Rolling bearing fault diagnosis using impulse feature enhancement and nonconvex regularization
暂无分享,去创建一个
Huibin Lin | Guolin He | Wu Fangtan | Guolin He | Huibin Lin | F. Wu
[1] Gaigai Cai,et al. Sparsity-enhanced signal decomposition via generalized minimax-concave penalty for gearbox fault diagnosis , 2018, Journal of Sound and Vibration.
[2] Jing Wang,et al. Basic pursuit of an adaptive impulse dictionary for bearing fault diagnosis , 2014, 2014 International Conference on Mechatronics and Control (ICMC).
[3] Steven Y. Liang,et al. Weak Fault Detection for Gearboxes Using Majorization-Minimization and Asymmetric Convex Penalty Regularization , 2018, Symmetry.
[4] Yang Yu,et al. A roller bearing fault diagnosis method based on EMD energy entropy and ANN , 2006 .
[5] Laurent Condat,et al. A Direct Algorithm for 1-D Total Variation Denoising , 2013, IEEE Signal Processing Letters.
[6] Guolin He,et al. Non-stationary vibration feature extraction method based on sparse decomposition and order tracking for gearbox fault diagnosis , 2018 .
[7] Robert B. Randall,et al. Rolling element bearing diagnostics—A tutorial , 2011 .
[8] Jin Chen,et al. Weak fault feature extraction of rolling bearings based on globally optimized sparse coding and approximate SVD , 2018, Mechanical Systems and Signal Processing.
[9] I. Johnstone,et al. Ideal spatial adaptation by wavelet shrinkage , 1994 .
[10] Robert B. Randall,et al. Enhancement of autoregressive model based gear tooth fault detection technique by the use of minimum entropy deconvolution filter , 2007 .
[11] Yi Qin,et al. Weak transient fault feature extraction based on an optimized Morlet wavelet and kurtosis , 2016 .
[12] Xuefeng Chen,et al. Fault Diagnosis for a Wind Turbine Generator Bearing via Sparse Representation and Shift-Invariant K-SVD , 2017, IEEE Transactions on Industrial Informatics.
[13] Cong Wang,et al. Fault feature extraction of rolling element bearings based on wavelet packet transform and sparse representation theory , 2018, J. Intell. Manuf..
[14] Huaqing Wang,et al. A Sparsity-Promoted Method Based on Majorization-Minimization for Weak Fault Feature Enhancement , 2018, Sensors.
[15] Xuefeng Chen,et al. Sparse representation based on parametric impulsive dictionary design for bearing fault diagnosis , 2019, Mechanical Systems and Signal Processing.
[16] Robert B. Randall,et al. A Stochastic Model for Simulation and Diagnostics of Rolling Element Bearings With Localized Faults , 2003 .
[17] Yanyang Zi,et al. Sparsity-based Algorithm for Detecting Faults in Rotating Machines , 2015, ArXiv.
[18] Ruqiang Yan,et al. Weighted low-rank sparse model via nuclear norm minimization for bearing fault detection , 2017 .
[19] Ivan W. Selesnick,et al. Total Variation Denoising Via the Moreau Envelope , 2017, IEEE Signal Processing Letters.
[20] David L. Donoho,et al. De-noising by soft-thresholding , 1995, IEEE Trans. Inf. Theory.
[21] Qing Li,et al. Multiple Faults Detection for Rotating Machinery Based on Bicomponent Sparse Low-Rank Matrix Separation Approach , 2018, IEEE Access.
[22] Dimitri P. Bertsekas,et al. On the Douglas—Rachford splitting method and the proximal point algorithm for maximal monotone operators , 1992, Math. Program..
[23] Huibin Lin,et al. Fault feature extraction of rolling element bearings using sparse representation , 2016 .
[24] Yaguo Lei,et al. A review on empirical mode decomposition in fault diagnosis of rotating machinery , 2013 .
[25] Qing Li,et al. An Improved Sparse Regularization Method for Weak Fault Diagnosis of Rotating Machinery Based Upon Acceleration Signals , 2018, IEEE Sensors Journal.