Walter Sextro

Deep learning algorithms for rotating machinery intelligent diagnosis: An open source benchmark study

A survey of wheel–rail contact models for rail vehicles

A convolutional neural network based on a capsule network with strong generalization for bearing fault diagnosis

Predictive maintenance in the Industry 4.0: A systematic literature review

Train–track–bridge dynamic interaction: a state-of-the-art review

ACDIN: Bridging the gap between artificial and real bearing damages for bearing fault diagnosis

Machinery health prognostics: A systematic review from data acquisition to RUL prediction

Intelligent fault diagnosis of rolling bearings based on normalized CNN considering data imbalance and variable working conditions

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

Prognostics and Health Management for Maintenance Practitioners - Review, Implementation and Tools Evaluation

A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings

An Enhanced Intelligent Diagnosis Method Based on Multi-Sensor Image Fusion via Improved Deep Learning Network

An approach for feature extraction and selection from non-trending data for machinery prognosis

Condition Monitoring of Bearing Damage in Electromechanical Drive Systems by Using Motor Current Signals of Electric Motors: A Benchmark Data Set for Data-Driven Classification

Machinery Prognostic Method Based on Multi-Class Support Vector Machines and Hybrid Differential Evolution – Particle Swarm Optimization

Friction in wheel–rail contact: A model comprising interfacial fluids, surface roughness and temperature