Mechanical fault intelligent diagnosis using attention-based dual-scale feature fusion capsule network

Deep multi-scale adversarial network with attention: A novel domain adaptation method for intelligent fault diagnosis

(2021) Bo Zhao et al.   JOURNAL OF MANUFACTURING SYSTEMS

Combination bidirectional long short-term memory and capsule network for rotating machinery fault diagnosis

(2021) Tian Han et al.   MEASUREMENT

Gearbox fault diagnosis based on Multi-Scale deep residual learning and stacked LSTM model

(2021) K.N. Ravikumar et al.   MEASUREMENT

Fault diagnosis of rotating machinery based on dual convolutional-capsule network (DC-CN)

(2021) DeCai Li et al.   MEASUREMENT

Multi-scale dynamic adaptive residual network for fault diagnosis

(2021) Haopeng Liang et al.   MEASUREMENT

Sparse Representation Convolutional Autoencoder for Feature Learning of Vibration Signals and its Applications in Machinery Fault Diagnosis

(2021) Mengqi Miao et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

A Robust Weight-Shared Capsule Network for Intelligent Machinery Fault Diagnosis

(2020) Ruyi Huang et al.   IEEE Transactions on Industrial Informatics

Actual bearing compound fault diagnosis based on active learning and decoupling attentional residual network

(2020) Yanrui Jin et al.   MEASUREMENT

Motor fault diagnosis using attention mechanism and improved adaboost driven by multi-sensor information

(2020) Zhuo Long et al.   MEASUREMENT

A multi-stage semi-supervised learning approach for intelligent fault diagnosis of rolling bearing using data augmentation and metric learning

(2020) Kun Yu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Fault diagnosis of rolling bearings using an Improved Multi-Scale Convolutional Neural Network with Feature Attention mechanism

(2020) Zifei Xu et al.   ISA TRANSACTIONS

Fault Diagnosis of an Autonomous Vehicle With an Improved SVM Algorithm Subject to Unbalanced Datasets

(2020) Qian Shi et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

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

(2019) Xiang Li et al.   SIGNAL PROCESSING

A deep capsule neural network with stochastic delta rule for bearing fault diagnosis on raw vibration signals

(2019) Tianyou Chen et al.   MEASUREMENT

Generalization of deep neural network for bearing fault diagnosis under different working conditions using multiple kernel method

(2019) Zenghui An et al.   NEUROCOMPUTING

Multiscale local features learning based on BP neural network for rolling bearing intelligent fault diagnosis

(2019) Jimeng Li et al.   MEASUREMENT

A reinforcement neural architecture search method for rolling bearing fault diagnosis

(2019) Ruixin Wang et al.   MEASUREMENT

Deep Ensemble Capsule Network for Intelligent Compound Fault Diagnosis Using Multisensory Data

(2019) Ruyi Huang et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Rolling Bearing Fault Diagnosis based on an Improved Denoising Method Using the Complete Ensemble Empirical Mode Decomposition and the Optimized Thresholding Operation

(2018) Rabah Abdelkader et al.   IEEE SENSORS JOURNAL

Margin Loss: Making Faces More Separable

(2018) Riqiang Gao et al.   IEEE SIGNAL PROCESSING LETTERS

A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method

(2018) Long Wen et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Multiscale Convolutional Neural Networks for Fault Diagnosis of Wind Turbine Gearbox

(2018) Guoqian Jiang et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Fault diagnosis of rolling bearings with recurrent neural network-based autoencoders

(2018) Han Liu et al.   ISA TRANSACTIONS

Intelligent fault diagnosis of rolling bearings using an improved deep recurrent neural network

(2018) Hongkai Jiang et al.   MEASUREMENT SCIENCE and TECHNOLOGY

Mechanical model development of rolling bearing-rotor systems: A review

(2018) Hongrui Cao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

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

An intelligent diagnosis scheme based on generative adversarial learning deep neural networks and its application to planetary gearbox fault pattern recognition

(2018) Zirui Wang et al.   NEUROCOMPUTING

Intelligent fault diagnosis of rotating machinery using improved multiscale dispersion entropy and mRMR feature selection

(2018) Xiaoan Yan et al.   KNOWLEDGE-BASED SYSTEMS

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

(2018) Zhiyu Zhu et al.   NEUROCOMPUTING

A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings

(2018) Biao Wang et al.   IEEE TRANSACTIONS ON RELIABILITY

Rolling bearing fault diagnosis based on partially ensemble empirical mode decomposition and variable predictive model-based class discrimination

(2016) Jinde Zheng   Archives of Civil and Mechanical Engineering

Manifold learning-based subspace distance for machinery damage assessment

(2016) Chuang Sun et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

An Improved Exponential Model for Predicting Remaining Useful Life of Rolling Element Bearings

(2015) Naipeng Li et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

An improved EEMD with multiwavelet packet for rotating machinery multi-fault diagnosis

(2013) Hongkai Jiang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING