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Automatic solar cell diagnosis and treatment

Author

Listed:
  • Alvaro Rodriguez

    (University of A Coruña)

  • Carlos Gonzalez

    (AIMEN Technology Centre)

  • Andres Fernandez

    (AIMEN Technology Centre)

  • Francisco Rodriguez

    (AIMEN Technology Centre)

  • Tamara Delgado

    (AIMEN Technology Centre)

  • Martin Bellman

    (SINTEF)

Abstract

Solar cells represent one of the most important sources of clean energy in modern societies. Solar cell manufacturing is a delicate process that often introduces defects that reduce cell efficiency or compromise durability. Current inspection systems detect and discard faulty cells, wasting a significant percentage of resources. We introduce Cell Doctor, a new inspection system that uses state of the art techniques to locate and classify defects in solar cells and performs a diagnostic and treatment process to isolate or eliminate the defects. Cell Doctor uses a fully automatic process that can be included in a manufacturing line. Incoming solar cells are first moved with a robotic arm to an Electroluminescence diagnostic station, where they are imaged and analysed with a set of Gabor filters, a Principal Component Analysis technique, a Random Forest classifier and different image processing techniques to detect possible defects in the surface of the cell. After the diagnosis, a laser station performs an isolation or cutting process depending on the detected defects. In a final stage, the solar cells are characterised in terms of their I–V Curve and I–V Parameters, in a Solar Simulator station. We validated and tested Cell Doctor with a labelled dataset of images of monocrystalline silicon cells, obtaining an accuracy and recall above 90% for Cracks, Area Defects and Finger interruptions; and precision values of 77% for Finger Interruptions and above 90% for Cracks and Area Defects. Which allows Cell Doctor to diagnose and repair solar cells in an industrial environment in a fully automatic way.

Suggested Citation

  • Alvaro Rodriguez & Carlos Gonzalez & Andres Fernandez & Francisco Rodriguez & Tamara Delgado & Martin Bellman, 2021. "Automatic solar cell diagnosis and treatment," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 1163-1172, April.
  • Handle: RePEc:spr:joinma:v:32:y:2021:i:4:d:10.1007_s10845-020-01642-6
    DOI: 10.1007/s10845-020-01642-6
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