An unsupervised online monitoring method for tool wear using a sparse auto-encoder
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
An unsupervised online monitoring method for tool wear using a sparse auto-encoder
Authors
Keywords
-
Journal
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
Volume 106, Issue 5-6, Pages 2493-2507
Publisher
Springer Science and Business Media LLC
Online
2019-12-21
DOI
10.1007/s00170-019-04788-7
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Online Tool Wear Monitoring Via Hidden Semi-Markov Model With Dependent Durations
- (2018) Kunpeng Zhu et al. IEEE Transactions on Industrial Informatics
- Estimation the wear state of milling tools using a combined ensemble empirical mode decomposition and support vector machine method
- (2018) Chuangwen XU et al. Journal of Advanced Mechanical Design Systems and Manufacturing
- Robust Tool Wear Monitoring Using Systematic Feature Selection in Turning Processes With Consideration of Uncertainties
- (2018) Bin Zhang et al. JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
- Deep learning for smart manufacturing: Methods and applications
- (2018) Jinjiang Wang et al. JOURNAL OF MANUFACTURING SYSTEMS
- Using multiple feature spaces-based deep learning for tool condition monitoring in ultra-precision manufacturing
- (2018) Chengming Shi et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Tool condition monitoring using spectral subtraction and convolutional neural networks in milling process
- (2018) Fatemeh Aghazadeh et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Predicting tool wear with multi-sensor data using deep belief networks
- (2018) Yuxuan Chen 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
- Application of audible sound signals for tool wear monitoring using machine learning techniques in end milling
- (2017) Achyuth Kothuru et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Monitoring tool wear using classifier fusion
- (2017) Elijah Kannatey-Asibu et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big Data
- (2016) Yaguo Lei et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Progressive tool flank wear monitoring by applying discrete wavelet transform on turned surface images
- (2016) Samik Dutta et al. MEASUREMENT
- Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data
- (2016) Feng Jia et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Monitoring of tool wear using measured machining forces and neuro-fuzzy modelling approaches during machining of GFRP composites
- (2015) A.I. Azmi ADVANCES IN ENGINEERING SOFTWARE
- Evaluation of neural models applied to the estimation of tool wear in the grinding of advanced ceramics
- (2015) Mauricio Eiji Nakai et al. EXPERT SYSTEMS WITH APPLICATIONS
- Real-time tool wear monitoring in milling using a cutting condition independent method
- (2015) Mehdi Nouri et al. INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE
- Tool wear monitoring using naïve Bayes classifiers
- (2014) Jaydeep Karandikar et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Monitoring and processing signal applied in machining processes – A review
- (2014) C.H. Lauro et al. MEASUREMENT
- Representation Learning: A Review and New Perspectives
- (2013) Y. Bengio et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- A two-step feature selection method for monitoring tool wear and its application to the coroning process
- (2012) Juil Yum et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- A review of flank wear prediction methods for tool condition monitoring in a turning process
- (2012) A. Siddhpura et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Advanced monitoring of machining operations
- (2010) R. Teti et al. CIRP ANNALS-MANUFACTURING TECHNOLOGY
- Wavelet analysis of sensor signals for tool condition monitoring: A review and some new results
- (2009) Kunpeng Zhu et al. INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE
Become a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get StartedAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started