An unsupervised dual-regression domain adversarial adaption network for tool wear prediction in multi-working conditions
出版年份 2022 全文链接
标题
An unsupervised dual-regression domain adversarial adaption network for tool wear prediction in multi-working conditions
作者
关键词
-
出版物
MEASUREMENT
Volume 200, Issue -, Pages 111644
出版商
Elsevier BV
发表日期
2022-07-22
DOI
10.1016/j.measurement.2022.111644
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- 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
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now