Open AccessPhysics Informed Deep Learning for Tracker Fault Detection in Photovoltaic Power Plants
Author(s) -
Jannik Zgraggen,
Yuandong Guo,
Antonio Notaristefano,
Lilach Goren Huber
Publication year - 2022
Publication title -
proceedings of the annual conference of the prognostics and health management society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.18
H-Index - 11
ISSN - 2325-0178
DOI - 10.36001/phmconf.2022.v14i1.3235
Subject(s) - photovoltaic system , anomaly detection , convolutional neural network , software deployment , computer science , fault (geology) , fault detection and isolation , deep learning , artificial intelligence , string (physics) , machine learning , real time computing , reliability engineering , engineering , electrical engineering , actuator , physics , quantum mechanics , seismology , geology , operating system