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.

The Interdisciplinary Research of Big Data and Wireless Channel: A Cluster-Nuclei Based Channel Model

Recently,internet stimulates the explosive progress of knowledge discovery in big volume data resource,to dig the valuable and hidden rules by computing.Simultaneously,the wireless channel measurement data reveals big volume feature,considering the massive antennas,huge bandwidth and versatile application scenarios.This article firstly presents a comprehensive survey of channel measurement and modeling research for mobile communication,especially for 5th Generation(5G) and beyond.Considering the big data research progress,then a cluster-nuclei based model is proposed,which takes advantages of both the stochastical model and deterministic model.The novel model has low complexity with the limited number of cluster-nuclei while the cluster-nuclei has the physical mapping to real propagation objects.Combining the channel properties variation principles with antenna size,frequency,mobility and scenario dug from the channel data,the proposed model can be expanded in versatile application to support future mobile research.

Robust and Efficient Data Transmission over Noisy Communication Channels Using Stacked and Denoising Autoencoders

We study the effects of quantization and additive white Gaussian noise(AWGN) in transmitting latent representations of images over a noisy communication channel. The latent representations are obtained using autoencoders(AEs). We analyze image reconstruction and classification performance for different channel noise powers, latent vector sizes, and number of quantization bits used for the latent variables as well as AEs’ parameters. The results show that the digital transmission of latent representations using conventional AEs alone is extremely vulnerable to channel noise and quantization effects. We then propose a combination of basic AE and a denoising autoencoder(DAE) to denoise the corrupted latent vectors at the receiver. This approach demonstrates robustness against channel noise and quantization effects and enables a significant improvement in image reconstruction and classification performance particularly in adverse scenarios with high noise powers and significant quantization effects.

Sampled-Data Consensus Control of MUSV Systems with Channel Fading and Transmission Delay

This paper studies sampled-data consensus control of a collection of unmanned surface vehicles(USV)operating in network environments with fading channels and time-varying transmission delay.The channel fading is modeled as each independent stochastic process whose probability distribution is known.By considering the effects of channel fading and transmission delay from sampler to the controller,a new MUSV system model is formulated in the framework of network.With the novel established model,stability analysis is given at first,then the sampled-data consensus controller is designed,which also extends to the robust control with wave-induced disturbance.The effectiveness of the presented method is demonstrated by numerical simulation.

Channel Estimation and Data Transmission in Massive MIMO TDD Systems

This paper mainly elaborates the studies of channel estimation and downlink data transmission in Massive MIMO. As there are different types of interference in single-cell and multi-cell systems, this paper establishes different models for them separately. In terms of uplink training, for getting channel state information, we introduce LS and MMSE channel estimation algorithms and make a comparison between them. At the same time, the problem of pilot contamination is solved by cell classification and pilot identification. Next, this paper defines mathematical models for downlink data transmission. We use pre-coding methods (including Zero-forcing and Maximal Ratio Combining schemes) and optimize power distribution to improve channel capacity and transmission rate. Furthermore, this paper provides numerical results to show the simulation performance in both single-cell and multi-cell systems and extends to prospects in the future.

多通道航磁同步数据采集系统的研制

针对无人机多传感器矢量磁测补偿系统,研制了一套小体积、低功耗的多通道数据同步采集系统。该系统采用模拟采集和控制部分分开设计的方法。模拟采集部分基于STM32处理器STM32F103C8T6,集成了9通道24位高精度的模数转换芯片ADS1255、倾角和温度传感器,能够实现9通道数据的同步采集、飞行载体的倾角数据和温度数据的获取。控制部分基于32位ARM低功耗处理器S3C2416和嵌入式LINUX系统,完成了数据实时采集、SD卡存储、GNSS同步校时和网络通信等功能,并具有功耗低、体积小的特点,满足了机载数据采集系统特定的应用需求。

