淮阴工学院毕业设计(论文)外文资料翻译系（院）：电子与电气工程学院专业：自动化姓名：洪波学号：1061204214外文出处：/index/VK20202146155322.pdf(用外文写)附件： 1.外文资料翻译译文；2.外文原文。
指导教师评语：该生所选材料与毕业设计课题比较相近，翻译质量较好，语句较通顺，字数符合要求，如果能够加深些内容就好了，符合设计要求。
签名：年月日附件1：外文资料翻译译文基于CAN总线的分布式数据采集与分析系统摘要：关于大型核物理设置分布式远程控制系统的目的是收集、存储和分析数据以及检测设备运行，通过WEB对其进行可视化。
系统使用CAN工业数据传送网络和DeviceNet高层协议。
其硬件部分是转换成频率信号的检测设备，并通过CAN 网络传输他们的数字形式到主机电脑。
该软件实现屏蔽，以保证协议栈的数据采集、传输。
用户界面是基于动态网页。
服务器脚本执行其形成和数据的图形可视化。
该系统用于监测BOREXINO中微子探测器（意大利）的光电倍增管黑暗噪音。
一、硬件部分系统的结构体系在工业系统，需要从很多模拟传感器组织数据采集，其中模拟参数转换成频率信号最合适4 - 20 mA的电流和频率接口。
这些物理参数随温度、电压、压力转换成可以轻易在传输过程中，以方便的频率信号进行进一步的处理。
这在技术上较为简单，更便宜，以确保大型分布式系统在电偶解耦多通道数据采集的所需。
因此，通用变频器在输入的建筑设计的模块，其中有几个是具有测量频率数的投入。
这些模块共有一个统一的工业通讯网络，确保了建设一个分层分布式系统，使接近传感器传感装置的频率输出。
在大量现有工业网络中，选择控制器区域网络（CAN）总线，便于我们系统模块的链接。
鉴于自身的特色（按位仲裁，差分信号传输模式，高度可靠的错误处理和错误逮捕算法），CAN工业网络很适合创建分布式数据采集、监测和控制系统。
CAN总线为数据传输，具有高速度(1 Mbit / s)和很强的抗噪能力。
CAN的灵活性是指CAN模块可以简单连接到总线和断开；在这种情况下，组件的总数是不受限于低级协议。
CAN2.0B最新标准描述只有两个低层次的ISO / OSI网络参考模型：（i）物理层和（ii）数据自动传输装置层。
为建立数据传输系统，它需要一个或另一个高(用于应用)水平的协议。
这个协议，方便使用DeviceNet或CanOpen协议，因为他们有一个开放的规格和适当的国际标准设计并支持他们。
DeviceNet协议被使用在黑暗的环境噪声中研制BOREXINO探测器的监测系统。
建筑系统的特色是数据采集系统划分成任意数量独立子系统的可能性。
在每个子系统中，多达256个频道，可衡量几个独立控制器，频率表，以及它们之间的通信是由DeviceNet协议的支持。
在这种情况下，每个子系统的控制器可以有不同的技术特点（通道数和测量频带），这取决于特定的物理问题。
然而，他们都有一个共同的建筑和同一简报的系统。
目前，使用8 、16 、64米的通道频率。
这是假设所有的传感器位于一个地区的设置是连接到一个模块。
每个频率计有CAN控制器，并作为从器件连接到CAN网络。
主设备的数据采集子系统控制计算机。
各个子系统的控制是独立的网络。
从控制计算机数据到达服务器，并把它们储藏和发送到客户站供其查询。
在开发该系统，我们假设相对缓慢变化的数据应该是衡量，即受监视的典型参数变化时间应该是1秒或以上。
在这种情况下，测得的频率值由10赫兹到0.5兆赫。
测量的频率为1赫兹在经营范围中边界；在此范围的边界，误差≤10％。
标准模块转换器通过CAN总线连接，可添加到系统中，以测量频率和其他物理参数。
该系统是通过增加模块使用标准的高级别CAN总线网络协议。
创建的系统实现了经典的三个层次的数据控制和采集系统各：（1）对象的访问级别，（2）管制站的水平，（3）支持图形界面的服务水平。
这是大型分布式系统的最佳架构。
此外，它允许一个规模相适应的数据采集系统，对以不同类型的大型物质设置。
这个独立的控制器用于允许一个逻辑组传感器根据自己的位置和功能。
因此，该系统可以被视为一个平台开发类似系统。
二、软件部分系统的结构体系我们考虑一个一般方框图系统软件的两个子系统的控制。
本软件为系统的监测、数据采集、基于多级方案分析；在特殊情况下，它是可能在这四个层面来区分：(1)硬件，(2)数据采集，(3) 数据处理及(4)数据展现的水平。
此外，它可以区分六子系统软件的功能：(1)数据采集子系统、(2)物理数据仿真系统；(3)数据处理系统，(4)数据存储子系统，(5)状态监测(可视化)子系统，(6)离线分析子系统。
两个客户端服务器链接用于传输系统之间的水平数据。
一个是位于层次之间的数据采集，其中服务器是TCP / IP守护进程模块和数据处理水平，其中客户端是数据服务器程序模块。
在其他环节之间的数据处理，其中服务器是数据服务器模块，数据编制水平，其中客户端是可视化子系统。
交换数据的客户端和服务器端之间通过标准的inquiryanswer原则插槽机制。
在适当时由系统执行数据采集、处理和演示水平物理隔离，分离的数据采集和分析过程的时间，也为成分的负载平衡。
我们考虑一个方案的操作和相互作用的各种模块的系统。
在数据采集方式的信息的前提下，由许多不同传感器参数组合的几个测量模块统一的CAN网络。
因此，这是数据采集子系统。
这些数据通过数据采集模块(DeviceNet主站)都写进了分布式存储空间。
如果安装不在工作模式，即分布式控制系统是关闭的，数据可以到从模拟到模块的分布式的内存空间。
仿真模块用于调试系统。
它允许一个模拟频繁和设置紧急状态，也就是说，它是用于检查监测系统的行为是否足够使用。
当模拟模块开始运行，它会检查是否基本数据采集系统运行或不和，只有当它关闭时，模拟数据写入分布内存空间。
该仿真系统接口部分允许指定的网上通过舒适的图形界面进行每个通道的模拟。
数据通过数据传输模块的分布式存储空间（TCP / IP协议守护程序）收集，模块提供数据的数据处理模块（数据服务器）。
数据传输模块发出采集的数据可以从每个频率计分系统和子系统同时进行所有操作。
这个数据调查发生的计时器时间，和审讯周期（T = 0.5秒）是典型的数据到达时间（T2 = 1秒）的1/2。
数据处理模块的数据包到数据库（DB）和暂时存储数据的频率。
临时存储空间的布置，是一个环形缓冲区，允许正在运行的可视化模块中的临时窗口模式的实现。
缓冲区的大小可以调整到所需史前长度可视化模块的要求。
包装子系统的DB数据执行数据初加工，其参照绝对时间，如果有可能，他们的压缩、包装到结构形式DB。
在收到的数据格式成为一个非物质的一种物质形式（频率，温度和电压转换）再存储和传输到Web客户端。
这些数据被保存在该方案的定期运行过程中，并在必要时，数据存储可以在测试模式下被禁用。
这个数据采集和模拟子系统和Dataserver模块都在Linux的操作系统下使用ANSI C语言写。
数据可视化显示数据的频率模块的频率计通道是在线模式。
该子系统将显示所有的渠道和设备的国家，在这种情况下，要求在DB状态的监视和校验设备整合状态的频率计通道到一个真正的物理设备。
调查数据分析模块生成的数据库管理系统（DBMS），以便得到关于在指定时间监测参数信息。
数据可视化和分析模块写入通过使用Perl和PHP语言.模块是通过使用Perl和PHP语言编写的CGI脚本。
三、结论软件和硬件组件，形成一个为我们开发建设的监控系统，包括数据采集和分析等系统，并以此为基础的完整平台可以确保及时监测大型核物质设置，包括及时对故障研设备响应.这个平台结构使人们能轻松扩展、更新和扩大在此基础上创建的系统的功能。
利用黑暗中噪声BOREXINO探测器监测系统的经验，使人们将其看作一个建立在基础的大型分布式物理设置在线监测系统平台。
