CONTEXT: An Industry 4.0 Dataset of Contextual Faults in a Smart Factory

Author:

Kaupp Lukas,Webert Heiko,Nazemi Kawa,Humm Bernhard,Simons Stephan

Publisher

Elsevier BV

Subject

General Engineering

Reference22 articles.

1. Agogino, A., Goebel, K“ 2007. Milling Data Set. Moffett Field, CA. URL: http://ti.arc.nasa.gov/project/prognostic-data-repository.

2. Detecting contextual faults in unmanned aerial vehicles using dynamic linear regression and k-nearest neighbour classifier;Alos;Gyroscopy and Navigation,2020

3. Bandeira de Mello Martins, Pedro, Barbosa Nascimento, V., de Freitas, A.R., Bittencourt e Silva, R, Guimãraes Duarte Pinto, R., 2018. Industrial Machines Dataset for Electrical Load Disagreggation. IEEE DataPort. doi:doi:10.21227/CG5V-DK02.

4. Self-organizing maps for anomaly localization and predictive maintenance in cyber-physical production systems;von Birgelen;Procedia CIRP,2018

5. Bonatakis, J., Chokor, A., Propes, N., 2018. PHM Data Challenge 18. Philadelphia, Pennsylvania, USA. URL: https://www.phmsociety.org/events/conference/phm/18/data-challenge.

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