelerating and idling operations and as high as 5.0×10^8 cm^-3 under accelerating operation. It was also indicated that the particle number measured by the two methods increased with the growth of engine load at each engine speed in both cases. The particle number presented a ＂U＂ shaped distribution with changing speed at high engine load conditions, which implies that the particle number will reach its lowest level at medium engine speeds. The particle sizes of both measurements showed single mode distributions. The peak of particle size was located at about 50-80 nm in the accumulation mode particle range. Nucleation mode particles will significantly increase at low engine load operations like idling and decelerating caused by the high concentration of unburned organic compounds.
基金Project supported by the National Natural Science Foundation of China （Grant Nos 40390150 and 10005001）.
文摘In the present paper, a physical model is proposed for reducing the problem of the drag reduction of an attached bow shock around the nose of a high-speed vehicle with on-board discharge, to the problem of a balance between the magnetic pressure and gas pressure of plane shock of a partially ionized gas consisting of the environmental gas around the nose of the vehicle and the on-board discharge-produced plasma. The relation between the shock strength and the discharge-induced magnetic pressure is studied by means of a set of one-fluid, hydromagnetic equations reformed for the present purpose, where the discharge-induced magnetic field consists of the electron current （produced by the discharge）-induced magnetic field and the partially ionized gas flow-induced one. A formula for the relation between the above parameters is derived. It shows that the discharge-induced magnetic pressure can minimize the shock strength, successfully explaining the two recent experimental observations on attached bow shock mitigation and elimination in a supersonic flow during on-board discharge [Phys. Plasmas 9 （2002） 721 and Phys. Plasmas 7 （2000） 1345]. In addition, the formula implies that the shock elimination leaves room for a layer of higher-density plasma rampart moving around the nose of the vehicle, being favourable to the plasma radar cloaking of the vehicle. The reason for it is expounded.
基金supported by National Natural Science Foundation of China(No.61763025)Gansu Science and Technology Program Project(No.18JR3RA104)+1 种基金Industrial support program for colleges and universities in Gansu Province(No.2020C-19)Lanzhou Science and Technology Project(No.2019-4-49)。
文摘The conventional troubleshooting methods for high-speed railway on-board equipment, with over-reliance on personnel experience, is characterized by one-sidedness and low efficiency. In the process of high-speed train operation, numerous text-based onboard logs are recorded by on-board computers. Machine learning methods can help technicians make a correct judgment of fault types using the on-board log reasonably. Therefore, a fault classification model of on-board equipment based on attention capsule networks is proposed. This paper presents an empirical exploration of the application of a capsule network with dynamic routing in fault classification. A capsule network can encode the internal spatial part-whole relationship between various entities to identify the fault types. As the importance of each word in the on-board log and the dependencies between them have a significant impact on fault classification, an attention mechanism is incorporated into the capsule network to distill important information. Considering the imbalanced distribution of normal data and fault data in the on-board log, the focal loss function is introduced into the model to adjust the imbalanced data. The experiments are conducted on the on-board log of a railway bureau and compared with other baseline models. The experimental results demonstrate that our model outperforms the compared baseline methods, proving the superiority and competitiveness of our model.
文摘On-board measurements of unit emissions of CO,HC,NOx and CO2 were conducted on 17 private cars powered by different types of fuels including gasoline,dual gasoline–liquefied petroleum gas（LPG）,gasoline,and diesel. The tests performed revealed the effect of LPG injection technology on unit emissions and made it possible to compare the measured emissions to the European Artemis emission model. A sequential multipoint injection LPG kit with no catalyst installed was found to be the most efficient pollutant reduction device for all of the pollutants,with the exception of the NOx. Specific test results for a sub-group of LPG vehicles revealed that LPG-fueled engines with no catalyst cannot compete with catalyzed gasoline and diesel engines. Vehicle age does not appear to be a determining parameter with regard to vehicle pollutant emissions. A fuel switch to LPG offers many advantages as far as pollutant emissions are concerned,due to LPG＇s intrinsic characteristics.However,these advantages are being rapidly offset by the strong development of both gasoline and diesel engine technologies and catalyst converters. The LPG＇s performance on a chassis dynamometer under real driving conditions was better than expected. The enforcement of pollutant emission standards in developing countries is an important step towards introducing clean technology and reducing vehicle emissions.
