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%.

• Periodical: Key Engineering Materials (Volumes 460-461)
• Pages: 605-610
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.460-461.605
• Online since: January 2011
• Authors: Lu Lu Jiang, Yong Ni, Li Hong Tang, Yong He
• Keywords: Engine, Fault Diagnosis, Inspect, Measurement, Neural Network (NN)

References

[1] Wollenberg, B.: IEEE T Power Syst. vol. PWRS-1(1986), p.241.

[2] Fauquembergue, P., Perrot, L.: 2nd Int. Symp. Expert Syst. Applicat. Power Syst., Seattle, WA, 1989, p.264.

[3] Fukui, C., Kawakami, J.: IEEE T Power Deliver. vol. PWRD-1(4). (1986), p.83.

[4] Germond, A., J., Niebur, D.: Europe. Proc. IEEE, vol. 80(1992), p.732.

[5] Komai, K.: IASTED Int. Symp. High Technol. Power Ind., Bozeman, MT. (1986), p.366.

[6] Talukdar, S., N.: IEEE Trans. Comput. vol. C-19(7). (1986), p.53.

[7] Lacher, R., C.: IEEE T Neural Network. 1(3). (1992), p.62.

[8] Hsieh, K., R., Chen, W., T.: IEEE T Neural Network. 4(2). (1993).

[9] Rodriguez, C., A: IEEE T Neural Network. 7(2). (1996), p.326.

[10] Limin, F.: IEEE T Neural Network. 7(6). (1996).