Automatic detection of visual faults on photovoltaic modules using deep ensemble learning network

Automatic detection of visual faults on photovoltaic modules using deep ensemble learning network

The present study proposes an ensemble-based deep neural network (DNN) model for autonomous detection of visual faults such as glass breakage, burn marks, snail trail, and discoloration, delamination on various photovoltaic modules (PVM). The proposed technique utilizes an image dataset captured by...

Full description

Bibliographic Details
Main Authors: S. Naveen Venkatesh, B. Rebecca Jeyavadhanam, A.M. Moradi Sizkouhi, S.M. Esmailifar, M. Aghaei, V. Sugumaran
Format: Article
Language:English
Published: Elsevier 2022-11-01
Series:Energy Reports
Subjects:
Photovoltaic modules
Autonomous fault detection
Deep neural network
Ensemble learning
Random forest
Unmanned aerial vehicle
Online Access:http://www.sciencedirect.com/science/article/pii/S2352484722023617

Internet

http://www.sciencedirect.com/science/article/pii/S2352484722023617

Similar Items