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Service-oriented architecture of adaptive, intelligent data acquisition and processing systems for long-pulse fusion experiments

机译:面向服务的自适应,智能数据采集和处理系统的体系结构,用于长脉冲融合实验

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摘要

The data acquisition systems used in long-pulse fusion experiments need to implement data reduction and pattern recognition algorithms in real time. In order to accomplish these operations, it is essential to employ software tools that allow for hot swap capabilities throughout the temporal evolution of the experiments. This is very important because processing needs are not equal during different phases of the experiment. The intelligent test and measurement system (ITMS) developed by UPM and CIEMAT is an example of a technology for implementing scalable data acquisition and processing systems based on PXI and CompactPCI hardware. In the ITMS platform, a set of software tools allows the user to define the processing algorithms associated with the different experimental phases using state machines driven by software events. These state machines are specified using the State Chart XML (SCXML) language. The software tools are developed using JAVA, JINI, an SCXML engine and several LabVIEW applications. Within this schema, it is possible to execute data acquisition and processing applications in an adaptive way. The power of SCXML semantics and the ability to work with XML user-defined data types allow for very easy programming of the ITMS platform. With this approach, the ITMS platform is a suitable solution for implementing scalable data acquisition and processing systems based on a service-oriented model with the ability to easily implement remote participation applications.
机译:长脉冲融合实验中使用的数据采集系统需要实时实现数据缩减和模式识别算法。为了完成这些操作,必须使用在整个实验过程中都具有热插拔功能的软件工具。这非常重要,因为在实验的不同阶段,处理需求并不相同。芬欧汇川和CIEMAT开发的智能测试和测量系统(ITMS)是基于PXI和CompactPCI硬件实施可扩展数据采集和处理系统的技术示例。在ITMS平台中,一组软件工具允许用户使用由软件事件驱动的状态机来定义与不同实验阶段相关的处理算法。这些状态机是使用状态图XML(SCXML)语言指定的。该软件工具是使用JAVA,JINI,SCXML引擎和若干LabVIEW应用程序开发的。在此架构内,可以以自适应方式执行数据采集和处理应用程序。 SCXML语义的强大功能以及与XML用户定义的数据类型一起使用的能力使ITMS平台的编程非常容易。通过这种方法,ITMS平台是一种适合的解决方案,用于基于可轻松实现远程参与应用程序的面向服务的模型来实现可伸缩的数据获取和处理系统。

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