Abstract
In this paper, we describe a multiple Signal Fault Detection system that employs fuzzy logic at two levels of detection: signal segment fault and signal fault. The system involves signal segmentation, feature extraction and fuzzy logic based segment fault detection and signal fault detection. At the signal segment level, we developed a fuzzy learning algorithm that learns from good vehicle signals only. The system has been implemented and tested extensively of vehicle signals. The experiments using vehicle engine Electronic Control Unit(ECU) signals are presented and discussed in the paper.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Eric Chowanietz, Automobile electronics, Butterworth-Heinemann, 1995
Hong Guo, Jacob A. Crossman, Yi Lu Murphey, and Mark Coleman, “Automotive Signal Diagnostics Using Wavelets and Machine Learning,” IEEE Transaction on Vehicular, November, 2000.
Feldkamp, L.A., Puskorius, G.V. “A Signal Processing Framework Based on Dynamic Neural Networks with Application to Problems in Adaption, Filtering and Classification,” Proceedings of the IEEE. Vol. 86:11. pp. 2259–2277. Nov 1998.
Jacob A. Crossman, Hong Guo, Yi Lu Murphey, and John Cardillo, “Automotive Signal Fault Diagnostics: Part I: signal fault analysis, signal segmentation, feature extraction and quasi optimal feature selection,” to appear in IEEE Transaction on Vehicular, 2002.
Yi Lu, Tie Qi Chen, and Brennan Hamilton, “A Fuzzy System for Automotive Fault Diagnosis: — Fast Rule Generation and Self-Tuning,” IEEE Transaction on Vehicular, Vol. 49, No. 1, January 2000.
Daubechies, I. Ten Lectures on Wavelets. Capital City Press. Montpelier,VT. 1992.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Murphey, Y.L., Crossman, J., Chen, Z. (2003). Multiple Signal Fault Detection Using Fuzzy Logic. In: Chung, P.W.H., Hinde, C., Ali, M. (eds) Developments in Applied Artificial Intelligence. IEA/AIE 2003. Lecture Notes in Computer Science(), vol 2718. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45034-3_9
Download citation
DOI: https://doi.org/10.1007/3-540-45034-3_9
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40455-2
Online ISBN: 978-3-540-45034-4
eBook Packages: Springer Book Archive