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Application of the Singular Spectrum Analysis on electroluminescence images of thin-film photovoltaic modules

arXiv 2109.04048 ↗First posted 9 Sep 2021cs.CV stat.APcited by 0

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Abstract (arXiv)

This paper discusses an application of the singular spectrum analysis method (SSA) in the context of electroluminescence (EL) images of thin-film photovoltaic (PV) modules. We propose an EL image decomposition as a sum of three components: global intensity, cell, and aperiodic components. A parametric model of the extracted signal is used to perform several image processing tasks. The cell component is used to identify interconnection lines between PV cells at sub-pixel accuracy, as well as to correct incorrect stitching of EL images. Furthermore, an explicit expression of the cell component signal is used to estimate the inverse characteristic length, a physical parameter related to the resistances in a PV module.

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References · 4

  1. 2018Automatic Classification of Defective Photovoltaic Module Cells in Electroluminescence Imagescited by 35
  2. 2020Encoder-decoder semantic segmentation models for electroluminescence images of thin-film photovoltaic modulescited by 4
  3. 2013Multivariate and 2D Extensions of Singular Spectrum Analysis with the Rssa Packagecited by 2
  4. 2018Automatic Processing and Solar Cell Detection in Photovoltaic Electroluminescence Imagescited by 1

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