A Novel Feature Extraction Approach for Mechanical Fault Diagnosis Based on ESAX and BoW Model
Author:
Affiliation:
1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China
2. School of Information, Mechanical and Electrical Engineering, Ningde Normal University, Ningde, China
Funder
National Natural Science Foundation of China
Natural Science Foundation of Fujian Province
Scientific Research and Innovation Team of Ningde Normal University
Special Project of Ningde Normal University
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/19/9717300/09805609.pdf?arnumber=9805609
Reference38 articles.
1. Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study
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5. A new feature extraction approach using improved symbolic aggregate approximation for machinery intelligent diagnosis
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