High-SpeedReal-TimeDataAcquisitionSystem Realized by Interleaving/Multiplexing Technique

The interleaving/multiplexing technique was used to realize a 200?MHz real time data acquisition system. Two 100?MHz ADC modules worked parallelly and every ADC plays out data in ping pang fashion. The design improved the system conversion rata to 200?MHz and reduced the speed of data transporting and storing to 50?MHz. The high speed HDPLD and ECL logic parts were used to control system timing and the memory address. The multi layer print board and the shield were used to decrease interference produced by the high speed circuit. The system timing was designed carefully. The interleaving/multiplexing technique could improve the system conversion rata greatly while reducing the speed of external digital interfaces greatly. The design resolved the difficulties in high speed system effectively. The experiment proved the data acquisition system is stable and accurate.

Design and Implementation of a High-Speed Multi-Channel Data Acquisition System

A data acquisition system （DAS） to implement high-speed, real-time and multi-channel data acquisition and store is presented. The control of the system is implemented by the combination of complex programable logic device （CPLD） and digital signal processing （DSP）, the bulk buffer of the system is implemented by the combination of CPLD, DSP, and synchronous dynamic random access memory （SDRAM）, and the data transfer is implemented by the combination of DSP, first in first out （FIFO）, universal serial bus （USB） and USB hub. The system could not only work independently in single-channel mode, but also implement high-speed real-time multi-channel data acquisition system （MCDAS） by the combination of multiple single-channels. The sampling rate and data storage capacity of each channel could reach up to 100 million sampiing per second and 256 MB respectively.

High-speed broadband data acquisition system based on FPGA

A field-programmable gate array(FPGA)based high-speed broadband data acquisition system is designed.The system has a dual channel simultaneous acquisition function.The maximum sampling rate is 500 MSa/s and bandwidth is200 MHz,which solves the large bandwidth,high-speed signal acquisition and processing problems.At present,the data acquisition system is successfully used in broadband receiver test systems.

If real-time route and high-speed data is important,GoTa is vital.

GoTaTM from ZTE is the world’s first CDMA-based system. Now, ZTE proudly introduces its third-generation digital trunking system featuring a centralized dispatch,

If real-time route and high-speed data is important, GoTa is vital.

GoTa TM from ZTE is the world’s first CDMA-based system. Now, ZTE proudly introduces its third-generation digital trunking system featuring

If real-time route and high-speed data is important, GoTa is vital.

Go Tafrom ZTE is the world’s first CDMA-based system. Now, ZTE proudly introduces its third-generation digital trunking system featuring a centralized dispatch,

A power-quality monitoring and assessment system for high-speed railways based on train-network-data center integration

In recent years,with the rapid development of high-speed railways(HSRs),power interruptions or disturbances in traction power supply systems have become increasingly dangerous.However,it is often impossible to detect these faults immediately through single-point monitoring or collecting data after accidents.To coordinate the power quality data of both traction power supply systems(TPSSs)and high-speed trains(HSTs),a monitoring and assessing system is proposed to access the power quality issues on HSRs.By integrating train monitoring,traction substation monitoring and data center,this monitoring system not only realizes the real-time monitoring of operational behaviors for both TPSSs and HSTs,but also conducts a comprehensive assessment of operational quality for train-network systems.Based on a large number of monitoring data,the field measurements show that this real-time monitoring system is effective for monitoring and evaluating a traction-network system.

A Modified Generative Adversarial Network for Fault Diagnosis in High-Speed Train Components with Imbalanced and Heterogeneous Monitoring Data

Data-driven methods are widely considered for fault diagnosis in complex systems.However,in practice,the between-class imbalance due to limited faulty samples may deteriorate their classification performance.To address this issue,synthetic minority methods for enhancing data have been proved to be effective in many applications.Generative adversarial networks(GANs),capable of automatic features extraction,can also be adopted for augmenting the faulty samples.However,the monitoring data of a complex system may include not only continuous signals but also discrete/categorical signals.Since the current GAN methods still have some challenges in handling such heterogeneous monitoring data,a Mixed Dual Discriminator GAN(noted as M-D2GAN)is proposed in this work.In order to render the expanded fault samples more aligned with the real situation and improve the accuracy and robustness of the fault diagnosis model,different types of variables are generated in different ways,including floating-point,integer,categorical,and hierarchical.For effectively considering the class imbalance problem,proper modifications are made to the GAN model,where a normal class discriminator is added.A practical case study concerning the braking system of a high-speed train is carried out to verify the effectiveness of the proposed framework.Compared to the classic GAN,the proposed framework achieves better results with respect to F-measure and G-mean metrics.

