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(Fault Detection and Isolation of the Nonlinear systems Using Neural Network-Based Multi-Fault Models)  

Lee, In-Su (Dept.of Electronics Electric Engineering, Sangmyung University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SC / v.39, no.1, 2002 , pp. 42-50 More about this Journal
Abstract
In this paper, we propose an FDI(fault detection and isolation) method using neural network-based multi-fault models to detect and isolate faults in nonlinear systems. When a change in the system occurs, the errors between the system output and the neural network nominal system output cross a threshold, and once a fault in the system is detected, the fault classifier statistically isolates the fault by using the error between each neural network-based fault model output and the system output. From the computer simulation results, it is verified that the proposed fault diagonal method can be performed successfully to detect and isolate faults in a nonlinear system.
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