附件2：外文原文（复印件）A Distributed Data AcquisitionAnd Analysis System Based on a CAN BusAbstract—A distributed remote-control system for large nuclear physical setups is intended to collect, store,and analyze data arriving from detecting devices and to visualize them via the WEB. The system uses the CAN industrial data transmission network and the DeviceNet high-level protocol. The hardware part is the set of controllers,which convert signals of the detecting devices into a frequency and transmit them in the digital form via the CAN network to the host computer. The software realizes the DeviceNet protocol stack, which ensures the data acquisition and transmission. The user interface is based on dynamic WEB pages. Server scripts carry out their formation and graphical visualization of data. The system is used for monitoring dark noises of photomultiplier tubes in the BOREXINO neutrino detector (Italy).ARCHITECTURE OF THE HARDW ARE PART OF THE SYSTEMIn industrial systems, where it is necessary to organize the data acquisition from many analog sensors, the most suitable are 4- to 20-mA current and frequency interfaces in which the analog parameter is at once generated or converted into the frequency signal. Such physical parameters as temperature, voltage, and pressure can be easily converted into frequency, ensuring convenience during transmission of signals for further processing. When the signal is transmitted in frequency form, it is technically simpler and cheaper to ensure the galvanic decoupling required for the multichannel data acquisition in large distributed systems. Thus, the universal input converter in the proposed architectural design is the module, which has several inputs for measuring frequency. The modules are unified by an industrial communication network, ensuring a possibility of constructing a hierarchical distributed system and bringing the sensing devices closer to sensors with the frequency output.Of a great number of existing industrial networks,the Controller Area Network (CAN) bus was selected in order to connect the modules of our system. In view of its own special features (bitwise arbitration, differential signal transmission mode, andhighly reliable algorithm of error handling and bug arrest), the CAN industrial network is well suitable for creating distributed data acquisition, monitoring and control systems. The CAN bus is characterized by a high data transmission speed (up to 1 Mbit/s) and high noise immunity. The CAN flexibility is attained due to the simple connection of CAN modules to the bus and disconnection from it;in this case, the total number of the modules is not limited by low-level protocol.The up-to-date CAN 2.0B standard [4] describes only two lower layers of theISO/OSI reference network model [5]: (i) the physical layer and (ii) the data link layer. For building the data transmission system, it is required that one or another high (applied)-level protocol be used. As this protocol, it is convenient to use DeviceNet or CanOpen protocols, since they have an open specification and appropriate international standards have been designed and supported for them. The DeviceNet protocol is used in the developed dark noise monitoring system of the BOREXINO detector [6].The architectural special feature of the system is the possibility of dividing the data acquisition system into an arbitrary number of independent subsystems. In each subsystem, up to 256 frequency channels can be measured by several independent controllers–frequency meters, and communication between them is supported by the DeviceNet protocol. In this case, the controllers for each subsystem can have different technical characteristics (the number of channels and measured frequency band), depending on the specific physical problem. However, they have a common architecture and the same presentation in the system. At present, 8-, 16-, and 64-channel frequency meters are used. It is assumed that all sensors