Design of high-speed signal acquisition system and analysis of signal integrity

The device is used for the test on the fuze detonating time according to the initial velocity of the projectile and the altitude and speed of enemy aircraft flight. For the special requirements of the high-speed signal acquisition in the process, the characteristics of the measured signal are analyzed. The system is investigated in chip selection, signal transmission, signal processing, signal storage, post-production PCB design, etc. The appropriate measures and solutions which affect the integrity and accuracy of the signal in each process are proposed. The rules for the layout of the device and wiring are made. The result show that the measurement values are accurate without loss of data.

An Optimal Feed Interpolator Based on G^2 Continuous Bézier Curves for High-Speed Machining of Linear Tool Path

A numerical control (NC) tool path of digital CAD model is widely generated as a set of short line segments in machining. However, there are three shortcomings in the linear tool path, such as discontinuities of tangency and curvature, huge number of line segments, and short lengths of line segments. These disadvantages hinder the development of high speed machining. To smooth the linear tool path and improve machining efficiency of short line segments, this paper presents an optimal feed interpolator based on G^2 continuous Bézier curves for the linear tool path. First, the areas suitable for fitting are screened out based on the geometric characteristics of continuous short segments (CSSs). CSSs in every area are compressed and fitted into a G^2 Continuous Bézier curve by using the least square method. Then a series of cubic Bézier curves are generated. However, the junction between adjacent Bézier curves is only G^0 continuous. By adjusting the control points and inserting Bézier transition curves between adjacent Bézier curves, the G^2 continuous tool path is constructed. The fitting error is estimated by the second-order Taylor formula. Without iteration, the fitting algorithm can be implemented in real-time environment. Second, the optimal feed interpolator considering the comprehensive constraints (such as the chord error constraint, the maximum normal acceleration, servo capacity of each axis, etc.) is proposed. Simulation and experiment are conducted. The results shows that the proposed method can generate smooth path, decrease the amount of segments and reduce machining time for machining of linear tool path. The proposed research provides an effective method for high-speed machining of complex 2-D/3-D profiles described by short line segments.

A Utility-Based Buffer Management Policy for Improving Data Dissemination in Opportunistic Networks

In opportunistic networks, most existing buffer management policies including scheduling and passive dropping policies are mainly for routing protocols. In this paper, we proposed a Utility-based Buffer Management strategy(UBM) for data dissemination in opportunistic networks. In UBM, we first design a method of computing the utility values of caching messages according to the interest of nodes and the delivery probability of messages, and then propose an overall buffer management policy based on the utility. UBM driven by receivers completely implements not only caching policies, passive and proactive dropping policies, but also scheduling policies of senders. Simulation results show that, compared with some classical dropping strategies, UBM can obtain higher delivery ratio and lower delay latency by using smaller network cost.

HOTCAP:a new software package for high-speed oscilloscopebased three-dimensional bunch charge and position measurement

A software package to be used in high-speed oscilloscope-basedthree-dimensionalbunch-by-bunch charge and position measurement is presented.The software package takes the pick-up electrode signal waveform recorded by the high-speed oscilloscope as input,and it calculates and outputs the bunch-by-bunch charge and position.In addition to enabling a three-dimensional observation of the motion of each passing bunch on all beam position monitor pick-up electrodes,it offers many additional features such as injection analysis,bunch response function reconstruction,and turn-by-turn beam analysis.The software package has an easy-to-understand graphical user interface and convenient interactive operation,which has been verified on the Windows 10 system.

A spatial decomposition approach for accelerating buffer analysis of vector data

Parallel vector buffer analysis approaches can be classified into 2 types:algorithm-oriented parallel strategy and the data-oriented parallel strategy.These methods do not take its applicability on the existing geographic information systems(GIS)platforms into consideration.In order to address the problem,a spatial decomposition approach for accelerating buffer analysis of vector data is proposed.The relationship between the number of vertices of each feature and the buffer analysis computing time is analyzed to generate computational intensity transformation functions(CITFs).Then,computational intensity grids(CIGs)of polyline and polygon are constructed based on the relative CITFs.Using the corresponding CIGs,a spatial decomposition method for parallel buffer analysis is developed.Based on the computational intensity of the features and the sub-domains generated in the decomposition,the features are averagely assigned within the sub-domains into parallel buffer analysis tasks for load balance.Compared with typical regular domain decomposition methods,the new approach accomplishes greater balanced decomposition of computational intensity for parallel buffer analysis and achieves near-linear speedups.

