Vibration, and temperature run-to-failure dataset of ball bearing for prognostics
Author:
Funder
Korea Institute for Advancement of Technology
Publisher
Elsevier BV
Reference7 articles.
1. Using deep learning-based approach to predict remaining useful life of rotating components;Deutsch;IEEE Trans. Syst., Man, Cybernet.: Syst.,2017
2. Residual life predictions for ball bearings based on self-organizing map and back propagation neural network methods;Huang;Mech. Syst. Signal. Process,2007
3. Rolling element bearing diagnostics in run-to-failure lifetime testing;Williams;Mech. Syst. Signal Process,2001
4. Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals;Ali;Appl. Acoust.,2015
5. Documentation of NI-9234 specifications, National Instruments official site. https://www.ni.com/docs/ko-KR/bundle/ni-9234-specs/page/specs.html, 2024 (Accessed 24 March 2020).
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