Immune model-based fault diagnosis

Guan-Chun Luh and Wei-Chong Cheng

Mathematics and Computers in Simulation (MATCOM), 2005, vol. 67, issue 6, 515-539

Abstract: 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.

Keywords: Model-based fault diagnosis; Fault detection and isolation; Immune model; Fault alarm concentration; Artificial immune regulation (search for similar items in EconPapers)
Date: 2005
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:67:y:2005:i:6:p:515-539

DOI: 10.1016/j.matcom.2004.07.004

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