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基于任务容器的多源数据实时监控系统研究
引用本文:山寿,王鹏,聂瑶佳.基于任务容器的多源数据实时监控系统研究[J].计算机测量与控制,2020,28(3):98-102.
作者姓名:山寿  王鹏  聂瑶佳
作者单位:中国飞行试验研究院测试所,西安710089;中国飞行试验研究院测试所,西安710089;中国飞行试验研究院测试所,西安710089
基金项目:空天地试飞综合监控技术(6141B05110303)
摘    要:为解决现有飞行试验监控模式存在的数据源单一、扩展性存在不足、系统鲁棒性差等缺点,进行基于数据分发服务规范DDS(data distribute service)的多源数据实时监控技术研究,在不改动实时监控系统硬件架构的情况下,根据现有实时监控系统数据特点和任务需求,采用任务容器技术对试飞数据处理任务进行分发与执行,实现飞行试验数据的分布式实时接收解析以及飞行任务的集中管控;采用基于模板方法的解析算法实现系统多源信号源的数据接入能力,提高了系统的扩展性;采用基于序列化和活跃度检查的任务派发机制实现了任务节点的状态监控及自动任务派发,提高了系统的稳定性,同时DDS通信协议的使用提高了实时监控系统在带宽受限状态下的通信能力。实际使用证明该技术的应用使监控系统具有高可靠、高稳定、动态可扩展等优点。

关 键 词:数据分发服务规范  任务容器  多源数据  分布式  高可靠
收稿时间:2019/12/9 0:00:00
修稿时间:2020/1/7 0:00:00

Research on Multi-source Data Real-time Monitoring SystemBased on Task Container
Abstract:In order to solve the shortcomings of the existing flight test monitoring mode, such as single data source, insufficient expansibility and poor system robustness, this paper studies the multi-source data real-time monitoring technology based on DDS (data distribution service). Without changing the hardware architecture of the real-time monitoring system, according to the data characteristics and task requirements of the existing real-time monitoring system, Using task container technology to distribute and execute flight test data processing tasks, realizing distributed real-time receiving and analysis of flight test data and centralized control of flight tasks; using analytic algorithm based on template method to realize data access ability of multi-source signal sources of the system, improving the scalability of the system; using task distribution mechanism based on serialization and activity check to realize At the same time, the use of DDS communication protocol improves the communication ability of the real-time monitoring system in the bandwidth limited state. The practical application shows that the real-time monitoring system with this technology has the advantages of high reliability, high stability and dynamic scalability.
Keywords:Task Container  Multi-source Data  Distributed  High Reliability
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