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混合系统的监测与故障诊断

Monitoring and fault diagnosis of hybrid systems.

作者信息

Zhao Feng, Koutsoukos Xenofon, Haussecker Horst, Reich Jim, Cheung Patrick

机构信息

Microsoft Research, Redmond, WA 98052, USA.

出版信息

IEEE Trans Syst Man Cybern B Cybern. 2005 Dec;35(6):1225-40. doi: 10.1109/tsmcb.2005.850178.

DOI:10.1109/tsmcb.2005.850178
PMID:16366248
Abstract

Many networked embedded sensing and control systems can be modeled as hybrid systems with interacting continuous and discrete dynamics. These systems present significant challenges for monitoring and diagnosis. Many existing model-based approaches focus on diagnostic reasoning assuming appropriate fault signatures have been generated. However, an important missing piece is the integration of model-based techniques with the acquisition and processing of sensor signals and the modeling of faults to support diagnostic reasoning. This paper addresses key modeling and computational problems at the interface between model-based diagnosis techniques and signature analysis to enable the efficient detection and isolation of incipient and abrupt faults in hybrid systems. A hybrid automata model that parameterizes abrupt and incipient faults is introduced. Based on this model, an approach for diagnoser design is presented. The paper also develops a novel mode estimation algorithm that uses model-based prediction to focus distributed processing signal algorithms. Finally, the paper describes a diagnostic system architecture that integrates the modeling, prediction, and diagnosis components. The implemented architecture is applied to fault diagnosis of a complex electro-mechanical machine, the Xerox DC265 printer, and the experimental results presented validate the approach. A number of design trade-offs that were made to support implementation of the algorithms for online applications are also described.

摘要

许多网络化嵌入式传感与控制系统可建模为具有相互作用的连续和离散动态特性的混合系统。这些系统在监测和诊断方面面临重大挑战。许多现有的基于模型的方法侧重于诊断推理,假设已生成适当的故障特征。然而,一个重要的缺失环节是将基于模型的技术与传感器信号的采集和处理以及故障建模相结合,以支持诊断推理。本文探讨了基于模型的诊断技术与特征分析之间接口处的关键建模和计算问题,以实现混合系统中早期和突发故障的高效检测与隔离。引入了一种对突发和早期故障进行参数化的混合自动机模型。基于该模型,提出了一种诊断器设计方法。本文还开发了一种新颖的模式估计算法,该算法利用基于模型的预测来聚焦分布式处理信号算法。最后,本文描述了一种集成了建模、预测和诊断组件的诊断系统架构。所实现的架构应用于复杂机电设备施乐DC265打印机的故障诊断,所呈现的实验结果验证了该方法。还描述了为支持在线应用算法的实现而进行的一些设计权衡。

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