Successive variational mode decomposition and blind source separation based on salp swarm optimization for bearing fault diagnosis

[1]  Lingli Cui,et al.  Early bearing fault diagnosis based on the improved singular value decomposition method , 2021, The International Journal of Advanced Manufacturing Technology.

[2]  Waqas Haider Bangyal,et al.  A New Initialization Approach in Particle Swarm Optimization for Global Optimization Problems , 2021, Comput. Intell. Neurosci..

[3]  Chaokun Yan,et al.  A Novel Feature Selection Method Based on Salp Swarm Algorithm , 2021, 2021 IEEE International Conference on Information Communication and Software Engineering (ICICSE).

[4]  Xiaohong Wang,et al.  Bearing fault diagnosis based on EMD and improved Chebyshev distance in SDP image , 2021 .

[5]  Shengtian Sang,et al.  Bearing fault diagnosis based on combined multi-scale weighted entropy morphological filtering and bi-LSTM , 2021, Applied Intelligence.

[6]  Salwani Abdullah,et al.  Salp swarm optimizer for modeling the software fault prediction problem , 2021, J. King Saud Univ. Comput. Inf. Sci..

[7]  Seyed Mohammad Mirjalili,et al.  Dynamic Salp swarm algorithm for feature selection , 2021, Expert Syst. Appl..

[8]  Abdelkrim Moussaoui,et al.  Optimal wavelet analysis and enhanced independent component analysis for isolated and combined mechanical faults diagnosis , 2020, International Journal of Advanced Mechatronic Systems.

[9]  Mojtaba Nazari,et al.  Successive variational mode decomposition , 2020, Signal Process..

[10]  Seyed Mohammad Mirjalili,et al.  Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection , 2020, Expert Syst. Appl..

[11]  Hossam Faris,et al.  Hybridized Extreme Learning Machine Model with Salp Swarm Algorithm: A Novel Predictive Model for Hydrological Application , 2020, Complex..

[12]  Guozheng Li,et al.  Blind source separation of composite bearing vibration signals with low-rank and sparse decomposition , 2019, Measurement.

[13]  Hafiz Tayyab Rauf,et al.  Bat Algorithm with Different Initialization Approaches for Numerical Optimization , 2019, 2019 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT).

[14]  Longwen Wu,et al.  Mode Mixing Suppression Algorithm for Empirical Mode Decomposition Based on Self-Filtering Method , 2019, Radioelectronics and Communications Systems.

[15]  Mohammad Reza Ghasemi,et al.  Modified particle swarm optimization with novel population initialization , 2019, Journal of Information and Optimization Sciences.

[16]  Yong Qin,et al.  Blind Source Separation Based on EMD and Correlation Measure for Rotating Machinery Fault Diagnosis , 2019, 2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC).

[17]  Mojtaba Tahani,et al.  Optimization of airfoil Based Savonius wind turbine using coupled discrete vortex method and salp swarm algorithm , 2019, Journal of Cleaner Production.

[18]  Alessandro Paolo Daga,et al.  The Politecnico di Torino rolling bearing test rig: Description and analysis of open access data , 2019, Mechanical Systems and Signal Processing.

[19]  Rabeh Abbassi,et al.  An efficient salp swarm-inspired algorithm for parameters identification of photovoltaic cell models , 2019, Energy Conversion and Management.

[20]  Gh. S. El-tawel,et al.  Feature Selection Using Chaotic Salp Swarm Algorithm for Data Classification , 2018, Arabian Journal for Science and Engineering.

[21]  Prem Kumar,et al.  Selecting effective intrinsic mode functions of empirical mode decomposition and variational mode decomposition using dynamic time warping algorithm for rolling element bearing fault diagnosis , 2018, Trans. Inst. Meas. Control.

[22]  Xiong Luo,et al.  Parameter Estimation for Soil Water Retention Curve Using the Salp Swarm Algorithm , 2018, Water.

[23]  Zhang Wenyuan,et al.  Land Cover Change Detection in Urban Lake Areas Using Multi-Temporary Very High Spatial Resolution Aerial Images , 2018 .

[24]  Zoubeida Messali,et al.  Robust fuzzy c-means clustering algorithm using non-parametric Bayesian estimation in wavelet transform domain for noisy MR brain image segmentation , 2017, IET Image Process..

[25]  Hossam Faris,et al.  Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems , 2017, Adv. Eng. Softw..

[26]  Wu Deng,et al.  Study on a Novel Bearing Fault Diagnosis Method from Frequency and Energy Perspective , 2017 .

[27]  Ming Zhang,et al.  Research on variational mode decomposition in rolling bearings fault diagnosis of the multistage centrifugal pump , 2017 .

[28]  Ivan Prebil,et al.  EEMD-based multiscale ICA method for slewing bearing fault detection and diagnosis , 2016 .

[29]  Jaouher Ben Ali,et al.  Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals , 2015 .

[30]  Hao Zhou,et al.  Research on Application of Blind Source Separation in Rolling Bearing Fault Diagnosis Based on Particle Swarm Optimization , 2014 .

[31]  Yu Yang,et al.  Partly ensemble empirical mode decomposition: An improved noise-assisted method for eliminating mode mixing , 2014, Signal Process..

[32]  Mohammad A. Karim,et al.  Toward aerosols LiDAR scattering plots clustering and analysis , 2013, Defense, Security, and Sensing.

[33]  Tsung-Ying Sun,et al.  Effective Learning Rate Adjustment of Blind Source Separation Based on an Improved Particle Swarm Optimizer , 2008, IEEE Transactions on Evolutionary Computation.

[34]  Weina Wang,et al.  On fuzzy cluster validity indices , 2007, Fuzzy Sets Syst..

[35]  J. Cardoso,et al.  Blind beamforming for non-gaussian signals , 1993 .

[36]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[37]  Fei Wu,et al.  Fault Diagnosis of Rolling Bearings Based on Improved Empirical Mode Decomposition and Fuzzy C-Means Algorithm , 2021, Traitement du Signal.

[38]  Ibrahim Aljarah,et al.  Salp Swarm Optimization Search Based Feature Selection for Enhanced Phishing Websites Detection , 2021, EvoApplications.

[39]  Chen Hong,et al.  Blind Source Separation based on Whale Optimization Algorithm , 2018 .

[40]  Jamil Ahmad,et al.  An Improved Bat Algorithm based on Novel Initialization Technique for Global Optimization Problem , 2018 .

[41]  É. Moulines,et al.  Second Order Blind Separation of Temporally Correlated Sources , 1993 .

[42]  J. Dunn.  A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters , 1973 .

[43]  J. Bezdek.  Cluster Validity with Fuzzy Sets , 1973 .