Proceedings ArticleDOI
Analysis and processing of shaft angular velocity signals in rotating machinery for diagnostic applications
Y.W. Kim,Giorgio Rizzoni,B. Samimy,Yue Wang +3 more
- Vol. 5, pp 2971-2974
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TLDR
The application of some modern signal processing methods to the analysis of angular velocity signals in a rotating machine for diagnostic purposes shows that these algorithms have potential for on-board diagnostic application in passenger and commercial vehicles, and more generally for failure detection of other classes of rotating machines.Abstract:
The paper presents the application of some modern signal processing methods to the analysis of angular velocity signals in a rotating machine for diagnostic purposes. The signal processing techniques considered in this paper include: classical non-parametric spectral analysis; principal component analysis; joint time-frequency analysis; the discrete wavelet transform; and change detection algorithm based on residual generation. These algorithms are employed to process shaft angular velocity data measured from an internal combustion engine, with the intent of detecting engine misfire. The results of these analyses show that these algorithms have potential for on-board diagnostic application in passenger and commercial vehicles, and more generally for failure detection of other classes of rotating machines.read more
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References
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Journal ArticleDOI
Time-frequency distributions-a review
TL;DR: A review and tutorial of the fundamental ideas and methods of joint time-frequency distributions is presented with emphasis on the diversity of concepts and motivations that have gone into the formation of the field.
Journal ArticleDOI
Linear and quadratic time-frequency signal representations
TL;DR: A tutorial review of both linear and quadratic representations is given, and examples of the application of these representations to typical problems encountered in time-varying signal processing are provided.
Journal ArticleDOI
Improved time-frequency representation of multicomponent signals using exponential kernels
H.-I. Choi,William J. Williams +1 more
TL;DR: In this article, a time-frequency distribution of L. Cohen's (1966) class is introduced, which is called exponential distribution (ED) after its exponential kernel function, and the authors interpret the ED from the spectral density-estimation point of view.
Journal ArticleDOI
Real Time Estimation of Engine Torque for the Detection of Engine Misfires
TL;DR: In this article, a deconvolution algorithm was proposed to estimate the mean torque produced by each cylinder during each stroke from a measurement of the crankshaft angular velocity, which is performed in the spatial frequency domain, recognizing that the combustion energy is concentrated at discrete spatial frequencies.
Proceedings ArticleDOI
Application of non-stationary analysis to machinery monitoring
TL;DR: The author discusses how nonstationary signal processes, such as the wavelet transform and the Wigner-Ville distribution, can be applied to machinery monitoring and diagnostics in industry.