Role of artificial intelligence in rotor fault diagnosis: a comprehensive review

Automatic Fault Classification for Journal Bearings Using ANN and DNN

(2023) T. Narendiranath Babu et al.   Archives of Acoustics

Application of EMD ANN and DNN for Self-Aligning Bearing Fault Diagnosis

(2023) Abhishek Rakesh et al.   Archives of Acoustics

Application of neural network algorithm in fault diagnosis of mechanical intelligence

(2020) Xianzhen Xu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Stepwise Intelligent Diagnosis Method for Rotor System with Sliding Bearing Based on Statistical Filter and Stacked Auto-Encoder

(2020) Haihong Tang et al.   Applied Sciences-Basel

Intelligent Fault Diagnosis of Multichannel Motor–Rotor System Based on Multimanifold Deep Extreme Learning Machine

(2020) Xiaoli Zhao et al.   IEEE-ASME TRANSACTIONS ON MECHATRONICS

Fault Diagnosis of Active Magnetic Bearing–Rotor System via Vibration Images

(2019) Xunshi Yan et al.   SENSORS

Fault Diagnosis of Induction Motors Using Recurrence Quantification Analysis and LSTM with Weighted BN

(2019) Dengyu Xiao et al.   SHOCK AND VIBRATION

A Precise Diagnosis Method of Structural Faults of Rotating Machinery based on Combination of Empirical Mode Decomposition, Sample Entropy, and Deep Belief Network

(2019) Zhaoyi Guan et al.   SENSORS

A Review of Early Fault Diagnosis Approaches and Their Applications in Rotating Machinery

(2019) Wei et al.   Entropy

Physics-Based Convolutional Neural Network for Fault Diagnosis of Rolling Element Bearings

(2019) Mohammadkazem Sadoughi et al.   IEEE SENSORS JOURNAL

Rotor fault diagnosis using a convolutional neural network with symmetrized dot pattern images

(2019) Xiaoxun Zhu et al.   MEASUREMENT

An SDP Characteristic Information Fusion-Based CNN Vibration Fault Diagnosis Method

(2019) Xiaoxun Zhu et al.   SHOCK AND VIBRATION

SDD-CNN: Small Data-Driven Convolution Neural Networks for Subtle Roller Defect Inspection

(2019) Xiaohang Xu et al.   Applied Sciences-Basel

Rotating machinery fault diagnosis based on convolutional neural network and infrared thermal imaging

(2019) Yongbo LI et al.   Chinese Journal of Aeronautics

Ensemble extreme learning machines for compound-fault diagnosis of rotating machinery

(2019) Xian-Bo Wang et al.   KNOWLEDGE-BASED SYSTEMS

An Integrated Approach to Rotating Machinery Fault Diagnosis Using, EEMD, SVM, and Augmented Data

(2019) Thiago H. G. Lobato et al.   Journal of Vibration Engineering & Technologies

Hydroelectric Generating Unit Fault Diagnosis Using 1-D Convolutional Neural Network and Gated Recurrent Unit in Small Hydro

(2019) Guo-Ping Liao et al.   IEEE SENSORS JOURNAL

Compound Fault Diagnosis of Gearboxes via Multi-label Convolutional Neural Network and Wavelet Transform

(2019) Pengfei Liang et al.   COMPUTERS IN INDUSTRY

Multi-Fault Bearing Classification Using Sensors and ConvNet-Based Transfer Learning Approach

(2019) Sandeep S. Udmale et al.   IEEE SENSORS JOURNAL

An Industrial Internet Application for Real-Time Fault Diagnosis in Industrial Motors

(2019) Saul Langarica et al.   IEEE Transactions on Automation Science and Engineering

Modelling of shaft unbalance: Modelling a multi discs rotor using K-Nearest Neighbor and Decision Tree Algorithms

(2019) Mohammad Gohari et al.   MEASUREMENT

Tackling Faults in the Industry 4.0 Era—A Survey of Machine-Learning Solutions and Key Aspects

