Fault State Recognition of Rolling Bearing Based Fully Convolutional Network
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- Type
- article
- Published
- 2019-09-01
- Cited by
- 59
- References
- 18
- OpenAlex
- https://openalex.org/W2782766333
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:64903980
Keywords
Computer science, Correctness, Convolutional neural network, Bearing (navigation), Fault (geology)
References
- Feature extraction for rolling element bearing fault diagnosis utilizing generalized S transform and two-dimensional non-negative matrix factorization
- Wavelet support vector machine for induction machine fault diagnosis based on transient current signal
- Fuzzy lattice classifier and its application to bearing fault diagnosis
- Fault diagnosis of sensor by chaos particle swarm optimization algorithm and support vector machine
- A novel intelligent gear fault diagnosis model based on EMD and multi-class TSVM
- Analysis of the Damage Causes of High Speed Bearing Failure
- Multivariate empirical mode decomposition and its application to fault diagnosis of rolling bearing
- A damage severity assessment method for bearings with rolling element damage
- A cointegration-based monitoring method for rolling bearings working in time-varying operational conditions
- End-to-End Comparative Attention Networks for Person Re-Identification
- Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
- Bearing fault diagnosis with auto-encoder extreme learning machine: A comparative study
- End-to-end keywords spotting based on connectionist temporal classification for Mandarin
- and s
- AND T
- I and J
Cited by
- Defect Diagnosis of Rolling Element Bearing using Deep Learning
- Deep Learning Algorithms for Bearing Fault Diagnosticsx—A Comprehensive Review
- Composite multi-scale weighted permutation entropy and extreme learning machine based intelligent fault diagnosis for rolling bearing
- Application of Multi-Dimension Input Convolutional Neural Network in Fault Diagnosis of Rolling Bearings
- Deep Learning Algorithms for Bearing Fault Diagnostics - A Review
- Time–Frequency Map-Based Abnormal Signal Detection
- Fault Pattern Recognition of Axle Box Bearings for High-speed EMU Based on Onboard Real-time Temperature Data
- Diagnosing Automotive Damper Defects Using Convolutional Neural Networks and Electronic Stability Control Sensor Signals
- Deep Convolutional and LSTM Recurrent Neural Networks for Rolling Bearing Fault Diagnosis Under Strong Noises and Variable Loads
- An Adaptive Anti-Noise Neural Network for Bearing Fault Diagnosis Under Noise and Varying Load Conditions
- Vibration analysis in bearings for failure prevention using CNN
- Data-Driven Fault Diagnosis Method Based on Second-Order Time-Reassigned Multisynchrosqueezing Transform and Evenly Mini-Batch Training
- A Novel Bearing Fault Diagnosis of Raw Signals Based on 1D Residual Convolution Neural Network
- Research on Bearing Fault Diagnosis Method Based on Two-Dimensional Convolutional Neural Network
- A multi-fault diagnosis method of gear-box running on edge equipment
- Comparing the Effectiveness of Two Convolutional Neural Networks Methods on Fault Diagnosis
- Multiple Sensors Fault Diagnosis for Rolling Bearing Based on Variational Mode Decomposition and Convolutional Neural Networks
- Intelligent fault diagnosis of rolling bearings based on refined composite multi-scale dispersion q-complexity and adaptive whale algorithm-extreme learning machine
- Fault Diagnosis of Bearings Based on Multi-Sensor Information Fusion and 2D Convolutional Neural Network
- Multi-Objective Sustainable Planning of Chemical Production Chains
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