A Two-Stage Method Using Spline-Kernelled Chirplet Transform and Angle Synchronous Averaging to Detect Faults at Variable Speed
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[1] Kang Zhang,et al. An order tracking technique for the gear fault diagnosis using local mean decomposition method , 2012 .
[2] Yaguo Lei,et al. Tacholess Envelope Order Analysis and Its Application to Fault Detection of Rolling Element Bearings with Varying Speeds , 2013, Sensors.
[3] Qiang Gao,et al. A Walsh transform-based Teager energy operator demodulation method to detect faults in axial piston pumps , 2019, Measurement.
[4] Yanxue Wang,et al. Research on variational mode decomposition and its application in detecting rub-impact fault of the rotor system , 2015 .
[5] Zhipeng Feng,et al. Time-varying demodulation analysis for rolling bearing fault diagnosis under variable speed conditions , 2017 .
[6] Boualem Boashash,et al. A unified approach to the STFT, TFDs, and instantaneous frequency , 1992, IEEE Trans. Signal Process..
[7] Yu Guo,et al. Fault feature extraction based on combination of envelope order tracking and cICA for rolling element bearings , 2017, Mechanical Systems and Signal Processing.
[8] Hongchun Sun,et al. A Single-Channel Blind Source Separation Technique Based on AMGMF and AFEEMD for the Rotor System , 2018, IEEE Access.
[9] Biao Huang,et al. Survey on the theoretical research and engineering applications of multivariate statistics process monitoring algorithms: 2008-2017 , 2018, The Canadian Journal of Chemical Engineering.
[10] Tomasz Barszcz,et al. A two-step procedure for estimation of instantaneous rotational speed with large fluctuations , 2013 .
[11] W. M. Zhang,et al. Polynomial Chirplet Transform With Application to Instantaneous Frequency Estimation , 2011, IEEE Transactions on Instrumentation and Measurement.
[12] Yi Qin,et al. The Optimized Deep Belief Networks With Improved Logistic Sigmoid Units and Their Application in Fault Diagnosis for Planetary Gearboxes of Wind Turbines , 2019, IEEE Transactions on Industrial Electronics.
[13] X. An,et al. Bearing fault diagnosis of a wind turbine based on variational mode decomposition and permutation entropy , 2017 .
[14] Arun K. Samantaray,et al. Rolling element bearing defect diagnosis under variable speed operation through angle synchronous averaging of wavelet de-noised estimate , 2016 .
[15] Luis Romeral,et al. Short-Circuit Detection by Means of Empirical Mode Decomposition and Wigner–Ville Distribution for PMSM Running Under Dynamic Condition , 2009, IEEE Transactions on Industrial Electronics.
[16] Wu Deng,et al. A Novel Fault Diagnosis Method Based on Integrating Empirical Wavelet Transform and Fuzzy Entropy for Motor Bearing , 2018, IEEE Access.
[17] G. Meng,et al. General Parameterized Time-Frequency Transform , 2014, IEEE Transactions on Signal Processing.
[18] Hui Wang,et al. An Adaptive Randomized Orthogonal Matching Pursuit Algorithm With Sliding Window for Rolling Bearing Fault Diagnosis , 2018, IEEE Access.
[19] Yu Zhang,et al. Incipient Fault Diagnosis of Roller Bearing Using Optimized Wavelet Transform Based Multi-Speed Vibration Signatures , 2017, IEEE Access.
[20] Tianyang Wang,et al. Rolling element bearing fault diagnosis via fault characteristic order (FCO) analysis , 2014 .
[21] Fan Jiang,et al. An Improved VMD With Empirical Mode Decomposition and Its Application in Incipient Fault Detection of Rolling Bearing , 2018, IEEE Access.
[22] Jiawei Xiang,et al. Rolling element bearing fault detection using PPCA and spectral kurtosis , 2015 .
[23] Shuilong He,et al. A hybrid approach to fault diagnosis of roller bearings under variable speed conditions , 2017 .
[24] Weigang Wen,et al. Rolling Bearing Fault Diagnosis via ConceFT-Based Time-Frequency Reconfiguration Order Spectrum Analysis , 2018, IEEE Access.
[25] Yi Qin,et al. A New Family of Model-Based Impulsive Wavelets and Their Sparse Representation for Rolling Bearing Fault Diagnosis , 2018, IEEE Transactions on Industrial Electronics.
[26] Lingli Cui,et al. Quantitative and Localization Diagnosis of a Defective Ball Bearing Based on Vertical–Horizontal Synchronization Signal Analysis , 2017, IEEE Transactions on Industrial Electronics.
[27] Jiawei Xiang,et al. A fault detection strategy using the enhancement ensemble empirical mode decomposition and random decrement technique , 2017, Microelectron. Reliab..
[28] Guolin He,et al. Non-stationary vibration feature extraction method based on sparse decomposition and order tracking for gearbox fault diagnosis , 2018 .
[29] Fei Dong,et al. Rolling Bearing Fault Diagnosis Using Modified LFDA and EMD With Sensitive Feature Selection , 2018, IEEE Access.
[30] Robert X. Gao,et al. Deep learning and its applications to machine health monitoring , 2019, Mechanical Systems and Signal Processing.
[31] Na Wu,et al. Quantitative fault analysis of roller bearings based on a novel matching pursuit method with a new step-impulse dictionary , 2016 .
[32] Shuhui Wang,et al. Convolutional neural network-based hidden Markov models for rolling element bearing fault identification , 2017, Knowl. Based Syst..
[33] Yang Yang,et al. Parameterised time-frequency analysis methods and their engineering applications: A review of recent advances , 2019, Mechanical Systems and Signal Processing.
[34] G. Meng,et al. Spline-Kernelled Chirplet Transform for the Analysis of Signals With Time-Varying Frequency and Its Application , 2012, IEEE Transactions on Industrial Electronics.
[35] Adel Belouchrani,et al. Fault Diagnosis in Industrial Induction Machines Through Discrete Wavelet Transform , 2011, IEEE Transactions on Industrial Electronics.
[36] Ruqiang Yan,et al. Gearbox Fault Diagnosis in a Wind Turbine Using Single Sensor Based Blind Source Separation , 2016, J. Sensors.
[37] Rabah Abdelkader,et al. Rolling Bearing Fault Diagnosis Based on an Improved Denoising Method Using the Complete Ensemble Empirical Mode Decomposition and the Optimized Thresholding Operation , 2018, IEEE Sensors Journal.