中国数字地震台网数据管理中心Y2K问题的解决方法及getdata_new软件

叙述了中国数字地震台网 (CDSN)数据管理中心 (DMC)的计算机 2 0 0 0年问题 (Y2 K)的解决情况 ,着重介绍了为解决 Y2 K问题而编制的 getdata new软件的功能 ,特点 ,结构和工作原理 ,并结合几个典型实例 ,对用法和应用情况进行说明。另外 ,本文对 getdata new所涉及的部分 ASL的程序也作了简介。

Static CSI Extraction and Application in the Tomographic Channel Model

In this paper, the statistical properties of parameters of each path in wireless channel models are analyzed to prove that there is the static part in channel state information(CSI) which can be extracted from huge amounts of CSI data. Based on the analysis, the concept of the Tomographic Channel Model(TCM) is presented. With cluster algorithms, the static CSI database can be built in an off-line manner. The static CSI database can provide prior information to help pilot design to reduce overhead and improve accuracy in channel estimation. A new CSI prediction method and a new channel estimation method between different frequency bands are introduced based on the static CSI database. Using measurement data, the performance of the new channel prediction method is compared with that of the Auto Regression(AR) predictor. The results indicate that the prediction range of the new method is better than that of the AR method and the new method can predict with fewer pilot symbols. Using measurement data, the new channel estimation method between different frequency bands can estimate the CSI of one frequency band based on known CSI of another frequency band without any feedback.

A New Infrared Atmospheric Sounding Interferometer Channel Selection and Assessment of Its Impact on Met Office NWP Forecasts

A new set of Infrared Atmospheric Sounding Interferometer （IASI） channels was re-selected from 314 EUMETSAT channels. In selecting channels, we calculated the impact of the individually added channel on the improvement in the analysis outputs from a one-dimensional variational analysis （1D-Var） for the Unified Model （UM） data assimilation system at the Met Office, using the channel score index （CSI） as a figure of merit. Then, 200 channels were selected in order by counting each individual channel＇s CSI contribution. Compared with the operationally used 183 channels for the UM at the Met Office, the new set shares 149 channels, while the other 51 channels are new. Also examined is the selection from the entropy reduction method with the same 1D-Var approach, Results suggest that channel selection can be made in a more objective fashion using the proposed CSI method. This is because the most important channels can be selected across the whole IASI observation spectrum. In the experimental trial runs using the UM global assimilation system, the new channels had an overall neutral impact in terms of improvement in forecasts, as compared with results from the operational channels. However, upper-tropospheric moist biases shown in the control run with operational channels were significantly reduced in the experimental trial with the newly selected channels. The reduction of moist biases was mainly due to the additional water vapor channels, which are sensitive to the upper-tropospheric water vapor.

Geologic-Geophysical Indicators of the Deep Structure of Zones of Geothermal Anomalies for Allocation of Channels of the Deep Heat and Mass Transfer

On the basis of the analysis of field thermogeochemical data along abnormal zones of a thermal stream in the Bukhara-Khiva, oil-and-gas region of the Turan (Tegermen, Chagakul, Shimoly Alat, Beshtepa) was succeeded to obtain important data on a deep structure of sites. Data of gas-chemical and geothermal observations show about confinedness of abnormal concentration of methane to zones of the increased values of the temperature field the measured values of temperatures (Tegermen Square and others). On geoelectric section mines 2-D of inversion of the MT-field depth of 4000 m are lower, among very high-resistance the chemogenic and carbonate deposits of the Paleozoic is traced the subvertical carrying-out abnormal zone. This zone is identified as the channel of a deep heat and mass transfer with which hydrocarbon (HC) deposits are connected. It is shown that electro-investigation when using a geophysical complex can and has to become “advancing” at exploration by oil and gas.

