Paper Title:
Fault Diagnosis Expert System of Automobile Engine Based on Neural Networks
  Abstract

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, Y. Ni, L. H. Tang, Y. He, "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
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