EveSyncIAI: Event Synchronization Industrial Augmented Intelligence for Fault Diagnosis
Author:
Affiliation:
1. Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, USA
2. Technology Service Business Group, Foxconn Industrial Internet, Guangdong, Shenzhen, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Condensed Matter Physics,Electronic, Optical and Magnetic Materials
Link
http://xplorestaging.ieee.org/ielx7/66/9851188/09786049.pdf?arnumber=9786049
Reference37 articles.
1. Detection and Diagnosis of Faults in Induction Motor Using an Improved Artificial Ant Clustering Technique
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3. Predicting remaining useful life of rotating machinery based artificial neural network
4. Gearbox fault diagnosis based on deep random forest fusion of acoustic and vibratory signals
5. Understanding receiver operating characteristic (ROC) curves
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