Statistical delay distribution analysis on high-speed railway trains

The focus of this study is to explore the statis-tical distribution models of high-speed railway (HSR) train delays. Based on actual HSR operational data, the delay causes and their classification, delay frequency, number of affected trains, and space–time delay distributions are discussed. Eleven types of delay events are classified, and a detailed analysis of delay distribution for each classifica-tion is presented. Models of delay probability delay prob-ability distribution for each cause are proposed. Different distribution functions, including the lognormal, exponen-tial, gamma, uniform, logistic, and normal distribution, were selected to estimate and model delay patterns. The most appropriate distribution, which can approximate the delay duration corresponding to each cause, is derived. Subsequently, the Kolmogorov–Smirnov (K–S) test was used to test the goodness of fit of different train delay distribution models and the associated parameter values. The test results show that the distribution of the test data is consistent with that of the selected models. The fitting distribution models show the execution effect of the timetable and help in finding out the potential conflicts in real-time train operations.

A fault prediction method for catenary of high-speed rails based on meteorological conditions

Fault frequency of catenary is related to meteo-rological conditions. In this work, based on the historical data, catenary fault frequency and weather-related fault rate are introduced to analyse the correlation between catenary faults and meteorological conditions, and further the effect of meteorological conditions on catenary oper-ation. Moreover, machine learning is used for catenary fault prediction. As with the single decision tree, only a small number of training samples can be classified cor-rectly by each weak classifier, the AdaBoost algorithm is adopted to adjust the weights of misclassified samples and weak classifiers, and train multiple weak classifiers. Finally, the weak classifiers are combined to construct a strong classifier, with which the final prediction result is obtained. In order to validate the prediction method, an example is provided based on the historical data from a railway bureau of China. The result shows that the mapping relation between meteorological conditions and catenary faults can be established accurately by AdaBoost algorithm. The AdaBoost algorithm can accurately predict a catenary fault if the meteorological conditions are provided.

The Design and Implementation of the Data Buffer Unit in an Artificial intelligence Computer ITM-1

This paper describes the function,structure and working status of the data buffer unitDBU,one of the most important functional units on ITM-1.It also discusses DBU’s supportto the multiprocessor system and Prolog language.

基于环境中移动运输代理的传感器网络建模

针对大型稀疏传感器网络中的数据获取,本文提出了一种利用环境中普遍存在的移动代理来连接稀疏传感器的网络体系结构和一种2-维网格随机游走分析模型;提出的传感器网络模型由3个抽象层构成,即由无线传感器构成的底层、由各种运输代理构成的中间层和由接入点/中央存储库构成的顶层。具体实现原理是位于中间层的移动运输代理从底层分布的无线传感器收集数据并缓冲数据,然后经过游走运输,最后将从底层的无线传感器收集的数据交付到顶层必要的接入点进行必要的存储和处理,从而实现整个传感器网络的数据获取;理论分析和仿真实验结果表明,提出的基于移动运输代理的传感器网络模型不仅具有较好的鲁棒性和可扩展性,而且相比于基站网络模型和Ad-hoc网络模型,在传感器功率消耗、数据成功率和基础设施投入成本方面有明显的优势。

智能网联汽车的高精地图数据交互模式

随着自动驾驶技术的发展,传统的地图服务已经不能满足以机器为主体的自动驾驶车辆的需要。具有更高精度、更多要素、更快更新频率的高精地图成为自动驾驶车辆的关键。不同来源数据之间的交互是高精地图用于自动驾驶导航决策的保证。针对智能网联汽车系统中高精地图的数据交互问题,本文首先对相关的研究进行了分析,依据高精地图的数据内容和数据来源对智能网联汽车中的高精地图数据进行再组织;然后详细阐述了基于车-路-云三方的高精地图数据交互的内容和交互机制,形成一个适用于智能网联汽车的高精地图数据交互模式;最后在仿真环境下对设计的数据交互模式进行了验证。

Protocol Buffers在即时通讯系统中的应用研究

即时通讯系统已经广泛应用在人们的生活中,随着用户数量的增长,计算机设备在网络中传输的数据量越来越大。由于网络中的数据传输是非结构化的,因此需要数据的序列化与逆序列化方法来实现网络数据到可读数据的转换。基于即时通讯系统对于数据的实时性需求,提出了使用Protocol Buffers作为系统的序列化与逆序列化的手段,并且将Protocol Buffers与目前几种比较主流的数据序列化方法进行了对比。

基于Data Window的数据管理与更新机制的研究与应用

介绍了DataWindow控件管理数据的基本原理和处理流程 ,并深入阐述了DataWindow对象的四个缓冲区 (PrimaryBuffer,DeleteBuffer,FilterBuffer,OriginalBuffer)的功能和相互关系 ,以及它们之间是如何各司其职 ,协作完成数据的增加、删除、修改 ,并把结果提交给数据库管理系统的基本原理和过程。最后讨论了DataWindow对象的数据更新机制在编程中的一些应用 。