Mixed-Up Experience Replay for Adaptive Online Condition Monitoring

Author:

Russell Matthew1ORCID,Wang Peng2ORCID,Liu Shaopeng3ORCID,Jawahir I. S.4

Affiliation:

1. Department of Electrical and Computer Engineering, University of Kentucky, Lexington, KY, USA

2. Department of Electrical and Computer Engineering and the Department of Mechanical and Aerospace Engineering, University of Kentucky, Lexington, KY, USA

3. GE Research, Niskayuna, NY, USA

4. Institute for Sustainable Manufacturing and the Department of Mechanical and Aerospace Engineering, University of Kentucky, Lexington, KY, USA

Funder

NSF

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Reference34 articles.

1. Bootstrap your own latent: A new approach to self-supervised learning;grill;Proc 34th Int Conf Neural Inf Process Syst,0

2. Fault Feature Extractor based on Bootstrap Your Own Latent and Data Augmentation Algorithm for Unlabeled Vibration Signals

3. Gradient episodic memory for continual learning;lopez-paz;Proc 31st Int Conf Neural Inf Process Syst,0

4. A Deep Adversarial Transfer Learning Network for Machinery Emerging Fault Detection

5. Barlow Twins: Self-supervised learning via redundancy reduction;zbontar;Proc 38th Int Conf Mach Learn,0

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