Local-Dictionary Sparsity Discriminant Preserving Projections for Rotating Machinery Fault Diagnosis Based on Pre-Selected Multi-Domain Features
Author:
Affiliation:
1. School of Automation, Northwestern Polytechnical University, Shaanxi, China
Funder
U.S. Department of Commerce
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7361/9766065/09740149.pdf?arnumber=9740149
Reference46 articles.
1. Discriminative sparse embedding based on adaptive graph for dimension reduction
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4. Fault diagnosis of rotor based on Local-Global Balanced Orthogonal Discriminant Projection
5. A novel dimensionality reduction method: Similarity order preserving discriminant analysis
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2. Intelligent Bearing Fault Diagnosis Based on Feature Fusion of One-Dimensional Dilated CNN and Multi-Domain Signal Processing;Sensors;2023-06-15
3. A Novel Fault Feature Selection and Diagnosis Method for Rotating Machinery With Symmetrized Dot Pattern Representation;IEEE Sensors Journal;2023-01-15
4. A Randomized Sparsity Preserving Projection and its Exponential Approach for Image Recognition;IEEE Access;2023
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