A Novel End-To-End Fault Diagnosis Approach for Rolling Bearings by Integrating Wavelet Packet Transform into Convolutional Neural Network Structures

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

Deep convolutional neural network based planet bearing fault classification

(2019) Dezun Zhao et al.   COMPUTERS IN INDUSTRY

A Lighted Deep Convolutional Neural Network Based Fault Diagnosis of Rotating Machinery

(2019) Shangjun Ma et al.   SENSORS

A bearing fault and severity diagnostic technique using adaptive deep belief networks and Dempster–Shafer theory

(2019) Kun Yu et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Sensor Data-Driven Bearing Fault Diagnosis Based on Deep Convolutional Neural Networks and S-Transform

(2019) Guoqiang Li et al.   SENSORS

An improved deep network for intelligent diagnosis of machinery faults with similar features

(2019) Jing Yang et al.   IEEJ Transactions on Electrical and Electronic Engineering

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

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

Estimation of Bearing Remaining Useful Life based on Multiscale Convolutional Neural Network

(2018) Jun Zhu et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Deep Residual Networks With Dynamically Weighted Wavelet Coefficients for Fault Diagnosis of Planetary Gearboxes

(2018) Minghang Zhao et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Early fault diagnosis of rolling bearings based on hierarchical symbol dynamic entropy and binary tree support vector machine

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

Combined deep belief network in deep learning with affinity propagation clustering algorithm for roller bearings fault diagnosis without data label

(2018) Fan Xu et al.   JOURNAL OF VIBRATION AND CONTROL

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

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

A review on data-driven fault severity assessment in rolling bearings

(2018) Mariela Cerrada et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A Novel Fault Diagnosis Method Based on Integrating Empirical Wavelet Transform and Fuzzy Entropy for Motor Bearing

(2018) Wu Deng et al.   IEEE Access

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

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

Intelligent fault detection using raw vibration signals via dilated convolutional neural networks

(2018) Mohammad Azam Khan et al.   JOURNAL OF SUPERCOMPUTING

Deep learning and its applications to machine health monitoring

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

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

Multi-feature entropy distance approach with vibration and acoustic emission signals for process feature recognition of rolling element bearing faults

(2017) Cheng-Wei Fei et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

A New Deep Transfer Learning Based on Sparse Auto-Encoder for Fault Diagnosis

(2017) Long Wen et al.   IEEE Transactions on Systems Man Cybernetics-Systems

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

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

Hierarchical adaptive deep convolution neural network and its application to bearing fault diagnosis

(2016) Xiaojie Guo et al.   MEASUREMENT

Fault detection in rotor bearing systems using time frequency techniques

(2016) N. Harish Chandra et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Construction of hierarchical diagnosis network based on deep learning and its application in the fault pattern recognition of rolling element bearings

(2016) Meng Gan 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

Bearing Health Monitoring Based on Hilbert–Huang Transform, Support Vector Machine, and Regression

(2015) Abdenour Soualhi et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Using supervised kernel entropy component analysis for fault diagnosis of rolling bearings

(2015) Hongdi Zhou et al.   JOURNAL OF VIBRATION AND CONTROL

A novel bearing fault diagnosis model integrated permutation entropy, ensemble empirical mode decomposition and optimized SVM

(2015) Xiaoyuan Zhang 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

Detection of weak transient signals based on wavelet packet transform and manifold learning for rolling element bearing fault diagnosis

(2015) Yi Wang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Bearing Fault Detection by a Novel Condition-Monitoring Scheme Based on Statistical-Time Features and Neural Networks

(2012) Miguel Delgado Prieto et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

An enhanced Kurtogram method for fault diagnosis of rolling element bearings

(2012) Dong Wang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING