Abstract
Abstract. In this paper we have used a combination of three algorithms: Dynamic time warping (DTW) and the coefficients of Mel frequency Cepstrum (MFC) and Fast Fourier Transformation (FFT) for classifying various engine faults. Dynamic time warping and MFCC (Mel Frequency Cepstral Coefficients), FFT are used usually for automatic speech recognition purposes. This paper introduces DTW algorithm and the coefficients extracted from Mel Frequency Cepstrum, FFT for automatic fault detection and identification (FDI) of internal combustion engines for the first time. The objective of the current work was to develop a new intelligent system that should be able to predict the possible fault in a running engine at different-different workshops. We are doing this first time. Basically we took different-different samples of Engine fault and applied these algorithms, extracted features from it and used Fuzzy Rule Base approach for fault Classification.
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References
J.C.C., Castejn O.: Incipient bearing fault diagnosis using DWT for feature extraction, World Congress, Besanon (France).
Ja Choi, Jong Myoung Ko, Chang Ouk Kim, Yoon Seong Kang, Seung Jun Lee.: Dynamic Time Warping Algorithms for Run-by-Run Process Fault Detection, ISSM Paper: PC-P-101
Fulufhelo V., Tshilidzi M., Unathi M.: Early classification of bearing faults using Hidden Markov Models, International Journal of Innovative Computing, Information and Control.
Wen-Xian Y.: Diagnosing the engine value faults by genetic programming, Journal of Sound and Vibration Volume 293, Issues 1–2. 5. http://www.motorera.com/dictionary
Ren Y., Hu Tianyou, Yang P., Liu X., Approach to disel engine fault diagnosis, Mechatronics and Automation, 2005 IEEE International Conference 3, 1451–1454 (2005)
Ren Y., Hu Tianyou; Yang P. Liu X.: Approach to diesel engine faultdiagnosis, Mechatronics and Automation, IEEE International Conference Volume 3, 1451–1454 (2005)
Shiyuan L., Fengshou G., Ball A.: Detection of engine valve faults by vibration signals measured on the cylinder head, Journal of Automobile Engineering.
Kobayashi K.; Uchikawa, Y.; Simizu, T.; Nakai, K.; Yoshizawa, M.: The rejection of magnetic noise from the wire using ICA for magneto cardiogram, Magnetics, IEEE Transactions 41(10), 4152–4154 (2005)
Ciaramella, E.; Giorgi, L.; Dapos; Errico, A.; Cavaliere, F.; Gaimari, G.; Prati, G. “Technique for setting the power preemphasis in WDM optical systems”, Journal of Light wave Technology, 24(1), 342–356 (2006)
Srinivasam R., Ming S.: Online fault diagnosis and state identification, Chemical engineering science
Sherlock B. G. and Kakad Y. P.: Transform domain technique for windowing the DCT and DST, Journal of the Franklin Institute 339(1), 111–120 (2002)
Duan C., He Zhengjia, and Jiang H.: A sliding window feature extraction method for rotating machine based the lifting scheme, Journal of Sound and Vibration Volume 229, Issues 4–5
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© 2009 Indian Institute of Information Technology, India
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Singh, V., Meena, N. (2009). Engine Fault Diagnosis using DTW, MFCC and FFT. In: Tiwary, U.S., Siddiqui, T.J., Radhakrishna, M., Tiwari, M.D. (eds) Proceedings of the First International Conference on Intelligent Human Computer Interaction. Springer, New Delhi. https://doi.org/10.1007/978-81-8489-203-1_6
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DOI: https://doi.org/10.1007/978-81-8489-203-1_6
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-8489-404-2
Online ISBN: 978-81-8489-203-1
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