基金financially supported by the National Natural Science Foundation of China(Nos.51576016 and 51476012)
文摘In this study,the particle size-resolved distribution from a China-3 certificated light-duty diesel vehicle was measured by using a portable emission measurement system（PEMS）.In order to examine the influences of vehicle specific power（VSP） and high-altitude operation,measurements were conducted at 8 constant speeds,which ranged from 10 to 80 km/hr at10 km/hr intervals,and two different high altitudes,namely 2200 and 3200 m.The results demonstrated that the numbers of particles in all size ranges decreased significantly as VSP increased when the test vehicle was running at lower speeds（〈 20 km/hr）,while at a moderate speed（between 30 and 60 km/hr）,the particle number was statistically insensitive to increase VSP.Under high-speed cruising conditions,the numbers of ultrafine particles and PM2.5were insensitive to changes in VSP,but the numbers of nanoparticles and PM10 surged considerably.An increase in the operational altitude of the test vehicle resulted in increased particle number emissions at low and high driving speeds;however,particle numbers obtained at moderate speeds decreased as altitude rose.When the test vehicle was running at moderate speeds,particle numbers measured at the two altitudes were very close,except for comparatively higher number concentrations of nanoparticles measured at 2200 m.
基金Gansu Province Higher Education Innovation Fund Project(No.2020B-104)“Innovation Star”Project for Outstanding Postgraduates of Gansu Province(No.2021CXZX-606)。
文摘Rapid and precise location of the faults of on-board equipment of train control system is a significant factor to ensure reliable train operation.Text data of the fault tracking table of on-board equipment are taken as samples,and an on-board equipment fault diagnosis model is designed based on the combination of convolutional neural network(CNN)and particle swarm optimization-support vector machines(PSO-SVM).Due to the characteristics of high dimensionality and sparseness of fault text data,CNN is used to achieve feature extraction.In order to decrease the influence of the imbalance of the fault sample data category on the classification accuracy,the PSO-SVM algorithm is introduced.The fully connected classification part of CNN is replaced by PSO-SVM,the extracted features are classified precisely,and the intelligent diagnosis of on-board equipment fault is implemented.According to the test analysis of the fault text data of on-board equipment recorded by a railway bureau and comparison with other models,the experimental results indicate that this model can obviously upgrade the evaluation indexes and can be used as an effective model for fault diagnosis for on-board equipment.
文摘A problem of peak power in DC-electrified railway systems is mainly caused by train power demand during acceleration.If this power is reduced,substation peak power will be significantly decreased.This paper presents a study on optimal energy saving in DC-electrified railway with on-board energy storage system(OBESS) by using peak demand cutting strategy under different trip time controls.The proposed strategy uses OBESS to store recovered braking energy and find an appropriated time to deliver the stored energy back to the power network in such a way that peak power of every substations is reduced.Bangkok Mass Transit System(BTS)-Silom Line in Thailand is used to test and verify the proposed strategy.The results show that substation peak power is reduced by63.49% and net energy consumption is reduced by 15.56%using coasting and deceleration trip time control.
基金supported in part by the National Key R&D Program(Grant No.2017YFE0121300)in part by the National Natural Science Foundation of China (Grant No. 61501321)+1 种基金in part by Tianjin science and technology program (Grant No. 17ZXRGGX00160)the support of the TEXEO project TEC201680339R funded by the Spanish Ministry of Economy and Competitivity
文摘Modern satellite communication systems require on-board processing(OBP)for performance improvements,and SRAM-FPGAs are an attractive option for OBP implementation.However,SRAM-FPGAs are sensitive to radiation effects,among which single event upsets(SEUs)are important as they can lead to data corruption and system failure.This paper studies the fault tolerance capability of a SRAM-FPGA implemented Viterbi decoder to SEUs on the user memory.Analysis and fault injection experiments are conducted to verify that over 97%of the SEUs on user memory would not lead to output errors.To achieve a better reliability,selective protection schemes are then proposed to further improve the reliability of the decoder to SEUs on user memory with very small overhead.Although the results are obtained for a specific FPGA implementation,the developed reliability estimation model and the general conclusions still hold for other implementations.
基金The National Natural Science Foundation of China (91438203,91638301,91438111,41601476).
文摘This paper focuses on the time efficiency for machine vision and intelligent photogrammetry, especially high accuracy on-board real-time cloud detection method. With the development of technology, the data acquisition ability is growing continuously and the volume of raw data is increasing explosively. Meanwhile, because of the higher requirement of data accuracy, the computation load is also becoming heavier. This situation makes time efficiency extremely important. Moreover, the cloud cover rate of optical satellite imagery is up to approximately 50%, which is seriously restricting the applications of on-board intelligent photogrammetry services. To meet the on-board cloud detection requirements and offer valid input data to subsequent processing, this paper presents a stream-computing of high accuracy on-board real-time cloud detection solution which follows the “bottom-up” understanding strategy of machine vision and uses multiple embedded GPU with significant potential to be applied on-board. Without external memory, the data parallel pipeline system based on multiple processing modules of this solution could afford the “stream-in, processing, stream-out” real-time stream computing. In experiments, images of GF-2 satellite are used to validate the accuracy and performance of this approach, and the experimental results show that this solution could not only bring up cloud detection accuracy, but also match the on-board real-time processing requirements.
