Multitask learning for health condition identification and remaining useful life prediction: deep convolutional neural network approach
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Multitask learning for health condition identification and remaining useful life prediction: deep convolutional neural network approach
Authors
Keywords
-
Journal
JOURNAL OF INTELLIGENT MANUFACTURING
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2020-07-25
DOI
10.1007/s10845-020-01630-w
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A review on the application of deep learning in system health management
- (2018) Samir Khan et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Remaining useful life estimation of engineered systems using vanilla LSTM neural networks
- (2018) Yuting Wu et al. NEUROCOMPUTING
- Remaining useful life estimation in prognostics using deep convolution neural networks
- (2018) Xiang Li et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- Recent advances in prognostics and health management for advanced manufacturing paradigms
- (2018) Tangbin Xia et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- A recurrent neural network based health indicator for remaining useful life prediction of bearings
- (2017) Liang Guo et al. NEUROCOMPUTING
- Multiobjective Deep Belief Networks Ensemble for Remaining Useful Life Estimation in Prognostics
- (2017) Chong Zhang et al. IEEE Transactions on Neural Networks and Learning Systems
- A review of diagnostic and prognostic capabilities and best practices for manufacturing
- (2016) Gregory W. Vogl et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Prognostics of gas turbine engine: An integrated approach
- (2015) Martha A. Zaidan et al. EXPERT SYSTEMS WITH APPLICATIONS
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Condition-based maintenance effectiveness for series–parallel power generation system—A combined Markovian simulation model
- (2015) A. Azadeh et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications
- (2013) Jay Lee et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- A recursive Bayesian framework for structural health management using online monitoring and periodic inspections
- (2012) Masoud Rabiei et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- Prognosis of Defect Propagation Based on Recurrent Neural Networks
- (2011) Arnaz Malhi et al. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
- Intelligent condition monitoring and prognostics system based on data-fusion strategy
- (2010) Gang Niu et al. EXPERT SYSTEMS WITH APPLICATIONS
- A Survey on Transfer Learning
- (2009) Sinno Jialin Pan et al. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
- An artificial neural network method for remaining useful life prediction of equipment subject to condition monitoring
- (2009) Zhigang Tian JOURNAL OF INTELLIGENT MANUFACTURING
- Physics-based modeling strategies for diagnostic and prognostic application in aerospace systems
- (2009) David B. Stringer et al. JOURNAL OF INTELLIGENT MANUFACTURING
- A new approach to intelligent fault diagnosis of rotating machinery
- (2007) Yaguo Lei et al. EXPERT SYSTEMS WITH APPLICATIONS
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 MoreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started