Establishment of the Secure Channel between Broker Nodes in Pub/Sub System

The paper mainly discusses the integrity of the forwarded subscription message guaranteed by secure channel which encrypted in data communication by using data encryption standard （DES） algorithm and chaos code algorithm between broker nodes in the routing process of the contentbased publish/subscribe system. It analyzes the security of the secure channel encrypted with data communication by DES algorithm and chaos code algorithm, and finds out the secure channel can be easily attacked by known plain text. Therefore, the paper proposes the improved algorithm of message encryption and authentication, combining encryption and the generation of the message authentication code together to finish scanning at one time, which enhances both the secure degree and running efficiency. This secure channel system has a certain reference value to the pub/sub system requiring highly communication security.

混合数据驱动的轻量化YOLOv5故障选线方法

针对传统选线方法精度低、实时性差、易受噪声干扰的问题,提出一种混合数据驱动的轻量化YOLOv5选线方法,简记为MSE-YOLOv5。首先,以零序电流作为区分故障线路与非故障线路的判断依据,为了增强二者间数据对比差异性,利用小波变换将零序电流信号映射为二维时频图;其次,为了扩充样本数量,利用搭建的小电流接地系统仿真模型,通过改变故障点位置、初相位以及接地电阻等参数生成仿真数据,与真实数据构成混合数据集;然后,为了减少选线时背景噪声对微弱故障信号特征的影响,在所搭建检测网络的颈部网络中引入通道注意力模块,从而增强故障特征的表达能力;最后,为了提高选线实时性,在网络中引入轻量化网络以减少其参数量与运算量。为了验证所提出方法的优势,利用某变电站真实故障数据进行测试,并与4种经典算法进行比较。结果表明:所提混合数据驱动的轻量化YOLOv5故障选线方法具有较高精度,其选线精度可达95.2%,即使在噪声干扰条件下,选线精度依然可以保持在90%以上;具有更轻的体量及更快的选线速度,参数量下降至原网络的1/5,计算量下降至1/7,检测速度可达7.7 ms。因此,混合数据驱动的轻量化YOLOv5故障选线方法具有体量小、速度快、精度高的优点,有利于后期将其部署到现场设备中。

基于多模态数据融合的改进中尺度涡检测模型

提出一种基于多模态数据融合的改进中尺度涡检测模型。该模型以海平面高度数据为基础,首次将融合表层海温数据扩展为融合多深度层海温数据;将海温数据的深度层作为通道,嵌入通道注意力机制,使得模型能够关注于海水温度数据中最具有区分度的深度层;模型在编码及解码过程中采用残差学习单元,在加深网络深度的同时,更好地拟合激活函数,缓解训练问题,以提高模型的检测准确率。以中国南海部分海域为例开展实验验证,结果表明该中尺度涡检测模型准确率达到93.62%,模型具备有效性和可靠性。

基于FPGA的多通道高速串行数据采集系统设计

针对卫星导航信号抗干扰领域中进行高精度高速多通道数据采集的需要,系统采用ADI公司的16位高速串行AD转换芯片AD9653,完成模数转换,其转换精度可达16比特,转换速率最高为125MSPS。分析AD9653的高速串行数据接口特点,采用Xilinx公司的Kintex-7系列FPGA提供的片同步技术,进行位时钟自适应相位校准和数据帧调整研究,保证了高速串行数据传输的稳定性与正确性。采用内部FIFO数据缓存的方式实现多通道数据的片内同步以保证后续抗干扰算法的正确处理。研究结果表明,使用该方法进行高速串行数据采集时系统稳定可靠、正确无误。为多通道高速串行数据采集提供了一种切实可行的解决方案,对类似需求的数据采集系统具有一定的参考价值。

Study on Mandatory Access Control in a Secure Database Management System

This paper proposes a security policy model for mandatory access control in class B1 database management system whose level of labeling is tuple. The relation hierarchical data model is extended to multilevel relation hierarchical data model. Based on the multilevel relation hierarchical data model, the concept of upper lower layer relational integrity is presented after we analyze and eliminate the covert channels caused by the database integrity. Two SQL statements are extended to process polyinstantiation in the multilevel secure environment. The system is based on the multilevel relation hierarchical data model and is capable of integratively storing and manipulating multilevel complicated objects ( e.g., multilevel spatial data) and multilevel conventional data ( e.g., integer, real number and character string).

