结构可重构系统的离散故障诊断

IF 1.7 4区计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS

Journal of Dynamic Systems Measurement and Control-Transactions of the Asme Pub Date : 2021-10-01 DOI:10.1115/1.4051252

Eeshan Deosthale, Daniel E. Jung, Q. Ahmed

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引用次数: 0

摘要

一类结构可重构混合系统的故障诊断比较复杂。这是因为SR系统倾向于切换它们的配置，这可能是错误的，也可能不是错误的。为了便于容错操作，识别SR系统的模式以及相应的故障(如果有的话)是很重要的。本文将SR系统的离散故障诊断与模式识别相结合，实现了两个主要目标:用于故障检测、隔离和模式识别的传感器选择，以及用于模式识别的残差选择。该框架是使用基于结构分析的方法构建的，以满足这些目标。该框架演示了10速自动变速器，这是SR系统的一个说明性示例。

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Discrete Fault Diagnosis of Structurally Reconfigurable Systems

Fault diagnosis of a certain class of hybrid systems referred to as structurally reconfigurable (SR) systems is complicated. This is because SR systems tend to switch their configuration, which may or may not be faulty. It is important to identify the mode of the SR system along with the corresponding fault if any, in order to facilitate a fault tolerant action. This paper combines discrete fault diagnosis with mode identification for SR systems to achieve two main objectives: Sensor selection for fault detection, isolation and mode identification, and residual selection for mode identification. The framework is built using a structural analysis-based approach to meet these objectives. This framework is demonstrated for a 10-speed Automatic Transmission, which is an illustrative example of SR systems.

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来源期刊

Journal of Dynamic Systems Measurement and Control-Transactions of the Asme 工程技术-仪器仪表

CiteScore

3.90

自引率

11.80%

发文量

审稿时长

24.0 months

期刊介绍： The Journal of Dynamic Systems, Measurement, and Control publishes theoretical and applied original papers in the traditional areas implied by its name, as well as papers in interdisciplinary areas. Theoretical papers should present new theoretical developments and knowledge for controls of dynamical systems together with clear engineering motivation for the new theory. New theory or results that are only of mathematical interest without a clear engineering motivation or have a cursory relevance only are discouraged. "Application" is understood to include modeling, simulation of realistic systems, and corroboration of theory with emphasis on demonstrated practicality.