(2019) Angelos Angelopoulos et al.   SENSORS

In Situ Motor Fault Diagnosis Using Enhanced Convolutional Neural Network in an Embedded System

(2019) Siliang Lu et al.   IEEE SENSORS JOURNAL

Acoustic based fault diagnosis of three-phase induction motor

(2018) Adam Glowacz   APPLIED ACOUSTICS

An Experimental Comparative Evaluation of Machine Learning Techniques for Motor Fault Diagnosis Under Various Operating Conditions

(2018) Ignacio Martin-Diaz et al.   IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS

Machine health management in smart factory: A review

(2018) Gil-Yong Lee et al.   Journal of Mechanical Science and Technology

Fault detection of broken rotor bar in LS-PMSM using random forests

(2018) Juan C. Quiroz et al.   MEASUREMENT

Artificial intelligence for fault diagnosis of rotating machinery: A review

(2018) Ruonan Liu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Rolling bearing fault feature learning using improved convolutional deep belief network with compressed sensing

(2018) Haidong Shao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

New Fault Recognition Method for Rotary Machinery Based on Information Entropy and a Probabilistic Neural Network

(2018) Quansheng Jiang et al.   SENSORS

A Novel Fault Diagnosis Method for Rotating Machinery Based on a Convolutional Neural Network

(2018) Sheng Guo et al.   SENSORS

Prognostics and Health Management: A Review of Vibration Based Bearing and Gear Health Indicators

(2018) Dong Wang et al.   IEEE Access

Fault Diagnosis Based on an Approach Combining a Spectrogram and a Convolutional Neural Network with Application to a Wind Turbine System

(2018) Wenxin Yu et al.   Energies

Literature review of Industry 4.0 and related technologies

(2018) Ercan Oztemel et al.   JOURNAL OF INTELLIGENT MANUFACTURING

A novel fusion diagnosis method for rotor system fault based on deep learning and multi-sourced heterogeneous monitoring data

(2018) Zhuang Yuan et al.   MEASUREMENT SCIENCE and TECHNOLOGY

A deep learning driven method for fault classification and degradation assessment in mechanical equipment

(2018) Zhe Li et al.   COMPUTERS IN INDUSTRY

Rotor Fault Diagnosis Based on Characteristic Frequency Band Energy Entropy and Support Vector Machine

(2018) Bin Pang et al.   Entropy

Deep learning and its applications to machine health monitoring

(2018) Rui Zhao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A bearing vibration data analysis based on spectral kurtosis and ConvNet

(2018) Sandeep S. Udmale et al.   SOFT COMPUTING

An adaptive spatiotemporal feature learning approach for fault diagnosis in complex systems

(2018) Te Han et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A support vector machine based fault diagnostics of Induction motors for practical situation of multi-sensor limited data case

(2018) Purushottam Gangsar et al.   MEASUREMENT

A novel adversarial learning framework in deep convolutional neural network for intelligent diagnosis of mechanical faults

(2018) Te Han et al.   KNOWLEDGE-BASED SYSTEMS

Fault diagnosis of wind turbine based on Long Short-term memory networks

(2018) Jinhao Lei et al.   RENEWABLE ENERGY

Quantitative and Localization Diagnosis of a Defective Ball Bearing Based on Vertical–Horizontal Synchronization Signal Analysis

(2017) Lingli Cui et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Dislocated Time Series Convolutional Neural Architecture: An Intelligent Fault Diagnosis Approach for Electric Machine

(2017) Ruonan Liu et al.   IEEE Transactions on Industrial Informatics

Convolutional Discriminative Feature Learning for Induction Motor Fault Diagnosis

(2017) Wenjun Sun et al.   IEEE Transactions on Industrial Informatics

Early Fault Detection in Induction Motors Using AdaBoost With Imbalanced Small Data and Optimized Sampling

(2017) Ignacio Martin-Diaz et al.   IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS

Artificial neural network and empirical mode decomposition based imbalance fault diagnosis of wind turbine using TurbSim, FAST and Simulink

