Fault Diagnosis Expert System of Automobile Engine Based on Neural Networks

Abstract:

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his paper reports a practical approach for detecting and diagnose engine faults in real-time based on both the historical and the real-time engine operation data using a specially design neural networks-based fault diagnosis expert system. This system consisted of multiple sensors for real-time monitoring, an engine database for historic data comparison, and a neural network-bases classifier for detecting faults based on both the real-time and the historic data. This neural network-based engine fault diagnosis system was evaluated in a series of validation tests. The results indicated that the system was capable to detect the predefined faults reliably, and the diagnosis error was less than 5%.

Info:

Periodical:

Key Engineering Materials (Volumes 460-461)

Edited by:

Yanwen Wu

Pages:

605-610

DOI:

10.4028/www.scientific.net/KEM.460-461.605

Citation:

L. L. Jiang et al., "Fault Diagnosis Expert System of Automobile Engine Based on Neural Networks", Key Engineering Materials, Vols. 460-461, pp. 605-610, 2011

Online since:

January 2011

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Price:

$35.00

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