Comparative study on the use of acoustic emission and vibration analyses for the bearing fault diagnosis of high-speed trains

Blind deconvolution based on cyclostationarity maximization and its application to fault identification

(2018) Marco Buzzoni et al.   JOURNAL OF SOUND AND VIBRATION

Incipient Fault Feature Extraction for Rotating Machinery Based on Improved AR-Minimum Entropy Deconvolution Combined with Variational Mode Decomposition Approach

(2017) Qing Li et al.   Entropy

A fault diagnosis scheme for rolling bearing based on local mean decomposition and improved multiscale fuzzy entropy

(2016) Yongbo Li et al.   JOURNAL OF SOUND AND VIBRATION

A summary of fault modelling and predictive health monitoring of rolling element bearings

(2015) Idriss El-Thalji et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Review of Automatic Fault Diagnosis Systems Using Audio and Vibration Signals

(2013) Patricia Henriquez et al.   IEEE Transactions on Systems Man Cybernetics-Systems

Rotational Machine Health Monitoring and Fault Detection Using EMD-Based Acoustic Emission Feature Quantification

(2012) Ruoyu Li et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Maximum correlated Kurtosis deconvolution and application on gear tooth chip fault detection

(2012) Geoff L. McDonald et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Application of cepstrum pre-whitening for the diagnosis of bearing faults under variable speed conditions

(2012) P. Borghesani et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

The application of spectral kurtosis on Acoustic Emission and vibrations from a defective bearing

(2010) B. Eftekharnejad et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Rolling element bearing diagnostics—A tutorial

(2010) Robert B. Randall et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING