The Application of LCS and Information Entropy as a Novel Fusion Algorithm for Degradation Feature Extraction
暂无分享,去创建一个
[1] Petre Caraiani. The predictive power of singular value decomposition entropy for stock market dynamics , 2014 .
[2] Fadi Dornaika,et al. Enhanced and parameterless Locality Preserving Projections for face recognition , 2011, Neurocomputing.
[3] Yan Liang,et al. Bias estimation for asynchronous multi-rate multi-sensor fusion with unknown inputs , 2018, Inf. Fusion.
[4] Jyoti K. Sinha,et al. An improved data fusion technique for faults diagnosis in rotating machines , 2014 .
[5] Bo-Suk Yang,et al. Machine performance degradation assessment and remaining useful life prediction using proportional hazard model and support vector machine , 2012, WCE 2010.
[6] Keheng Zhu,et al. A roller bearing fault diagnosis method based on hierarchical entropy and support vector machine with particle swarm optimization algorithm , 2014 .
[7] Rick S. Blum,et al. Theoretical analysis of correlation-based quality measures for weighted averaging image fusion , 2010, Inf. Fusion.
[8] Plamen P. Angelov,et al. Density-based averaging - A new operator for data fusion , 2013, Inf. Sci..
[9] Yujing Wang,et al. Classification of fault location and the degree of performance degradation of a rolling bearing based on an improved hyper-sphere-structured multi-class support vector machine , 2012 .
[10] Shaojiang Dong,et al. Bearing degradation process prediction based on the PCA and optimized LS-SVM model , 2013 .
[11] Jinde Zheng,et al. A rolling bearing fault diagnosis approach based on LCD and fuzzy entropy , 2013 .
[12] Yongsheng Zhu,et al. Bearing performance degradation assessment based on the rough support vector data description , 2013 .
[13] Shaoyuan Li,et al. A switch-mode information fusion filter based on ISRUKF for autonomous navigation of spacecraft , 2014, Inf. Fusion.
[14] Jiangping Wang,et al. Vibration-based fault diagnosis of pump using fuzzy technique , 2006 .
[15] Shahrul Kamaruddin,et al. An overview of time-based and condition-based maintenance in industrial application , 2012, Comput. Ind. Eng..
[16] Jyoti K. Sinha,et al. Vibration-based condition monitoring of rotating machines using a machine composite spectrum , 2013 .
[17] Maciej Krawczak,et al. An approach to dimensionality reduction in time series , 2014, Inf. Sci..
[18] Xuemin Tian,et al. Sparse Kernel Locality Preserving Projection and Its Application in Nonlinear Process Fault Detection , 2013 .
[19] Zhang Yan. Bearing running state recognition based on non-extensive wavelet feature scale entropy and support vector machine , 2012 .
[20] Mohammad Hossein Fazel Zarandi,et al. Relative entropy fuzzy c-means clustering , 2014, Inf. Sci..
[21] Junsheng Cheng. Local Characteristic-scale Decomposition Method and Its Application to Gear Fault Diagnosis , 2012 .
[22] Jay Lee,et al. Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications , 2014 .
[23] James A. Rodger,et al. Toward reducing failure risk in an integrated vehicle health maintenance system: A fuzzy multi-sensor data fusion Kalman filter approach for IVHMS , 2012, Expert Syst. Appl..
[24] Jun Du,et al. Layered clustering multi-fault diagnosis for hydraulic piston pump , 2013 .
[25] A. Plastino,et al. A Shannon-Tsallis transformation , 2012, 1201.4507.
[26] Hong-ru Li,et al. Degradation feature extraction of the hydraulic pump based on high-frequency harmonic local characteristic-scale decomposition sub-signal separation and discrete cosine transform high-order singular entropy , 2016 .
[27] Ladislav Kristoufek,et al. Measuring correlations between non-stationary series with DCCA coefficient , 2013, 1310.3984.
[28] Lin Liang,et al. Quantitative diagnosis of a spall-like fault of a rolling element bearing by empirical mode decomposition and the approximate entropy method , 2013 .
[29] Abdolreza Ohadi,et al. Comparison of FDA-based and PCA-based features in fault diagnosis of automobile gearboxes , 2013, Neurocomputing.
[30] Davide Anguita,et al. Machine learning for wear forecasting of naval assets for condition-based maintenance applications , 2015, 2015 International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles (ESARS).