PhD academic projects in The University of Manchester
Under the supervision of Dr Robert Heinemann and Otto Jan Bakker.
Minimal deep learning system for real-time tool condition monitoring in stacked drilling.
Minimal Deep Learning System for Stacked Drilling
Deep Learning, Embedded Device, Real-time
An online cloud computing framework for real-time tool condition monitoring.
Exponential Backoff Producer-Consumer Framework
Deep Learning, Cloud Computing, Real-time
The basic signal unit representing events in machining processes.
Minimum Sufficient Signal Condition
Deep Learning, Machine Signal
Accurate and interpretable process incidence identification using support vector machines.
SVM in Process Incidence Identification
Machine Learning, Feature Analysis, Process Monitoring
Remove size limits of perceived signals for real-time process incidence identification.
TPP in Process Incidence Identification
Deep Learning, Tool Wear, Process Monitoring
Achieve multi-objective prediction in one unified model.
Multi-objective Prediction in Hybrid Stacks
Deep Learning, Tool Wear, Process Monitoring
MEng academic projects in Northwestern Polytechnical University
Under the supervision of Prof. Rong Mo and Huibin Sun.
Predict the future tendency of tool wear evolution in an online way.
LSTM-based Tool Wear Forecast
Deep Learning, Tool Wear Forecast, Long-short Term Memory
A fast and accurate CNN model to monitor tool wear during machining processes.
Tool Wear Monitoring in Multiple Conditions
Deep Learning, Machine Tool, Tool Wear Monitoring, Convolutional Neural Network
One model to predict tool wear across multiple machining conditions and transfer to new conditions.
Transfer Learning in Tool Wear Monitoring
Deep Learning, Machine Tool, Tool Wear Monitoring, Transfer Learning
An intuitive way to demonstrate the mechanism of convolutional kernels in 1D signal processing.
DBSCAN-based TDA Visualization
Deep Learning, Keras, Topology Data Analysis, Visualization
Simulate real and random signals aligned with tool wear using conditional GANs.
Deep CGAN Tool Wear Digital Twin
Deep Learning, Keras, Machine Tool, Digital Twin, Conditional GAN