Bearing Fault Diagnosis Method Based on Deep Convolutional Neural Network and Random Forest Ensemble Learning
出版年份 2019 全文链接
标题
Bearing Fault Diagnosis Method Based on Deep Convolutional Neural Network and Random Forest Ensemble Learning
作者
关键词
-
出版物
SENSORS
Volume 19, Issue 5, Pages 1088
出版商
MDPI AG
发表日期
2019-03-04
DOI
10.3390/s19051088
参考文献
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注意：仅列出部分参考文献，下载原文获取全部文献信息。- A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method
- (2018) Long Wen et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Intelligent Bearing Fault Diagnosis Method Combining Compressed Data Acquisition and Deep Learning
- (2018) Jiedi Sun et al. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
- Fault Diagnosis for Rotating Machinery Using Multiple Sensors and Convolutional Neural Networks
- (2018) Min Xia et al. IEEE-ASME TRANSACTIONS ON MECHATRONICS
- Intelligent fault diagnosis of rolling bearing using deep wavelet auto-encoder with extreme learning machine
- (2018) Shao Haidong et al. KNOWLEDGE-BASED SYSTEMS
- Artificial intelligence for fault diagnosis of rotating machinery: A review
- (2018) Ruonan Liu et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- A novel method for intelligent fault diagnosis of rolling bearings using ensemble deep auto-encoders
- (2018) Haidong Shao et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Remaining useful life estimation in prognostics using deep convolution neural networks
- (2018) Xiang Li et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- Multi-Level and Multi-Scale Feature Aggregation Using Pretrained Convolutional Neural Networks for Music Auto-Tagging
- (2017) Jongpil Lee et al. IEEE SIGNAL PROCESSING LETTERS
- Deep Learning Based Approach for Bearing Fault Diagnosis
- (2017) Miao He et al. IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
- A Data-Driven Fault Diagnosis Methodology in Three-Phase Inverters for PMSM Drive Systems
- (2017) Baoping Cai et al. IEEE TRANSACTIONS ON POWER ELECTRONICS
- A Convolutional Neural Network for Fault Classification and Diagnosis in Semiconductor Manufacturing Processes
- (2017) Ki Bum Lee et al. IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING
- Rolling bearing fault detection and diagnosis based on composite multiscale fuzzy entropy and ensemble support vector machines
- (2017) Jinde Zheng et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- CNN for saliency detection with low-level feature integration
- (2017) Hongyang Li et al. NEUROCOMPUTING
- Deep Learning Enabled Fault Diagnosis Using Time-Frequency Image Analysis of Rolling Element Bearings
- (2017) David Verstraete et al. SHOCK AND VIBRATION
- A New Deep Transfer Learning Based on Sparse Auto-Encoder for Fault Diagnosis
- (2017) Long Wen et al. IEEE Transactions on Systems Man Cybernetics-Systems
- Online Fault Diagnosis of Motor Bearing via Stochastic-Resonance-Based Adaptive Filter in an Embedded System
- (2017) Siliang Lu et al. IEEE Transactions on Systems Man Cybernetics-Systems
- Stacked Sparse Autoencoder-Based Deep Network for Fault Diagnosis of Rotating Machinery
- (2017) Yumei Qi et al. IEEE Access
- Multivariate outlier mining and regression feedback for 3D measurement improvement in opto-mechanical system
- (2016) Wendy Flores-Fuentes et al. OPTICAL AND QUANTUM ELECTRONICS
- Sensor Data Fusion with Z-Numbers and Its Application in Fault Diagnosis
- (2016) Wen Jiang et al. SENSORS
- Fault Diagnosis for Rotating Machinery Using Vibration Measurement Deep Statistical Feature Learning
- (2016) Chuan Li et al. SENSORS
- Flood hazard risk assessment model based on random forest
- (2015) Zhaoli Wang et al. JOURNAL OF HYDROLOGY
- Intelligent fault diagnosis of roller bearings with multivariable ensemble-based incremental support vector machine
- (2015) XiaoLi Zhang et al. KNOWLEDGE-BASED SYSTEMS
- Rolling bearing fault diagnosis using an optimization deep belief network
- (2015) Haidong Shao et al. MEASUREMENT SCIENCE and TECHNOLOGY
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Efficient distance metric learning by adaptive sampling and mini-batch stochastic gradient descent (SGD)
- (2014) Qi Qian et al. MACHINE LEARNING
- Sentiment classification: The contribution of ensemble learning
- (2013) Gang Wang et al. DECISION SUPPORT SYSTEMS
- Fault diagnosis of rolling element bearing with intrinsic mode function of acoustic emission data using APF-KNN
- (2013) D.H. Pandya et al. EXPERT SYSTEMS WITH APPLICATIONS
- Motor Bearing Fault Diagnosis Using Trace Ratio Linear Discriminant Analysis
- (2013) Xiaohang Jin et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- An application of a discrete wavelet transform and a back-propagation neural network algorithm for fault diagnosis on single-circuit transmission line
- (2012) A. Ngaopitakkul et al. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
- Signal Model-Based Fault Detection and Diagnosis for Induction Motors Using Features of Vibration Signal in Two-Dimension Domain
- (2011) Van Tuan Do et al. STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING
- EEMD method and WNN for fault diagnosis of locomotive roller bearings
- (2010) Yaguo Lei et al. EXPERT SYSTEMS WITH APPLICATIONS
- Signal feature extraction based on an improved EMD method
- (2009) Li Lin et al. MEASUREMENT
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