一种宽带非线性信道校正方法

针对高速数传解调器接收宽带高阶调制信号时因信道非线性导致的性能恶化问题,提出一种基于两层自适应均衡网络的非线性信道校正方法。该方法先利用递归最小二乘法获得Volterra非线性前置校正系数,再利用自适应基带均衡器消除信道的剩余影响,以提升解调器的捕获跟踪能力,并在高速数传解调器工程应用中实现2.4 Gb/s 16QAM信号的稳定接收。

随机通道扰动的图像数据增强方法

数据增强中遮挡仿真方法将输入图像随机裁剪的区域像素全部置零,会擦除有效纹理特征,导致网络泛化能力欠佳。因此,提出一种随机通道扰动的图像数据增强方法(ChannelCut)。ChannelCut方法包括Channel-Cut1和ChannelCut2两种方法。在输入图像上随机选取三个方形区域,并且对输入图像进行通道分离,得到三个通道图像;ChannelCut1方法在三个通道图像上分别选取一个方形区域将其像素置零,且三个通道选择的区域互不相同;ChannelCut2方法保留ChannelCut1方法中选取的方形区域像素,并将每个通道中剩余两个方形区域的像素置零;将两种方法处理后的三个通道图像分别进行合并,得到两种随机通道扰动图像。将所提方法融合到Resnet18、ShuffleNet V2、MobileNet V3等CNN模型中,并在CIFAR-10、Imagenette等五个数据集上开展实验。该方法在五个数据集上的分类准确率均优于主流方法,显著提高了基线模型的性能;在细粒度图像分类中更占有优势;在时间性能上优于使用强化学习的自动数据增强类型方法。该方法能够不同程度地保留图像纹理特征,丰富图像多样性,具有较强的通用性和有效性,显著地提高卷积神经网络模型的鲁棒性和泛化性。

基于扩展现实的航空噪声数据模拟系统开发

该文是基于扩展现实技术提出的各种机型在静态和起飞状态的噪声数据模拟系统。即在虚拟场景中实现各种机型的静态试车和起飞程序,同时使用实际机型的噪声记录作为噪声源,并使用头戴显示器以双声通道实现可听化,呈现出噪声数据的可听化和在虚拟环境中的可视化。系统将使用经验公式处理数据,合成起飞状态的噪声,协助噪声适航审定程序进程更有效的进行,有利于相关部门根据对环境保护的要求,制定出航空噪声的适航规章和控制标准。

5G新通话研究与应用

本文深入阐述5G新通话数据通道Data Channel的构建,特别是在网络全流程中,详细描述不同的呼叫阶段建立的方法、释放、终结流程,对语音业务演进进行了前瞻性深入研究。本文阐述了IMS网络演进方向,开拓了行业市场新蓝海,描绘了丰富用户业务体验的前景,也阐述了分阶段开展、实现5G新通话的途径,进一步阐明数据通道工作流程,详细描述在通话时及通话中,终端和网络侧建立数据通道的信令交互流程,最后列举了2个典型应用,为提升用户交互式、沉浸式新体验,进一步拓展应用提供借鉴模板、参考思路。

基于LabVIEW的风电主轴承螺栓预紧力监测系统

针对大型风电主轴承容易产生轴向振动故障问题,基于端盖螺栓预紧力的变化特性,本文拟开发一款螺栓预紧力采集监测系统。该系统采用一种嵌入分布式的垫片压力传感器测量方法,以DH5902N数据采集卡和计算机为硬件,实现螺栓预紧力数据采集和分析。构建应用于风电机主轴承的压力传感器检测模型,通过建立基于传感器数据测量的螺栓预紧力校正算法,实现风电机主轴承轴向受力检测。选用LabVIEW作为软件开发平台,实现多通道数据采集显示与灯光报警等功能,最终实现对风电主轴承的受力状态监测。