Automatic feature constructing from vibration signals for machining state monitoring
Published 2017 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Automatic feature constructing from vibration signals for machining state monitoring
Authors
Keywords
Intelligent manufacturing, Automatic feature construction, Machining state monitoring, Deep belief networks
Journal
JOURNAL OF INTELLIGENT MANUFACTURING
Volume -, Issue -, Pages -
Publisher
Springer Nature
Online
2017-02-08
DOI
10.1007/s10845-017-1302-x
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Timely online chatter detection in end milling process
- (2016) Yang Fu et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Representation Learning: A Review and New Perspectives
- (2013) Y. Bengio et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Combined intelligent methods based on wireless sensor networks for condition monitoring and fault diagnosis
- (2013) İlhan Aydın et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Advance in chatter detection in ball end milling process by utilizing wavelet transform
- (2013) Somkiat Tangjitsitcharoen et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Indicators for monitoring chatter in milling based on instantaneous angular speeds
- (2013) M. Lamraoui et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
- (2012) Geoffrey Hinton et al. IEEE SIGNAL PROCESSING MAGAZINE
- Development of chatter detection in milling processes
- (2012) Somkiat Tangjitsitcharoen 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
- A review of chatter vibration research in turning
- (2012) M. Siddhpura et al. INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE
- Fault diagnosis and prognosis using wavelet packet decomposition, Fourier transform and artificial neural network
- (2012) Zhenyou Zhang et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Acoustic Modeling Using Deep Belief Networks
- (2011) Abdel-rahman Mohamed et al. IEEE Transactions on Audio Speech and Language Processing
- Chatter in machining processes: A review
- (2011) Guillem Quintana et al. INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE
- On-line chatter detection using servo motor current signal in turning
- (2011) HongQi Liu et al. Science China-Technological Sciences
- Advanced monitoring of machining operations
- (2010) R. Teti et al. CIRP ANNALS-MANUFACTURING TECHNOLOGY
- Design of multisensor fusion-based tool condition monitoring system in end milling
- (2009) Sohyung Cho et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- A review of machining monitoring systems based on artificial intelligence process models
- (2009) Jose Vicente Abellan-Nebot et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Advance in detection system to improve the stability and capability of CNC turning process
- (2009) Somkiat Tangjitsitcharoen JOURNAL OF INTELLIGENT MANUFACTURING
- On-line chatter detection and identification based on wavelet and support vector machine
- (2009) Zhehe Yao et al. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
- Development of an intelligent multisensor chatter detection system in milling
- (2009) E. Kuljanic et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Intermittent and chaotic vibrations in a regenerative cutting process
- (2008) Grzegorz Litak et al. CHAOS SOLITONS & FRACTALS
- Multisensor approaches for chatter detection in milling
- (2008) E. Kuljanic et al. JOURNAL OF SOUND AND VIBRATION
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchAdd 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