Practical framework of Gini index in the application of machinery fault feature extraction
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Yonghao Miao | Hao Li | Jingjing Wang | Boyao Zhang | Yonghao Miao | Boyao Zhang | Hao Li | Jingjing Wang
[1] M. G. A. Nassef,et al. An adaptive variational mode decomposition based on sailfish optimization algorithm and Gini index for fault identification in rolling bearings , 2020 .
[2] Dong Wang,et al. Smoothness index-guided Bayesian inference for determining joint posterior probability distributions of anti-symmetric real Laplace wavelet parameters for identification of different bearing faults , 2015 .
[3] Yaguo Lei,et al. Envelope harmonic-to-noise ratio for periodic impulses detection and its application to bearing diagnosis , 2016 .
[4] Marco Buzzoni,et al. Blind deconvolution based on cyclostationarity maximization and its application to fault identification , 2018, Journal of Sound and Vibration.
[5] Scott T. Rickard,et al. Comparing Measures of Sparsity , 2008, IEEE Transactions on Information Theory.
[6] Kaiyun Wang,et al. A two-level adaptive chirp mode decomposition method for the railway wheel flat detection under variable-speed conditions , 2021 .
[7] Nader Sawalhi,et al. Rolling element bearing fault identification using a novel three-step adaptive and automated filtration scheme based on Gini index. , 2020, ISA transactions.
[8] Shuilong He,et al. A hybrid approach to fault diagnosis of roller bearings under variable speed conditions , 2017 .
[9] Qiang Wang,et al. Application of improved MCKD method based on QGA in planetary gear compound fault diagnosis , 2019, Measurement.
[10] Jing Lin,et al. Feature Mining and Health Assessment for Gearboxes Using Run-Up/Coast-Down Signals , 2016, Sensors.
[11] Ming Zhang,et al. Research on variational mode decomposition in rolling bearings fault diagnosis of the multistage centrifugal pump , 2017 .
[12] Xiaodong Jia,et al. A novel strategy for signal denoising using reweighted SVD and its applications to weak fault feature enhancement of rotating machinery , 2017 .
[13] Jijian Lian,et al. Adaptive variational mode decomposition method for signal processing based on mode characteristic , 2018, Mechanical Systems and Signal Processing.
[14] Ming Zhao,et al. Period-oriented multi-hierarchy deconvolution and its application for bearing fault diagnosis. , 2021, ISA transactions.
[15] Yonghao Miao,et al. Improvement of kurtosis-guided-grams via Gini index for bearing fault feature identification , 2017 .
[16] Minqiang Xu,et al. A fault diagnosis scheme for planetary gearboxes using modified multi-scale symbolic dynamic entropy and mRMR feature selection , 2017 .
[17] Jing Lin,et al. Health Assessment of Rotating Machinery Using a Rotary Encoder , 2018, IEEE Transactions on Industrial Electronics.
[18] Dong Wang,et al. Some further thoughts about spectral kurtosis, spectral L2/L1 norm, spectral smoothness index and spectral Gini index for characterizing repetitive transients , 2018 .
[19] 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 .
[20] Jay Lee,et al. A geometrical investigation on the generalized lp/lq norm for blind deconvolution , 2017, Signal Process..
[21] Tomasz Barszcz,et al. A novel method for the optimal band selection for vibration signal demodulation and comparison with the Kurtogram , 2011 .
[22] J. Antoni. Fast computation of the kurtogram for the detection of transient faults , 2007 .
[23] Chuan Li,et al. A nonparametric health index and its statistical threshold for machine condition monitoring , 2021 .
[24] Yonghao Miao,et al. Detection and recovery of fault impulses via improved harmonic product spectrum and its application in defect size estimation of train bearings , 2016 .
[25] Bingchang Hou,et al. A Comparison of Machine Health Indicators Based on the Impulsiveness of Vibration Signals , 2021, Acoustics Australia.
[26] Pietro Borghesani,et al. A statistical methodology for the design of condition indicators , 2019, Mechanical Systems and Signal Processing.
[27] J. Antoni. The spectral kurtosis: a useful tool for characterising non-stationary signals , 2006 .
[28] Jing Lin,et al. A Data-Driven Monitoring Scheme for Rotating Machinery Via Self-Comparison Approach , 2019, IEEE Transactions on Industrial Informatics.
[29] Qiang Miao,et al. A parameter-adaptive VMD method based on grasshopper optimization algorithm to analyze vibration signals from rotating machinery , 2018, Mechanical Systems and Signal Processing.
[30] Qing Zhao,et al. Multipoint Optimal Minimum Entropy Deconvolution and Convolution Fix: Application to vibration fault detection , 2017 .
[31] Jérôme Antoni,et al. The infogram: Entropic evidence of the signature of repetitive transients , 2016 .
[32] Qing Zhao,et al. Maximum correlated Kurtosis deconvolution and application on gear tooth chip fault detection , 2012 .
[33] Xiaolong Wang,et al. Diagnosis of compound faults of rolling bearings through adaptive maximum correlated kurtosis deconvolution , 2016 .
[34] Qiang Miao,et al. An optimized time varying filtering based empirical mode decomposition method with grey wolf optimizer for machinery fault diagnosis , 2018 .
[35] Shaopu Yang,et al. A general multi-objective optimized wavelet filter and its applications in fault diagnosis of wheelset bearings , 2020 .
[36] Ming Zhao,et al. Research on sparsity indexes for fault diagnosis of rotating machinery , 2020 .
[37] M. N. Albezzawy,et al. Early Rolling Bearing Fault Detection Using A Gini Index Guided Adaptive Morlet Wavelet Filter , 2019, 2019 IEEE 10th International Conference on Mechanical and Aerospace Engineering (ICMAE).
[38] Yonghao Miao,et al. Sparse maximum harmonics-to-noise-ratio deconvolution for weak fault signature detection in bearings , 2016 .
[39] Qing Ni,et al. A novel correntropy-based band selection method for the fault diagnosis of bearings under fault-irrelevant impulsive and cyclostationary interferences , 2021 .
[40] Alessandro Fasana,et al. The Autogram: An effective approach for selecting the optimal demodulation band in rolling element bearings diagnosis , 2018 .
[41] Lifeng Xi,et al. The sum of weighted normalized square envelope: A unified framework for kurtosis, negative entropy, Gini index and smoothness index for machine health monitoring , 2020, Mechanical Systems and Signal Processing.
[42] Robert B. Randall,et al. Enhancement of autoregressive model based gear tooth fault detection technique by the use of minimum entropy deconvolution filter , 2007 .
[43] Zhike Peng,et al. Box-Cox sparse measures: A new family of sparse measures constructed from kurtosis and negative entropy , 2021 .