ENBIS-17 in Naples

9 – 14 September 2017; Naples (Italy) Abstract submission: 21 November 2016 – 10 May 2017

Electroluminescence Image Analysis and Suspicious Areas Detection

11 September 2017, 12:20 – 12:40

Abstract

Submitted by
Evgenii Sovetkin
Authors
Evgenii Sovetkin (RWTH-Aachen), Ansgar Steland (RWTH-Aachen)
Abstract
In this work we consider several problems arising in quality control analysis of electroluminescence (EL) images of photovoltaics (PV) modules. The EL image technique is a useful tool for investigating the state of a PV module and allows us to look inside a module and to analyse the crystalline structure at high resolution. However, there is a lack of methods to employ the information provided by EL images in the analysis of large PV systems.
We first consider several practical issues that arise in field studies, i.e.\ when images are taken under outdoor conditions and not in a lab. We discuss a new problem-specific procedure for automatic correction of rotation and perspective distortions, which to some extent employs statistical approaches such as robust regression; and a procedure for automatic detection of the module and its cell areas (by means of a modified version of the Hough Transform). Those techniques provide us with images of the PV module cells, intensity light of which are of the main interest in quality study.
Secondly, we discuss a spatial test to screen large databases of EL image data aiming at the detection of malfunctioning cells. The spatial test statistics is based on comparing sample averages inside two regions indexed by a region location parameter. The asymptotics is established for a general class of random fields for several of regions sets.
Lastly, we discuss simulation studies and an application of the method to the real EL image data.

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