Shift-Invariant Sparse Filtering for Bearing Weak Fault Signal Denoising
Author:
Affiliation:
1. College of Mechanical and Vehicle Engineering, Chongqing University of China, Chongqing, China
2. State Key Laboratory of Mechanical Transmission, Chongqing University of China, Chongqing, China
3. Chongqing Gearbox Company Ltd, Chongqing, China
Funder
National Key Research and Development Program of China
Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7361/10302460/10268343.pdf?arnumber=10268343
Reference33 articles.
1. Bearing Fault Feature Extraction Based on Adaptive OMP and Improved K-SVD
2. Fault diagnosis of rotating machines based on the EMD manifold
3. Discriminative Dictionary Learning-Based Sparse Classification Framework for Data-Driven Machinery Fault Diagnosis
4. Sparse representation based on local time–frequency template matching for bearing transient fault feature extraction
5. Rotor crack detection based on high-precision modal parameter identification method and wavelet finite element model
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1. AEEFCSR: an adaptive ensemble empirical feed-forward cascade stochastic resonance system for weak signal detection;Measurement Science and Technology;2024-09-09
2. Bearing Fault Vibration Signal Denoising Based on Adaptive Denoising Autoencoder;Electronics;2024-06-19
3. An Adaptive Multi-D-Norm-Driven Sparse Unfolding Deconvolutional Network for Bearing Fault Diagnosis;Sensors;2024-04-19
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