Publications, Activities, and Awards
- A deep bi-directional long short-term memory model for automatic rotating speed extraction from raw vibration signals
- A new strategy for rotating machinery fault diagnosis under varying speed conditions based on deep neural networks and order tracking
- A speed normalized autoencoder for rotating machinery fault detection under varying speed conditions
- Aluminum structure crack length estimation and prediction
- Aluminum structure crack length estimation and prediction
- Physics-Informed LSTM Hyperparameters Selection for Gearbox Fault Detection
- Scholarship
- Speed adaptive gates: Improving fault classification accuracy of deep learning models for rotating machinery under varying speed conditions
- Structure fatigue crack length estimation and prediction using ultrasonic wave data based on ensemble linear regression and Paris’s law
- Virtual rotating speed meter: Extracting machinery rotating speed from vibration signals based on deep learning and transfer learning
- Virtual Rotating Speed Meter: Extracting Machinery Rotating Speed from Vibration Signals Based on Deep Learning and Transfer Learning