A.M. Pertew

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

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

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

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

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

A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches

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

On design of quantized fault detection filters with randomly occurring nonlinearities and mixed time-delays

LMI-based sensor fault diagnosis for nonlinear Lipschitz systems