This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Malfunction Detection in Multi-cylinder Engines Using Wavelet Packet Dictionary
Technical Paper
2005-01-2261
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
In this paper, wavelets as signal processing tools are used to analyze the acceleration data acquired at the cylinder head for the detection and characterization of combustion malfunctions in multi-cylinder industrial engines. The objectives were to collect data on 1) normal operations, and 2) operations with a deactivated cylinder to simulate a faulty condition. Wavelet packet and local discriminatory basis algorithm are used to select wavelets that can recognize different conditions. It is shown that the wavelet packet provides a useful data analysis structure for extracting features that are capable of detecting the combustion malfunction of one cylinder in a 12-cylinder engine. Feature extraction is followed by a classification that uses a neural network for the fault identification phase.
Recommended Content
Authors
Citation
Tafreshi, R., Sassani, F., Ahmadi, H., and Dumont, G., "Malfunction Detection in Multi-cylinder Engines Using Wavelet Packet Dictionary," SAE Technical Paper 2005-01-2261, 2005, https://doi.org/10.4271/2005-01-2261.Also In
References
- Harrison M.F. De Soto I. Rubio Unzueta P.L. A linear acoustic model for multi-cylinder IC engine intake manifolds including the effects of the intake throttle Journal of sound and vibration 278 4-5 2004 975 1011
- Geveci Mert Osburn Andrew W, Franchek Matthew, A, An investigation of crankshaft oscillations for cylinder health diagnostics Mechanical systems and signal processing 2004
- Gyan Philippe Ginoux Stéphane Crankangle Jean-Claude Champoussin Guezennec Yann Based Torque Estimation: Mechanistic / Stochastic SAE 2000 World Congress Detroit, Michigan March 6-9 2000
- Daubechies I. Ten lectures on wavelets SIAM Philadelphia, PA 1992
- Mallat S. A wavelet tour of signal processing Academic Press 1999
- Coifman R. R. Meyer Y. Wickerhauser M. V. Wavelet analysis and signal processing, Wavelets and their applications 153 178 Boston 1992 Jones Barlett, B. Ruskai et al.
- Coifman R. R. Wickerhauser M. V. Entropy-based Algorithm for Best Basis Selection IEEE Transactions on Information Theory 38 2 1992 713 718
- Karmeshu, N. R. Pal Uncertainty, entropy and maximum entropy principle- and overview Studies in fuzziness and soft computing, Vol. 119, Entropy measures, maximum entropy principle and emerging applications Karmeshu Springer 2003
- Mallat S. Zhang Z. Matching pursuit with time frequency dictionaries IEEE Trans. on Signal Processing 41 1993 3397 3415
- Ahmadi H. Dumont G. Sassani F. Tafreshi R. Performance of informative wavelets for classification and diagnosis of machine faults International Journal on Wavelets, Multiresolution and Information Processing (IJWMIP) 1 3 2003 275 289
- Tafreshi R. Ahmadi H. Sassani F. Dumont G. Informative wavelet algorithm in diesel engine diagnosis The 17th IEEE international symposium on intelligent control (ISIC'02) 2002 361 366
- Liu B. Ling S. F. On the selection of informative wavelets for machinery diagnosis Mechanical systems and signal processing 13 1 1999 145 162
- Tafreshi R. Sassani F. Ahmadi H. Dumont G. Local discriminant bases in machine fault diagnosis using vibration signals Journal of integrated computer-aided engineering 9 2004
- Saito N. Coifman R. R. Local discriminant bases, Mathematical imaging: wavelet applications in signal and image processing II Proc. SPIE 2303 1994