✦ LIBER ✦

Immune model-based fault diagnosis

✍ Scribed by Guan-Chun Luh; Wei-Chong Cheng

Publisher: Elsevier Science
Year: 2005
Tongue: English
Weight: 570 KB
Volume: 67
Category: Article
ISSN: 0378-4754
DOI: 10.1016/j.matcom.2004.07.004

No coin nor oath required. For personal study only.

✦ Synopsis

In this paper, a novel approach to immune model-based fault diagnosis methodology for nonlinear systems is presented. The diagnosis scheme consists of forward/inverse immune model identification, filtered residual generation, the fault alarm concentration (FAC), and the artificial immune regulation (AIR). A two-link manipulator simulation was employed to validate the effectiveness and robustness of the diagnosis approach. The simulation results show that it can detect and isolate actuator faults, sensor faults, and system component faults efficiently.

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