Fault diagnosis of rolling bearings using an Improved Multi-Scale Convolutional Neural Network with Feature Attention mechanism
出版年份 2020 全文链接
标题
Fault diagnosis of rolling bearings using an Improved Multi-Scale Convolutional Neural Network with Feature Attention mechanism
作者
关键词
Multi-Scale, Convolutional Neural Network, Fault diagnosis, Deep learning, Rolling bearings
出版物
ISA TRANSACTIONS
Volume 110, Issue -, Pages 379-393
出版商
Elsevier BV
发表日期
2020-10-27
DOI
10.1016/j.isatra.2020.10.054
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。- Vibration fault diagnosis of wind turbines based on variational mode decomposition and energy entropy
- (2019) Xuejun Chen et al. ENERGY
- An improved deep convolutional neural network with multi-scale information for bearing fault diagnosis
- (2019) Wenyi Huang et al. NEUROCOMPUTING
- Intelligent fault diagnosis of rotating machinery based on one-dimensional convolutional neural network
- (2019) Chunzhi Wu et al. COMPUTERS IN INDUSTRY
- Study of adaptive blades in extreme environment using fluid–structure interaction method
- (2019) Weipao Miao et al. JOURNAL OF FLUIDS AND STRUCTURES
- Mechanical fault diagnosis using Convolutional Neural Networks and Extreme Learning Machine
- (2019) Zhuyun Chen et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Compound Fault Diagnosis of Gearboxes via Multi-label Convolutional Neural Network and Wavelet Transform
- (2019) Pengfei Liang et al. COMPUTERS IN INDUSTRY
- Multiscale Convolutional Neural Networks for Fault Diagnosis of Wind Turbine Gearbox
- (2018) Guoqian Jiang et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Complete ensemble local mean decomposition with adaptive noise and its application to fault diagnosis for rolling bearings
- (2018) Lei Wang et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load
- (2018) Wei Zhang et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks
- (2017) Osama Abdeljaber et al. JOURNAL OF SOUND AND VIBRATION
- Research on variational mode decomposition in rolling bearings fault diagnosis of the multistage centrifugal pump
- (2017) Ming Zhang et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Fault diagnosis of gearbox using empirical mode decomposition and multi-fractal detrended cross-correlation analysis
- (2016) Hongmei Liu et al. JOURNAL OF SOUND AND VIBRATION
- Convolutional Neural Network Based Fault Detection for Rotating Machinery
- (2016) Olivier Janssens et al. JOURNAL OF SOUND AND VIBRATION
- Rolling bearing fault diagnosis using an optimization deep belief network
- (2015) Haidong Shao et al. MEASUREMENT SCIENCE and TECHNOLOGY
- A fault diagnosis method based on local mean decomposition and multi-scale entropy for roller bearings
- (2014) Huanhuan Liu et al. MECHANISM AND MACHINE THEORY
- Representation Learning: A Review and New Perspectives
- (2013) Y. Bengio et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Bearing fault diagnosis using multi-scale entropy and adaptive neuro-fuzzy inference
- (2010) Long Zhang et al. EXPERT SYSTEMS WITH APPLICATIONS
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExplorePublish 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 More