Cross‐machine intelligent fault diagnosis of gearbox based on deep learning and parameter transfer

Damage‐sensitive feature extraction with stacked autoencoders for unsupervised damage detection

(2021) Moisés Felipe Silva et al.   Structural Control & Health Monitoring

Deep transfer learning with limited data for machinery fault diagnosis

(2021) Te Han et al.   APPLIED SOFT COMPUTING

A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges

(2021) Weihua Li et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Applications of machine learning to machine fault diagnosis: A review and roadmap

(2020) Yaguo Lei et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Bearing fault diagnosis base on multi-scale CNN and LSTM model

(2020) Xiaohan Chen et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Deep learning algorithms for rotating machinery intelligent diagnosis: An open source benchmark study

(2020) Zhibin Zhao et al.   ISA TRANSACTIONS

Understanding and Improving Deep Learning-Based Rolling Bearing Fault Diagnosis with Attention Mechanism

(2019) Xiang Li et al.   SIGNAL PROCESSING

Fault diagnosis of rolling element bearing based on artificial neural network

(2019) Rohit S. Gunerkar et al.   Journal of Mechanical Science and Technology

Automated bearing fault diagnosis scheme using 2D representation of wavelet packet transform and deep convolutional neural network

(2019) M.M. Manjurul Islam et al.   COMPUTERS IN INDUSTRY

Acoustic spectral imaging and transfer learning for reliable bearing fault diagnosis under variable speed conditions

(2019) Md Junayed Hasan et al.   MEASUREMENT

A novel gas turbine fault diagnosis method based on transfer learning with CNN

(2019) Shi-sheng Zhong et al.   MEASUREMENT

An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings

(2019) Bin Yang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Transfer learning with convolutional neural networks for small sample size problem in machinery fault diagnosis

(2019) Dengyu Xiao et al.   PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE

Transfer Learning Based Fault Diagnosis with Missing Data Due to Multi-Rate Sampling

(2019) Danmin Chen et al.   SENSORS

ReLTanh: An activation function with vanishing gradient resistance for SAE-based DNNs and its application to rotating machinery fault diagnosis

(2019) Xin Wang et al.   NEUROCOMPUTING

A diagnosis framework based on domain adaptation for bearing fault diagnosis across diverse domains

(2019) Ping Ma et al.   ISA TRANSACTIONS

Deep transfer network with joint distribution adaptation: A new intelligent fault diagnosis framework for industry application

(2019) Te Han et al.   ISA TRANSACTIONS

A domain adaptation model for early gear pitting fault diagnosis based on deep transfer learning network

(2019) Jialin Li et al.   Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability

Support vector machines based non-contact fault diagnosis system for bearings

(2019) Deepam Goyal et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Particle filtering‐based adaptive training of neural networks for real‐time structural damage diagnosis and prognosis

(2019) Francesco Cadini et al.   Structural Control & Health Monitoring

Gear pitting severity level identification using binary segmentation methodology

(2019) Pradeep Kundu et al.   Structural Control & Health Monitoring

Entropy Based Fault Classification Using the Case Western Reserve University Data: A Benchmark Study

(2019) Yongbo Li et al.   IEEE TRANSACTIONS ON RELIABILITY

Intelligent fault diagnosis method for rotating machinery via dictionary learning and sparse representation-based classification

(2018) Te Han et al.   MEASUREMENT

Multi-level wavelet packet fusion in dynamic ensemble convolutional neural network for fault diagnosis

(2018) Yan Han et al.   MEASUREMENT

An integrated multi-sensor fusion-based deep feature learning approach for rotating machinery diagnosis

(2018) Jie Liu et al.   MEASUREMENT SCIENCE and TECHNOLOGY

A novel tracking deep wavelet auto-encoder method for intelligent fault diagnosis of electric locomotive bearings

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

An automatic and robust features learning method for rotating machinery fault diagnosis based on contractive autoencoder

(2018) Changqing Shen et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

A fault diagnosis method for planetary gearboxes under non-stationary working conditions using improved Vold-Kalman filter and multi-scale sample entropy

(2018) Yongbo Li et al.   JOURNAL OF SOUND AND VIBRATION

A Convolutional Neural Network Based on a Capsule Network with Strong Generalization for Bearing Fault Diagnosis

(2018) Zhiyu Zhu et al.   NEUROCOMPUTING

Deep residual learning-based fault diagnosis method for rotating machinery

(2018) Wei Zhang et al.   ISA TRANSACTIONS

Identification of mechanical compound-fault based on the improved parameter-adaptive variational mode decomposition

(2018) Yonghao Miao et al.   ISA TRANSACTIONS

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

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

A review of stochastic resonance in rotating machine fault detection

(2018) Siliang Lu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

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

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

Time-frequency analysis and support vector machine in automatic detection of defect from vibration signal of centrifugal pump

(2017) Anil Kumar et al.   MEASUREMENT

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

Comparison of random forest, artificial neural networks and support vector machine for intelligent diagnosis of rotating machinery

(2017) Te Han et al.   TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL

Rolling bearing fault diagnosis under fluctuant conditions based on compressed sensing

(2016) Hang Yuan et al.   Structural Control & Health Monitoring

Residual life prediction for ball bearings based on joint approximate diagonalization of eigen matrices and extreme learning machine

(2015) Fang Liu et al.   PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE