Stable and explainable deep learning damage prediction for prismatic cantilever steel beam

Fault-Attention Generative Probabilistic Adversarial Autoencoder for Machine Anomaly Detection

(2020) Jingyao Wu et al.   IEEE Transactions on Industrial Informatics

A novel unsupervised deep learning model for global and local health condition assessment of structures

(2018) Mohammad Hossein Rafiei et al.   ENGINEERING STRUCTURES

Deep learning and its applications to machine health monitoring

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

A deep learning approach to condition monitoring of cantilever beams via time-frequency extended signatures

(2018) Habil. Darian M. Onchis   COMPUTERS IN INDUSTRY

Deep Fault Recognizer: An Integrated Model to Denoise and Extract Features for Fault Diagnosis in Rotating Machinery

(2016) Xiaojie Guo et al.   Applied Sciences-Basel

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

Observing damaged beams through their time–frequency extended signatures

(2013) Darian Onchis   SIGNAL PROCESSING

Vibration analysis of rotating machinery using time–frequency analysis and wavelet techniques

(2011) F. Al-Badour et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

THE FLEXIBLE GABOR-WAVELET TRANSFORM FOR CAR CRASH SIGNAL ANALYSIS

(2009) DARIAN M. ONCHIŞ et al.   International Journal of Wavelets Multiresolution and Information Processing