located in one region of the monitored setup are connected to one module. Each frequency meter has a CAN controller and is connected to the CAN network as a slave device. The master device is the control computer of the data acquisition subsystem.Each subsystem of controllers is the independent CAN network. Data from the control computer arrive at the server, where they are stored and issued in accordance with inquiries of client stations.While developing the system, we assumed that relatively slowly varying data should have been measured, i.e., that the typical variation time of the monitored parametershould be 1 s or over. In this case, the measured frequency value can vary from 10 Hz to 0.5 MHz. The frequency is measured with an accuracy of 1 Hz in the middle of the operating range; at the borders of this range, the error is ≤10%.Standard modules–converters connected via the CAN bus can be added into the system in order to measure physical parameters other than frequency. The system is expanded by adding modules using standard high-level protocols of the CAN-bus network.The created system realizes all levels of classical three-level data control and acquisition system [7]:(i) object access level, (ii) control station level, and (iii) service level for supporting the graphical interface.It is this architecture that suits distributed and large systems best. In addition, it allows one to scale and adapt the data acquisition system to large physical setups of different types. The independent groups of controllers used allow one to logically group sensors according to their location or function. Therefore, the system can be considered a platform for developing similar systems.ARCHITECTURE OF THE SOFTW ARE PART OF THE SYSTEMWe consider a general block diagram of the system software for two subsystems of controllers. The software for the system of monitoring, data acquisition, and analysis is based on a multilevel scheme; in particular, it is possible to distinguish four levels in it: (i) hardware, (ii) data acquisition, (iii) data processing, and (iv) data presentation levels.In addition, it is possible to distinguish six functional subsystems in the software: (i) data acquisition subsystem, (ii) physical data simulation subsystem; (iii) data processing subsystem, (iv) data storage subsystem,(v) status monitoring (visualization) subsystem,and (vi) off-line analysis subsystem.Two client–server links are used to transmit data between levels of the system. One is located between the data acquisition level, where the server is a TCP/IP Daemon module, and the data processing level, where the client is the Dataserver program module. The other link is located between the data processing level, where the server is the Dataserver module, and the data presentation level, where the client is the visualization subsystem.Data are exchanged between the client and server via a standard socket mechanism on the inquiryanswer principle.The data acquisition, processing, and presentation levels are physically separated and located in different computers due to the nonuniformity of problems executed by the system, the separation of data acquisition and analysis processes in time, and also for balancing the loads on components.We consider a scheme of operation and interaction of various modules of the system.In the data acquisition mode, the information on the monitored parameters arrives from many various sensors grouped by means of several measuring modules and unified by the CAN network. Hence, the data acquisition subsystem is distributed.These data are written into the distributed memory