基金supported by the National Natural Science Foundation of China(91338108,91438206)
文摘The harsh space radiation environment compromises the reliability of an on-board switching fabric by leading to cross-point and switching element(SE)faults.Different from traditional faulttolerant switching fabrics only taking crosspoint faults into account,a novel Input and Output Parallel Clos network,referred to as the(p_1,p_2)-IOPClos,is proposed to tolerate both cross-point and SE faults.In the(p_1,p_2)-IOPClos,there are p_1 and p_2 expanded parallel switching planes in the input and output stages,respectively.The multiple input/output switching planes are interconnected through the middle stage to provide multiple paths in each stage by which the network throughput can be increased remarkably.Furthermore,the network reliability of the(p_1,p_2)-IOPClos under the above both kinds of faults is analyzed.The corresponding implementation cost is also presented along with the network size.Both theoretical analysis and numerical results indicate that the(p_1,p_2)-IOPClos outperforms traditional Clos-type networks at reliability,while has less implementation cost than the multi-plane Clos network.
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.
文摘To make the on-board computer system more dependable and real-time in a satellite, an algorithm of the fault-tolerant scheduling in the on-board computer system with high priority recovery is proposed in this paper. This algorithm can schedule the on-board fault-tolerant tasks in real time. Due to the use of dependability cost, the overhead of scheduling the fault-tolerant tasks can be reduced. The mechanism of the high priority recovery will improve the response to recovery tasks. The fault-tolerant scheduling model is presented simulation results validate the correctness and feasibility of the proposed algorithm.
文摘As a result of the exponential growing rate of worldwide Internet usage, satellite systems are required to support broadband Internet applications. The transmission control protocol （TCP） which is widely used in the Internet, performs very well on wired networks. However, in the case of satellite channels, clue to the delay and transmission errors, TCP performance degrades significantly and bandwidth of satellite links can not be fully utilized. To improve the TCP performance, a new idea of placing a TCP spoofing proxy in the satellite is considered. A Novel Satellite Transport Protocol （NSTP） which takes advantage of the special properties of the satellite channel is also proposed. By using simulation, as compared with traditional TCPs, the on-board spoofing proxy integrated with the special transport protocol can significantly enhance throughput performance on the high BER satellite link, the time needed to transfer files and the bandwidth used in reverse path are sharply reduced.
基金supported by the National Natural Science Foundation of China(No.61403100)Fundamental Research Funds for the Central Universities(HIT.NSRIF.2015037)
文摘To make full use of expanded maneuverability and increased range,adaptive constrained on-board guidance technology is the key capability for a glide vehicle with a double-pulse rocket engine,especially under the requirements of desired target changing and on-line reconfigurable control and guidance.Based on the rapid footprint analysis,whether the new target is within the current footprint area is firstly judged.If not,the rocket engine ignites by the logic obtained from the analysis of optimal flight range by the method of hp-adaptive Gauss pseudospectral method(hp-GPM).Then,an on-board trajectory generation method based on powered quasi-equilibrium glide condition(QEGC)and linear quadratic regulator(LQR)method is used to guide the vehicle to the new target.The effectiveness of the guidance method consisted of powered on-board trajectory generation,LQR trajectory tracking,footprint calculation,and ignition time determination is indicated by some simulation examples.
文摘The present analytical review is devoted to the current problem of thermodynamic stability and related thermodynamic characteristics of the following graphene layers systems: 1) double-side hydrogenated graphene of composition CH (theoretical graphane) (Sofo et al. 2007) and experimental graphane (Elias et al. 2009);2) theoretical single-side hydrogenated graphene of composition CH;3) theoretical single-side hydrogenated graphene of composition C2H (graphone);4) experimental hydrogenated epitaxial graphene, bilayer graphene and a few layers of graphene on SiO2 or other substrates;5) experimental and theoretical single-external side hydrogenated single-walled carbon nanotubes, and experimental hydrofullerene C60H36;6) experimental single-internal side hydrogenated (up to C2H or CH composition) graphene nanoblisters with intercalated high pressure H2 gas inside them, formed on a surface of highly oriented pyrolytic graphite or epitaxial graphene under the atomic hydrogen treatment;and 7) experimental hydrogenated graphite nanofibers-multigraphene with intercalated solid H2 nano-regions of high density inside them, relevant to solving the problem of hydrogen on-board storage (Nechaev 2011-2012).
