Evaluation of the health state and prediction of the remaining life of the track circuit are important for the safe operation of the equipment of railway signal system.Based on support vector data description(SVDD)and...Evaluation of the health state and prediction of the remaining life of the track circuit are important for the safe operation of the equipment of railway signal system.Based on support vector data description(SVDD)and gray prediction,this paper illustrates a method of life prediction for ZPW-2000A track circuit,which combines entropy weight method,SVDD,Mahalanobis distance and negative conversion function to set up a health state assessment model.The model transforms multiple factors affecting the health state into a health index named H to reflect the health state of the equipment.According to H,the life prediction model of ZPW-2000A track circuit equipment is established by means of gray prediction so as to predict the trend of health state of the equipment.The certification of the example shows that the method can visually reflect the health state and effectively predict the remaining life of the equipment.It also provides a theoretical basis to further improve the maintenance and management for ZPW-2000A track circuit.展开更多
At present,ZPW-2000 track circuit fault diagnosis is artificially analyzed and monitored.Its discrimination method not only is low efficient and takes a long period,but also requires highly experienced personnel to an...At present,ZPW-2000 track circuit fault diagnosis is artificially analyzed and monitored.Its discrimination method not only is low efficient and takes a long period,but also requires highly experienced personnel to analyze the data.Therefore,we introduce kernel principal component analysis and stacked auto-encoder network(KPCA-SAD)into the fault diagnosis of ZPW-2000 track circuit.According to the working principle and fault characteristics of track circuit,a fault diagnosis model of KPCA-SAE network is established.The relevant parameters of key components recorded in the data collected by field staff are used as the fault feature parameters.The KPCA method is used to reduce the dimension and noise of fault document matrix to avoid information redundancy.The SAE network is trained by the processed fault data.The model parameters are optimized overall by using back propagation(BP)algorithm.The KPCA-SAE model is simulated in Matlab platform and is finally proved to be effective and feasible.Compared with the traditional method of artificially analyzing fault data and other intelligent algorithms,the KPCA-SAE based classifier has higher fault identification accuracy.展开更多
The multi-tone frequency modulation （FM） signal transferred through track circuit in automatic train control （ATC） system is analyzed. A digital filter with ideal sloping shape in frequency domain is designed for ...The multi-tone frequency modulation （FM） signal transferred through track circuit in automatic train control （ATC） system is analyzed. A digital filter with ideal sloping shape in frequency domain is designed for frequency discrimination. With this filter, the FM signal is converted into AM-FM signal by frequency-to-amplitude conversion. The modulating signal is finally extracted from the envelope of the AM-FM signal. Simulations show that the digital demodulation method could accurately recover the modulating signal in low signal noise ratio （SNR） circumstance, and has good performance in suppressing interference of harmonies of traction current frequency. The feasibility of the proposed method is proved in a hardware system based on SHARC DSP.展开更多
Rail breakage is one of the major safety risks in railway transportation.Because of the large axle weight,high density and large capacity of the heavy-haul railway,the damage to rail caused by heavy-haul train wheels ...Rail breakage is one of the major safety risks in railway transportation.Because of the large axle weight,high density and large capacity of the heavy-haul railway,the damage to rail caused by heavy-haul train wheels will be more serious than that caused by ordinary passenger and cargo trains,resulting in a higher frequency of rail breakage.Taking the Daqin Railway Line as the research object,this paper analyses and discusses rail breakages occurring in interstation tracks and in-station tracks by establishing the ZPW-2000A track circuit calculation model considering the land leakage resistance between the rail line tracks;introduces the defining standards and measurement index of the broken rail coefficient to quantitatively analyse the influence of various influencing factors on the rail breakage inspection performance under the most unfavourable working conditions;and compares the model simulation data,the laboratory model data and the field test results to verify its effectiveness,so as to provide a reference and theoretical basis for the subsequent improvement and solution of the heavy-haul railway rail breakage problem.展开更多
针对压电能量收集中基于传统开路电压法的最大功率点追踪(Maximum Power Point Tracking,MPPT)存在的开路电压(VOC)高,导致有效输入电压范围受限这一问题,提出了一种单周期直接MPPT算法。该算法采用双采样电容两步采样技术,即在两个连...针对压电能量收集中基于传统开路电压法的最大功率点追踪(Maximum Power Point Tracking,MPPT)存在的开路电压(VOC)高,导致有效输入电压范围受限这一问题,提出了一种单周期直接MPPT算法。该算法采用双采样电容两步采样技术,即在两个连续周期内,两次将整流器从输出大电容上断开,并连接到电容值不同且略大于压电源寄生电容的采样电容上,每次半个周期,从而获得两个不同的采样电压。在此基础上,通过建立两次采样电压与最大功率点电压(VMPP)之间的数学模型,拟合出便于电路实现的计算公式,进而求解出VMPP。该算法不仅可以最大化的减小VMPP计算过程中的能量损失,同时还避免了VOC的产生,使得压电能量收集系统的最大输入电压可达CMOS器件的极限工作电压。采用标准0.18μm CMOS工艺完成了压电能量收集芯片的设计。后仿真结果表明:所提出的算法能够实时监测压电源的状态。在压电源发生变化时,仅需一个压电源振动周期即可自适应追踪到新的VMPP,追踪速度快且追踪精度高。当压电源功率在20μW~5 mW范围内变化时,VMPP计算精度达到93%,MPPT精度可达99%以上。展开更多
基金Natural Science Fund of Gansu Province(No.1310RJZA046)
文摘Evaluation of the health state and prediction of the remaining life of the track circuit are important for the safe operation of the equipment of railway signal system.Based on support vector data description(SVDD)and gray prediction,this paper illustrates a method of life prediction for ZPW-2000A track circuit,which combines entropy weight method,SVDD,Mahalanobis distance and negative conversion function to set up a health state assessment model.The model transforms multiple factors affecting the health state into a health index named H to reflect the health state of the equipment.According to H,the life prediction model of ZPW-2000A track circuit equipment is established by means of gray prediction so as to predict the trend of health state of the equipment.The certification of the example shows that the method can visually reflect the health state and effectively predict the remaining life of the equipment.It also provides a theoretical basis to further improve the maintenance and management for ZPW-2000A track circuit.
