System Control and Diagnosis in Data-Rich Environment

数据丰富环境中的系统控制与诊断

• 批准号: RGPIN-2016-06375
• 负责人: Zhao, Qing
• 金额: $ 2.99万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=637398
• 关键词: System; Control; Diagnosis; Data; Rich

Owing to the fast development of computer and network technology, nowadays processes and control systems are enhanced by rich measurement data from numerous sensors of multiple sources and locations. In large-scale manufacturing and chemical processes, application of distributed control systems (DCS) has created such a data-rich environment. Real-time measurements as well as historical data from different locations and sources are available for processing. Meanwhile, due to the lack of effective tools digging in the massive amount of data for relevant and useful information, industries are facing the so-called “data rich but information poor” syndrome.

由于计算机和网络技术的快速发展，现在的过程和控制系统通过来自多个来源和位置的众多传感器的丰富测量数据来增强。在大规模制造和化工过程中，分布式控制系统（DCS）的应用创造了这样一个数据丰富的环境。实时测量以及来自不同地点和来源的历史数据可供处理。与此同时，由于缺乏有效的工具在海量数据中挖掘相关的有用信息，行业面临着所谓的“数据丰富但信息贫乏”的综合症。