Deep learning for diagnosis and classification of faults in industrial rotating machinery

Forecasting fault events for predictive maintenance using data-driven techniques and ARMA modeling

(2018) Marcia Baptista et al.   COMPUTERS & INDUSTRIAL ENGINEERING

Improved similarity-based modeling for the classification of rotating-machine failures

(2018) Matheus A. Marins et al.   JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS

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

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 reliable technique for remaining useful life estimation of rolling element bearings using dynamic regression models

(2018) Wasim Ahmad et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Deep learning and its applications to machine health monitoring

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

Convolutional Neural Network Based Fault Detection for Rotating Machinery

(2016) Olivier Janssens et al.   JOURNAL OF SOUND AND VIBRATION

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

(2016) Xiaojie Guo et al.   MEASUREMENT

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

(2016) Francisco Ordóñez et al.   SENSORS