基金National Natural Science Foundation of China(No.61763023)。
文摘At present,ZPW-2000 track circuit fault diagnosis is artificially analyzed and monitored.Its discrimination method not only is low efficient and takes a long period,but also requires highly experienced personnel to analyze the data.Therefore,we introduce kernel principal component analysis and stacked auto-encoder network(KPCA-SAD)into the fault diagnosis of ZPW-2000 track circuit.According to the working principle and fault characteristics of track circuit,a fault diagnosis model of KPCA-SAE network is established.The relevant parameters of key components recorded in the data collected by field staff are used as the fault feature parameters.The KPCA method is used to reduce the dimension and noise of fault document matrix to avoid information redundancy.The SAE network is trained by the processed fault data.The model parameters are optimized overall by using back propagation(BP)algorithm.The KPCA-SAE model is simulated in Matlab platform and is finally proved to be effective and feasible.Compared with the traditional method of artificially analyzing fault data and other intelligent algorithms,the KPCA-SAE based classifier has higher fault identification accuracy.
文摘The multi-tone frequency modulation （FM） signal transferred through track circuit in automatic train control （ATC） system is analyzed. A digital filter with ideal sloping shape in frequency domain is designed for frequency discrimination. With this filter, the FM signal is converted into AM-FM signal by frequency-to-amplitude conversion. The modulating signal is finally extracted from the envelope of the AM-FM signal. Simulations show that the digital demodulation method could accurately recover the modulating signal in low signal noise ratio （SNR） circumstance, and has good performance in suppressing interference of harmonies of traction current frequency. The feasibility of the proposed method is proved in a hardware system based on SHARC DSP.
文摘Rail breakage is one of the major safety risks in railway transportation.Because of the large axle weight,high density and large capacity of the heavy-haul railway,the damage to rail caused by heavy-haul train wheels will be more serious than that caused by ordinary passenger and cargo trains,resulting in a higher frequency of rail breakage.Taking the Daqin Railway Line as the research object,this paper analyses and discusses rail breakages occurring in interstation tracks and in-station tracks by establishing the ZPW-2000A track circuit calculation model considering the land leakage resistance between the rail line tracks;introduces the defining standards and measurement index of the broken rail coefficient to quantitatively analyse the influence of various influencing factors on the rail breakage inspection performance under the most unfavourable working conditions;and compares the model simulation data,the laboratory model data and the field test results to verify its effectiveness,so as to provide a reference and theoretical basis for the subsequent improvement and solution of the heavy-haul railway rail breakage problem.
文摘针对压电能量收集中基于传统开路电压法的最大功率点追踪(Maximum Power Point Tracking,MPPT)存在的开路电压(VOC)高,导致有效输入电压范围受限这一问题,提出了一种单周期直接MPPT算法。该算法采用双采样电容两步采样技术,即在两个连续周期内,两次将整流器从输出大电容上断开,并连接到电容值不同且略大于压电源寄生电容的采样电容上,每次半个周期,从而获得两个不同的采样电压。在此基础上,通过建立两次采样电压与最大功率点电压(VMPP)之间的数学模型,拟合出便于电路实现的计算公式,进而求解出VMPP。该算法不仅可以最大化的减小VMPP计算过程中的能量损失,同时还避免了VOC的产生,使得压电能量收集系统的最大输入电压可达CMOS器件的极限工作电压。采用标准0.18μm CMOS工艺完成了压电能量收集芯片的设计。后仿真结果表明:所提出的算法能够实时监测压电源的状态。在压电源发生变化时,仅需一个压电源振动周期即可自适应追踪到新的VMPP,追踪速度快且追踪精度高。当压电源功率在20μW~5 mW范围内变化时,VMPP计算精度达到93%,MPPT精度可达99%以上。
