A Three-Dimensional Vibration Data Compression Method for Rolling Bearing Condition Monitoring
Author:
Affiliation:
1. School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China
2. School of Electrical and Electronic Engineering, Nanyang Technological University, Jurong West, Singapore
Funder
National Key Research and Development Program of China
Key Research and Development Program of Sichuan Province
China Scholarship Council
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/19/10012124/10025624.pdf?arnumber=10025624
Reference27 articles.
1. Data-Driven Fault Diagnosis Method Based on Compressed Sensing and Improved Multiscale Network
2. Compressive sensing meets time–frequency: An overview of recent advances in time–frequency processing of sparse signals
3. A Fast Noniterative Algorithm for Compressive Sensing Using Binary Measurement Matrices
4. Learning-Based Sparse Data Reconstruction for Compressed Data Aggregation in IoT Networks
5. A Two-Stage Compression Method for the Fault Detection of Roller Bearings
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