PhD academic projects in The University of Manchester

Under the supervision of Dr Robert Heinemann and Otto Jan Bakker.


Remove size limit of preceiving signals to achieve real-time process incidence identification.

TPP in process incidence identification

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 process.

Tool wear monitoring in multiple condition

Deep Learning, Machine Tool, Tool wear monitoring, Convolutional Neural Network


One model to predict tool wear in multiple machining condition and its easy transferring to new condition.

The transfer learning in tool wear monitoring

Deep Learning, Machine Tool, Tool wear monitoring, Transfer Learning


Easy, intuitive and accurate way to demonstrate Mechanism of convolutional kernel in processing 1D signal.

DBSCAN based TDA Visualization

Deep Learning, Keras, Topology Data Analysis, Visualization


Simulate real and random signal accordance to tool wear by deep conditional convolutional generative adversarial network

Deep CGAN based tool wear digital twin

Deep Learning, Keras, Machine Tool, Digital Twin, Deep Convolutional Generative Adversarial Neural Network

Android & Flutter open source projects


Lightweight Discuz! forum client for Android.

Discuz Hub

MIT License, Since 2018


Cross-platform Discuz! forum client for screen in any size.


MIT License, Since 2020

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