Hilbert–Huang Transform-Based Vibration Signal Analysis for Machine Health Monitoring

By Ruqiang Yan, Robert X. Gao. IEEE Transactions on Instrumentation and Measurement, 2006

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Fault detection by means of Hilbert Huang Transform of the stator current in a PMSM with demagnetization (2010, methodology): “The Hilbert–Huang transform (HHT) is based on the instantaneous frequencies resulting from the intrinsic-mode functions (IMFs) of the signal being analyzed [ 16 ]; thus, it is not constrained by the uncertainty limitations with respect to the time and frequency resolutions to which other time–freque”
Bearing Health Monitoring Based on Hilbert–Huang Transform, Support Vector Machine, and Regression (2015, methodology): “Recent research works using the HHT are reported in the literature.”
A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches (2015, background): “, STFT and WT), which has shown quite interesting performance in terms of fault severity evaluation [163].”
Motor Bearing Fault Detection Using Spectral Kurtosis-Based Feature Extraction Coupled With K-Nearest Neighbor Distance Analysis (2016, methodology): “Time-frequency domain analysis includes short-time Fourier transform [18], wavelet transforms [19], [20], and Hilbert–Huang transforms (HHTs) [21], [22].”