A new bearing fault diagnosis method based on signal-to-image mapping and convolutional neural network

A deep learning method for bearing fault diagnosis based on Cyclic Spectral Coherence and Convolutional Neural Networks

(2020) Zhuyun Chen et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Damage detection in a novel deep-learning framework: a robust method for feature extraction

(2019) Tian Guo et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

A new bearing fault diagnosis method based on modified convolutional neural networks

(2019) Jiangquan ZHANG et al.   Chinese Journal of Aeronautics

Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization

(2019) Ramprasaath R. Selvaraju et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Mechanical fault diagnosis using Convolutional Neural Networks and Extreme Learning Machine

(2019) Zhuyun Chen et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Remaining Useful Life Estimation of Structure Systems Under the Influence of Multiple Causes: Subsea Pipelines as a Case Study

(2019) Baoping Cai et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

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

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

Intelligent fault diagnosis of rolling bearing using deep wavelet auto-encoder with extreme learning machine

(2018) Shao Haidong et al.   KNOWLEDGE-BASED SYSTEMS

Non-stationary vibration feature extraction method based on sparse decomposition and order tracking for gearbox fault diagnosis

(2018) Yongzhuo Li et al.   MEASUREMENT

Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization

(2018) Feng Jia 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

A review on the application of deep learning in system health management

(2018) Samir Khan et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load

(2018) Wei Zhang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A neural network constructed by deep learning technique and its application to intelligent fault diagnosis of machines

(2018) Feng Jia et al.   NEUROCOMPUTING

Deep Learning and Computational Neuroscience

(2018) Erik De Schutter   NEUROINFORMATICS

Deep learning and its applications to machine health monitoring

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

A Dynamic-Bayesian-Network-Based Fault Diagnosis Methodology Considering Transient and Intermittent Faults

(2017) Baoping Cai et al.   IEEE Transactions on Automation Science and Engineering

Rolling bearing fault detection and diagnosis based on composite multiscale fuzzy entropy and ensemble support vector machines

(2017) Jinde Zheng et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification

(2017) Chen Lu et al.   SIGNAL PROCESSING

A real-time fault diagnosis methodology of complex systems using object-oriented Bayesian networks

(2016) Baoping Cai et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data

(2016) Feng Jia et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Application of fuzzy C-means method and classification model of optimized K-nearest neighbor for fault diagnosis of bearing

(2015) Shaojiang Dong et al.   Journal of the Brazilian Society of Mechanical Sciences and Engineering

Multiple-domain manifold for feature extraction in machinery fault diagnosis

(2015) Meng Gan et al.   MEASUREMENT

Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study

(2015) Wade A. Smith et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

Multi-fault diagnosis for rolling element bearings based on ensemble empirical mode decomposition and optimized support vector machines

(2013) Xiaoyuan Zhang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Support vector machine with genetic algorithm for machinery fault diagnosis of high voltage circuit breaker

(2011) Jian Huang et al.   MEASUREMENT

Random forests classifier for machine fault diagnosis

(2009) Bo-Suk Yang et al.   Journal of Mechanical Science and Technology