space via the data acquisition module (DeviceNet Master). If the setup is not in the working mode, i.e., the distributed controller system is off, the data can arrive into the distributed memory space from the simulation module.The simulation module is intended for debugging the system. It allows one to simulate infrequent and emergency states of the setup; i.e., it is used for checking the adequacy of the monitoring system behavior. When the simulation module starts operating, it checks whether the basic data acquisition system is operating or not and, only if it is off, simulated data are written into the distributed memory space. The interface part of the simulation system allows one to specify online the behavior of each simulated channel via the comfortable graphical interface.Data are collected by the data transmission module (TCP/IP Daemon) from the distributed memory space.In response to inquiries, the module delivers data to the data processing module (Dataserver). The data transmission module can issue data acquired both from each individual frequency meter subsystem and from all operating subsystems simultaneously. The data inquiry takes place in accordance with the timer, and the interrogation period ( T = 0.5 s) is equal to 1/2 of the typical data arrival time ( T = 1 s).The data processing module packs data into the database (DB) and temporarily stores data on frequencies. The temporary storage space is arranged as a ring buffer,permitting the realization of the running temporary window mode in the visualization module. The buffer size can be adjusted to the required prehistory length requested by the visualization module. The DB data packing subsystem executes primary processing of data; their referencing to the absolute time; if it is possible, their compression; and packing into the DB in structured form. Data received in a nonphysical format are converted into a physical form (frequency, temperature,and voltage) before storage and transmission to WEB clients. The data are saved periodically during operation of the program, and, if necessary, the data saving can be disabled in the test mode.The data acquisition and simulation subsystems and the Dataserver module are written in language ANSI C for use in the Linux operational system.The data visualization module displays data on frequencies in frequency meter channels in an online mode. This subsystem displays the states of all the channels and devices, in this case, requesting in the DB the status of the equipment and verifying the conformity of the status of the frequency meter channel to a real physical device.The data analysis module generates inquiries for the database management system (DBMS) in order to receive information on the monitored parameter over the specified time. The data visualization and analysis modules are written by using CGI scripts in the Perl and PHP languages.modules are written by using CGI scripts in the Perl and PHP languages.CONCLUSIONThe software and hardware components that we developed form a complete platform for building the systems for monitoring, data acquisition, and analysis.The systems based on it are capable of ensuring prompt monitoring of the large nuclear physical setup, including timely response to malfunctions in the equipment.The platform structure allows one to easily scale,update, and expand the functional capabilities of the systems created on its basis. The experience of using the dark noise monitoring system of the BOREXINO detector allows one to consider the platform as a basis for building distributed online monitoring systems for large physical setups.。