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Multi-domain extreme learning machine for bearing failure detection based on variational modal decomposition and approximate cyclic correntropy

Wang Xiaohui, Sui Guangzhou, Xiang Jiawei, Wang Guangbin, Huo Zhiqiang, Huang Zhen
2020 IEEE Access  
An intelligent bearing failure detection method was proposed based on local mean decomposition, singularvalue decomposition (SVD), and an extreme learning machine (ELM) [7] .  ...  Based on this, in 2019, Zhao et al. [23] first proposed using cyclic correntropy spectrum analysis for bearing failure detection.  ... 
doi:10.1109/access.2020.3034651 fatcat:lipqs3ii5jdhleugbbaow7mc2a

Deep Learning Algorithms for Bearing Fault Diagnostics – A Comprehensive Review

Shen Zhang, Shibo Zhang, Bingnan Wang, Thomas G. Habetler
2020 IEEE Access  
While conventional machine learning (ML) methods, including artificial neural network, principal component analysis, support vector machines, etc., have been successfully applied to the detection and categorization  ...  INDEX TERMS Bearing fault, deep learning, diagnostics, feature extraction, machine learning.  ...  to 40% of all the machine failures.  ... 
doi:10.1109/access.2020.2972859 fatcat:jrrbqanyj5d2vo7kdkdapl6hga

Machine Learning and Deep Learning Algorithms for Bearing Fault Diagnostics – A Comprehensive Review [article]

Shen Zhang, Shibo Zhang, Bingnan Wang, Thomas G. Habetler
2019 arXiv   pre-print
In this survey paper, we systematically summarize existing literature on bearing fault diagnostics with machine learning (ML) and data mining techniques.  ...  of bearing faults for decades, recent developments in deep learning (DL) algorithms in the last five years have sparked renewed interest in both industry and academia for intelligent machine health monitoring  ...  (JEMA) [7] reveal that bearing fault is the most common fault type and is responsible for 30% to 40 % percent of all the machine failures.  ... 
arXiv:1901.08247v2 fatcat:3aqshcdumjgjxkpj2o774tw3di

2021 Index IEEE Transactions on Circuits and Systems II: Express Briefs Vol. 68

2021 IEEE Transactions on Circuits and Systems - II - Express Briefs  
Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  ., +, TCSII Dec. 2021 3592-3596 Adversarial machine learning Adversarial Examples Detection of Radio Signals Based on Multifeature Fusion.  ... 
doi:10.1109/tcsii.2022.3144928 fatcat:bm53w7gva5bthholfhhiq4yg3a

Table of Contents

2021 2021 40th Chinese Control Conference (CCC)   unpublished
GUI Yuanyuan 1972 An Evolutionary Multi-Layer Extreme Learning Machine for Data Clustering Problems . . .  ...  CHEN Yadong, DING Xiangjun, WANG Jianan, WANG Chunyan, SHAN Jiayuan 7777 Collision Detection and Avoidance for Multi-UAV Based on Deep Reinforcement Learning . . . . . . . . .  ... 
doi:10.23919/ccc52363.2021.9550117 fatcat:55y7a2gagfhtpc6llmfvl7gqpm

CCC 2020 Contents

2020 2020 39th Chinese Control Conference (CCC)   unpublished
Delays Proceedings of the 39th Chinese Control Conference, July 27-29, 2020, Shenyang, China A Signal Analysis of Mill Shell Vibration Based on Variational Modal Decomposition . . . . . . . .  ...  TANG Jiangen, ZOU Yingyong, YU Jun, ZHANG Yongde 7235 Robust Adaptive Fixed-time Trajectory Tracking Control of Manipulator Based on Extreme Learning Machine . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.23919/ccc50068.2020.9188973 fatcat:7t2dwrbc3zdcjnyijypuga7yhe