Analysis of Defects on Solar Power Cells

Third Party Funds Group - Sub project

Overall project details

Overall project: Laboranalyse von Degradationsmechanismen unter beschleunigter Alterung und Entwicklung geeigneter feldtauglicher bildgebender Detektionsverfahren und Entwicklung und Evaluation eines Algorithmus zur Fehlerdetektion und Prognostizierung der Ausfallwahrscheinlichkeit

Project Details

Project leader:
Prof. Dr.-Ing. Andreas Maier

Project members:
Mathis Hoffmann

Contributing FAU Organisations:
Lehrstuhl für Informatik 5 (Mustererkennung)

Funding source: Bundesministerium für Wirtschaft und Technologie (BMWi)
Start date: 01/08/2018
End date: 31/07/2021

Abstract (technical / expert description):

Over the last decade, a large number of solar power
plants have been installed in Germany. To ensure a high
performance, it is necessary to detect defects early.
Therefore, it is required to control the quality of the
solar cells during the production process, as well as to
monitor the installed modules. Since manual inspections
are expensive, a large degree of automation is required.

This project aims to develop a new approach to
automatically detect and classify defects on solar power
cells and to estimate their impact on the performance.
Further, big data methods will be applied to identify
circumstances that increase the probability of a cell to
become defect. As a result, it will be possible to reject
cells in the production that have a high likelihood to
become defect.

Last updated on 2019-19-07 at 11:24