Engine Misfire Detection with Pervasive Mobile Audio
We address the problem of detecting whether an engine is misfiring by using machine learning techniques on transformed audio data collected from a smartphone. We recorded audio samples in an uncontrolled environment and extracted Fourier, Wavelet and Mel-frequency Cepstrum features from normal and a...
Main Authors: | Siegel, Joshua E, Kumar, Sumeet, Ehrenberg, Isaac Mayer, Sarma, Sanjay E |
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Other Authors: | Massachusetts Institute of Technology. Department of Mechanical Engineering |
Format: | Article |
Language: | en_US |
Published: |
Springer International Publishing
2018
|
Online Access: | http://hdl.handle.net/1721.1/117389 https://orcid.org/0000-0002-5540-7401 https://orcid.org/0000-0003-1038-7598 https://orcid.org/0000-0003-2812-039X |
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