@inproceedings{1b892fa228f2412ead92767e33ec75d5,
title = "Fault detection and isolation using artificial neural networks",
abstract = "This paper presents fault detection and isolation method using neural network-based multi-fault models to detect and isolate faults in nonlinear systems. The fault diagnosis system consists of a fault detection part to sense the faults and a fault isolation part to identify the types of faults that have occurred. In the proposed method, the fault is detected when the errors between the nonlinear system and the artificial neural network (ANN) nominal system output cross a predetermined threshold. Once a fault in the system is detected, the fault classifier based on ANN isolates the fault. Simulation results demonstrate the effectiveness of the proposed ANN-based fault diagnosis method.",
keywords = "Artificial neural networks, Fault detection and isolation, Nonlinear system",
author = "Lee, \{In Soo\} and Lee, \{Gordon K.\}",
year = "2006",
language = "English",
isbn = "9781604236750",
series = "19th International Conference on Computer Applications in Industry and Engineering, CAINE 2006",
pages = "335--340",
booktitle = "19th International Conference on Computer Applications in Industry and Engineering, CAINE 2006",
note = "19th International Conference on Computer Applications in Industry and Engineering, CAINE 2006 ; Conference date: 13-11-2006 Through 15-11-2006",
}