(2017) Hasmat Malik et al.   IET Renewable Power Generation

An enhancement deep feature fusion method for rotating machinery fault diagnosis

(2017) Haidong Shao et al.   KNOWLEDGE-BASED SYSTEMS

A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals

(2017) Wei Zhang et al.   SENSORS

Multiple-fault diagnosis in induction motors through support vector machine classification at variable operating conditions

(2016) José D. Martínez-Morales et al.   ELECTRICAL ENGINEERING

Representational Learning for Fault Diagnosis of Wind Turbine Equipment: A Multi-Layered Extreme Learning Machines Approach

(2016) Zhi-Xin Yang et al.   Energies

A new support vector data description method for machinery fault diagnosis with unbalanced datasets

(2016) Lixiang Duan et al.   EXPERT SYSTEMS WITH APPLICATIONS

An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big Data

(2016) Yaguo Lei et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks

(2016) Turker Ince et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Application of intelligent tools to detect and classify broken rotor bars in three-phase induction motors fed by an inverter

(2016) Wagner Fontes Godoy et al.   IET Electric Power Applications

Segmented infrared image analysis for rotating machinery fault diagnosis

(2016) Lixiang Duan et al.   INFRARED PHYSICS & TECHNOLOGY

Convolutional Neural Network Based Fault Detection for Rotating Machinery

(2016) Olivier Janssens et al.   JOURNAL OF SOUND AND VIBRATION

Theoretical and bifurcation analysis of a flexible rotor supported by gas-lubricated bearing system with porous bushing

(2016) Cheng-Chi Wang et al.   Journal of Vibroengineering

A sparse auto-encoder-based deep neural network approach for induction motor faults classification

(2016) Wenjun Sun et al.   MEASUREMENT

A comprehensive evaluation of intelligent classifiers for fault identification in three-phase induction motors

(2015) Rodrigo H. Cunha Palácios et al.   ELECTRIC POWER SYSTEMS RESEARCH

A Symbolic Representation Approach for the Diagnosis of Broken Rotor Bars in Induction Motors

(2015) Petros Karvelis et al.   IEEE Transactions on Industrial Informatics

Thermal image based fault diagnosis for rotating machinery

(2015) Olivier Janssens et al.   INFRARED PHYSICS & TECHNOLOGY

Fault diagnosis approach for rotating machinery based on dynamic model and computational intelligence

(2015) Junhong Zhang et al.   MEASUREMENT

Fault diagnosis of rotating machinery with a novel statistical feature extraction and evaluation method

(2015) Wei Li et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Knowledge extraction using data mining for multi-class fault diagnosis of induction motor

(2015) Pratyay Konar et al.   NEUROCOMPUTING

Industry 4.0 as a Cyber-Physical System study

(2015) Pieter J. Mosterman et al.   Software and Systems Modeling

Reliable Fault Classification of Induction Motors Using Texture Feature Extraction and a Multiclass Support Vector Machine

(2014) Jia Uddin et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

Unbalance localization through machine nonlinearities using an artificial neural network approach

(2014) R.B. Walker et al.   MECHANISM AND MACHINE THEORY

Analysis of Dynamic Characteristics for a Rotor System with Pedestal Looseness

(2014) Hui Ma et al.   SHOCK AND VIBRATION

Quantitative Diagnosis of Rotor Vibration Fault Using Process Power Spectrum Entropy and Support Vector Machine Method

(2014) Cheng-Wei Fei et al.   SHOCK AND VIBRATION

Real-time condition monitoring on VSD-fed induction motors through statistical analysis and synchronous speed observation

(2014) Eduardo Cabal-Yepez et al.   International Transactions on Electrical Energy Systems

Wind turbine fault detection based on SCADA data analysis using ANN

(2014) Zhen-You Zhang et al.   Advances in Manufacturing

Broken rotor bar diagnosis in induction machines through stationary wavelet packet transform and multiclass wavelet SVM

(2013) Hassen Keskes et al.   ELECTRIC POWER SYSTEMS RESEARCH

Singular value decomposition based feature extraction approaches for classifying faults of induction motors

