Fault detection and identification in nonlinear complex systems

非线性复杂系统中的故障检测与识别

• 批准号: DP140102180
• 负责人: A/Prof Mohammad Aldeen
• 金额: $ 18.88万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2014
• 资助国家: 澳大利亚
• 起止时间: 2014-06-01 至 2018-04-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP140102180
• 关键词: Fault; detection; identification; nonlinear; complex; Fault; detection; identification; nonlinear; complex

Complex systems usually comprise a large number of inter-dependent subsystems linked together to perform a certain task. Examples of such systems are power systems, irrigation systems, air traffic control systems, to name a few. Such systems are subject to component failure or malfunction. Total failure can cause an unacceptable financial losses and/or danger to personnel. It is therefore extremely essential, from economic and safety view points, that a way be found to ensure reliable and viable operation of complex plants. A first step in achieving this goal is to detect faults on-line and in real-time when they occur and identify their location and characteristics, which is the aim of this project.

复杂的系统通常包括大量相互依赖的子系统，这些子系统链接在一起以执行某个任务。此类系统的示例是电力系统，灌溉系统，空中交通管制系统，仅举几例。此类系统受到组件故障或故障的约束。总失败会造成不可接受的财务损失和/或对人员的危险。因此，从经济和安全观点来看，发现一种方法可以确保复杂植物的可靠运行。实现此目标的第一步是在线和实时检测故障并确定其位置和特征，这是该项目的目的。