Joint loss learning-enabled semi-supervised autoencoder for bearing fault diagnosis under limited labeled vibration signals

CNN parameter design based on fault signal analysis and its application in bearing fault diagnosis

(2023) Diwang Ruan et al.   ADVANCED ENGINEERING INFORMATICS

Fault diagnosis of rolling bearing based on online transfer convolutional neural network

(2022) Quansheng Xu et al.   APPLIED ACOUSTICS

A hierarchical deep learning framework for combined rolling bearing fault localization and identification with data fusion

(2022) Mingxuan Liang et al.   JOURNAL OF VIBRATION AND CONTROL

Deep convolutional generative adversarial network with semi-supervised learning enabled physics elucidation for extended gear fault diagnosis under data limitations

(2022) Kai Zhou et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Harnessing fuzzy neural network for gear fault diagnosis with limited data labels

(2021) Kai Zhou et al.   The International Journal of Advanced Manufacturing Technology

A new dynamic model and transfer learning based intelligent fault diagnosis framework for rolling element bearings race faults: Solving the small sample problem

(2021) Yunjia Dong et al.   ISA TRANSACTIONS

ANS-net: anti-noise Siamese network for bearing fault diagnosis with a few data

(2021) Qin Fang et al.   NONLINEAR DYNAMICS

Probabilistic bearing fault diagnosis using Gaussian process with tailored feature extraction

(2021) Mingxuan Liang et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

An improved empirical wavelet transform and sensitive components selecting method for bearing fault

(2021) Qingqing Liu et al.   MEASUREMENT

A semi-supervised GAN method for RUL prediction using failure and suspension histories

(2021) Rui He et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Multispecies bioacoustic classification using transfer learning of deep convolutional neural networks with pseudo-labeling

(2020) Ming Zhong et al.   APPLIED ACOUSTICS

Interpreting network knowledge with attention mechanism for bearing fault diagnosis

(2020) Zhi-bo Yang et al.   APPLIED SOFT COMPUTING

Generative adversarial networks

(2020) Ian Goodfellow et al.   COMMUNICATIONS OF THE ACM

Structural model updating using adaptive multi-response Gaussian process meta-modeling

(2020) K. Zhou et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Bearing Fault Diagnosis of a PWM Inverter Fed-Induction Motor Using an Improved Short Time Fourier Transform

(2019) Mohammed-El-Amine Khodja et al.   Journal of Electrical Engineering & Technology

An improved deep convolutional neural network with multi-scale information for bearing fault diagnosis

(2019) Wenyi Huang et al.   NEUROCOMPUTING

Multitask Convolutional Neural Network With Information Fusion for Bearing Fault Diagnosis and Localization

(2019) Sheng Guo et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

A Generic Intelligent Bearing Fault Diagnosis System Using Compact Adaptive 1D CNN Classifier

(2018) Levent Eren et al.   Journal of Signal Processing Systems for Signal Image and Video Technology

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

Envelope analysis of rotating machine vibrations in variable speed conditions: A comprehensive treatment

(2017) D. Abboud et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Incipient Fault Diagnosis of Roller Bearing Using Optimized Wavelet Transform Based Multi-Speed Vibration Signatures

(2017) Zhiqiang Huo et al.   IEEE Access

Vibration signal models for fault diagnosis of planet bearings

(2016) Zhipeng Feng et al.   JOURNAL OF SOUND AND VIBRATION

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

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

Neural network approach for damaged area location prediction of a composite plate using electromechanical impedance technique

(2013) S. Na et al.   COMPOSITES SCIENCE AND TECHNOLOGY