Rolling element bearing faults diagnosis based on kurtogram and frequency domain correlated kurtosis
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Xiaohui Gu | Shaopu Yang | Yongqiang Liu | Rujiang Hao | Shaopu Yang | Yongqiang Liu | Rujiang Hao | X. Gu | Yong-qiang Liu
[1] Jérôme Antoni,et al. The infogram: Entropic evidence of the signature of repetitive transients , 2016 .
[2] Robert B. Randall,et al. Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study , 2015 .
[3] Wensheng Su,et al. Rolling element bearing faults diagnosis based on optimal Morlet wavelet filter and autocorrelation enhancement , 2010 .
[4] P. D. McFadden,et al. Vibration monitoring of rolling element bearings by the high-frequency resonance technique — a review , 1984 .
[5] Robert B. Randall,et al. The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines , 2006 .
[6] Jing Yuan,et al. Improved spectral kurtosis with adaptive redundant multiwavelet packet and its applications for rotating machinery fault detection , 2012 .
[7] Peter W. Tse,et al. The design of a new sparsogram for fast bearing fault diagnosis: Part 1 of the two related manuscripts that have a joint title as “Two automatic vibration-based fault diagnostic methods using the novel sparsity measurement – Parts 1 and 2” , 2013 .
[8] Chuan Li,et al. Criterion fusion for spectral segmentation and its application to optimal demodulation of bearing vibration signals , 2015 .
[9] Peter W. Tse,et al. An enhanced Kurtogram method for fault diagnosis of rolling element bearings , 2013 .
[10] Wei He,et al. Rolling element bearing fault detection based on optimal antisymmetric real Laplace wavelet , 2011 .
[11] Yaguo Lei,et al. Application of an improved kurtogram method for fault diagnosis of rolling element bearings , 2011 .
[12] J. Antoni. Fast computation of the kurtogram for the detection of transient faults , 2007 .
[13] Jianshe Kang,et al. A New Improved Kurtogram and Its Application to Bearing Fault Diagnosis , 2015 .
[14] Ming Liang,et al. Identification of multiple transient faults based on the adaptive spectral kurtosis method , 2012 .
[15] Qing Zhao,et al. Maximum correlated Kurtosis deconvolution and application on gear tooth chip fault detection , 2012 .
[16] Binqiang Chen,et al. Detecting of transient vibration signatures using an improved fast spatial–spectral ensemble kurtosis kurtogram and its applications to mechanical signature analysis of short duration data from rotating machinery , 2013 .
[17] Gang Yu,et al. A new statistical modeling and detection method for rolling element bearing faults based on alpha–stable distribution , 2013 .
[18] Ming Liang,et al. An adaptive SK technique and its application for fault detection of rolling element bearings , 2011 .
[19] J. Antoni. The spectral kurtosis: a useful tool for characterising non-stationary signals , 2006 .
[20] Tomasz Barszcz,et al. A novel method for the optimal band selection for vibration signal demodulation and comparison with the Kurtogram , 2011 .
[21] I. S. Bozchalooi,et al. A joint resonance frequency estimation and in-band noise reduction method for enhancing the detectability of bearing fault signals , 2008 .
[22] Peter W. Tse,et al. A general sequential Monte Carlo method based optimal wavelet filter: A Bayesian approach for extracting bearing fault features , 2015 .