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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© 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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