An unsupervised dual-regression domain adversarial adaption network for tool wear prediction in multi-working conditions

Milling tool wear prediction using multi-sensor feature fusion based on stacked sparse autoencoders

(2022) Zhaopeng He et al.   MEASUREMENT

Tool wear state prediction based on feature-based transfer learning

(2021) Jianbo Li et al.   The International Journal of Advanced Manufacturing Technology

Deep learning-based tool wear prediction and its application for machining process using multi-scale feature fusion and channel attention mechanism

(2021) Xingwei Xu et al.   MEASUREMENT

Two-Stage Transfer Learning for Fault Prognosis of Ion Mill Etching Process

(2021) Chongdang Liu et al.   IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING

A new tool wear condition monitoring method based on deep learning under small samples

(2021) Yuqing Zhou et al.   MEASUREMENT

Modeling and analysis of tool wear prediction based on SVD and BiLSTM

(2020) Xiaoqiang Wu et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

A Comprehensive Survey on Transfer Learning

(2020) Fuzhen Zhuang et al.   PROCEEDINGS OF THE IEEE

Multiscale Convolutional Attention Network for Predicting Remaining Useful Life of Machinery

(2020) Biao Wang et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Remaining Useful Lifetime Prediction via Deep Domain Adaptation

(2019) Paulo Roberto de Oliveira da Costa et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Tool wear condition monitoring based on continuous wavelet transform and blind source separation

(2018) Tarak Benkedjouh et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Deep Transfer Learning Based on Sparse Autoencoder for Remaining Useful Life Prediction of Tool in Manufacturing

(2018) Chuang Sun et al.   IEEE Transactions on Industrial Informatics

Tool wear monitoring based on kernel principal component analysis and v-support vector regression

(2016) Dongdong Kong et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

A weighted hidden Markov model approach for continuous-state tool wear monitoring and tool life prediction

(2016) Jinsong Yu et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Tool wear predictability estimation in milling based on multi-sensorial data

(2015) P. Stavropoulos et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Evaluation of expert system for condition monitoring of a single point cutting tool using principle component analysis and decision tree algorithm

(2010) M. Elangovan et al.   EXPERT SYSTEMS WITH APPLICATIONS

Tool Wear Monitoring Using Acoustic Emissions by Dominant-Feature Identification

(2010) Jun-Hong Zhou et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

A theory of learning from different domains

(2009) Shai Ben-David et al.   MACHINE LEARNING