(2013) Myeongsu Kang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Rotor Faults Diagnosis Using Feature Selection and Nearest Neighbors Rule: Application to a Turbogenerator

(2012) Melisande Biet   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Study of open crack in rotor shaft using changes in frequency response function phase

(2012) Abdul Ghaffar Abdul Rahman et al.   INTERNATIONAL JOURNAL OF DAMAGE MECHANICS

Current envelope analysis for defect identification and diagnosis in induction motors

(2012) Jinjiang Wang et al.   JOURNAL OF MANUFACTURING SYSTEMS

Automatic diagnosis method for structural fault of rotating machinery based on distinctive frequency components and support vector machines under varied operating conditions

(2012) Hongtao Xue et al.   NEUROCOMPUTING

Spectral Regression Based Fault Feature Extraction for Bearing Accelerometer Sensor Signals

(2012) Zhanguo Xia et al.   SENSORS

Rotor fault diagnosis system based on sGA-based individual neural networks

(2011) Chin-Sheng Chen et al.   EXPERT SYSTEMS WITH APPLICATIONS

Intelligent fault inference for rotating flexible rotors using Bayesian belief network

(2011) Bin Gang Xu   EXPERT SYSTEMS WITH APPLICATIONS

Intelligent fault diagnosis of rotating machinery using infrared thermal image

(2011) Ali M.D. Younus et al.   EXPERT SYSTEMS WITH APPLICATIONS

Early fault diagnosis of rotating machinery based on wavelet packets—Empirical mode decomposition feature extraction and neural network

(2011) G.F. Bin et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

SVM practical industrial application for mechanical faults diagnostic

(2010) Lane Maria Rabelo Baccarini et al.   EXPERT SYSTEMS WITH APPLICATIONS

Induction motor fault diagnosis based on thek-NN and optimal feature selection

(2010) Ngoc-Tu Nguyen et al.   INTERNATIONAL JOURNAL OF ELECTRONICS

Multi-fault classification based on support vector machine trained by chaos particle swarm optimization

(2010) Xianlun Tang et al.   KNOWLEDGE-BASED SYSTEMS

Diagnostics of gear faults based on EMD and automatic selection of intrinsic mode functions

(2010) Roberto Ricci et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Development of smart sensors system for machine fault diagnosis

(2009) Jong-Duk Son et al.   EXPERT SYSTEMS WITH APPLICATIONS

Online Detection of Broken Rotor Bars in Induction Motors by Wavelet Packet Decomposition and Artificial Neural Networks

(2009) A. Sadeghian et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Vibration response of misaligned rotors

(2009) Tejas H. Patel et al.   JOURNAL OF SOUND AND VIBRATION

Coupled bending-torsional vibration analysis of rotor with rub and crack

(2009) Tejas H. Patel et al.   JOURNAL OF SOUND AND VIBRATION

Support vector machine for fault diagnosis of the broken rotor bars of squirrel-cage induction motor

(2009) Jaroslaw Kurek et al.   NEURAL COMPUTING & APPLICATIONS

Optimal feature selection using genetic algorithm for mechanical fault detection of induction motor

(2008) Ngoc-Tu Nguyen et al.   Journal of Mechanical Science and Technology

Fault detection using transient machine signals

(2008) Markus Timusk et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Model-based identification of rotating machines

(2008) A.W. Lees et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Improvement of induction motor fault diagnosis performance by using genetic algorithm-based feature selection

(2008) N-T Nguyen et al.   PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE

Wavelet support vector machine for induction machine fault diagnosis based on transient current signal

(2007) A WIDODO et al.   EXPERT SYSTEMS WITH APPLICATIONS

Decision-level fusion based on wavelet decomposition for induction motor fault diagnosis using transient current signal

(2007) Gang Niu et al.   EXPERT SYSTEMS WITH APPLICATIONS

A new approach to intelligent fault diagnosis of rotating machinery

(2007) Yaguo Lei et al.   EXPERT SYSTEMS WITH APPLICATIONS