Skip to main content
Log in

A Mamdani Fuzzy Logic System to Enhance Solar Cell Micro-Cracks Image Processing

  • 3DR Express
  • Published:
3D Research

Abstract

Micro-cracks in solar Photo-Voltaic Cells (PVCs) can be formed in the vicinity of PVC/wafer manufacturing process or by thermal stress produced in transportation/handling or by inclement weather condition. Its insight is must as it reduces the efficiency of PVCs, enfeeble the cell constitution as well as affect the net manufactured production yield resulting in increase in production cost. The detection of these micro-cracks is strenuous owing to wafer’s heterogeneous textured base and involves two steps; first visualization of micro-cracks to imaging device, second efficient image processing technique to extract these micro-cracks from the captured image. In this paper Mamdani Fuzzy logic is proposed for extracting micro-cracks from solar PVCs images and comparison of performance analysis is done using MATLAB. The results show that using the proposed strategy, micro cracks visibility is much more prominent than its counterparts present in literature. To access local and remote output current data of solar panel the Internet of Things accreditation is done using Arduino and WiFi module.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Powell, D. M., Fu, R., Horowitz, K., Basore, P. A., Woodhouse, M., & Buonassisi, T. (2015). The capital intensity of photovoltaics manufacturing: barrier to scale and opportunity for innovation. Energy & Environmental Science, 8, 395–408.

    Article  Google Scholar 

  2. Rajput, P., Tiwari, G. N., Sastry, O. S., Bora, B., & Sharma, V. (2016). Degradation of monocrystalline photovoltaic modules after 22 years of outdoor exposure in the composite climate of India. Solar Energy, 135, 786–795.

    Article  Google Scholar 

  3. Dhimish, M., Holmes, V., & Dales, M. (2016). Grid-connected PV virtual instrument system (GCPV-VIS) for detecting photovoltaic failure. In IEEE international symposium on environment friendly energies and applications (EFEA) (pp. 1–6).

  4. Sharma, V., & Chandel, S. S. (2013). Performance and degradation analysis for long term reliability of solar photovoltaic systems: A review. Renewable and Sustainable Energy Reviews, 27, 753–767.

    Article  Google Scholar 

  5. Kontgers, M., Kunze, I., Kajari-Schroder, S., Breitenmoser, X., & Bjørneklett, B. (2010). Quantifying the risk of power loss in PV modules due to micro cracks. In 25th European photovoltaic solar energy conference (pp. 3745–3752).

  6. Morlier, A., Haase, F., & Kontges, M. (2015). Impact of cracks in multicrystalline silicon solar cells on PV module power—A simulation study based on field data. IEEE Journal of Photovoltaics, 5(6), 1735–1741.

    Article  Google Scholar 

  7. Paggi, M., Corrado, M., & Rodriguez, M. A. (2013). A multi-physics and multi-scale numerical approach to microcracking and power-loss in photovoltaic modules. Composite Structures, 95, 630–638.

    Article  Google Scholar 

  8. Köntges, M., Kajari-Schröder, S., Kunze, I., & Jahn, U. (2011). Crack statistic of crystalline silicon photovoltaic modules. In 26th European photovoltaic solar energy conference and exhibition (pp. 3290–3294).

  9. Rupnowski, P., & Sopori, B. (2009). Strength of silicon wafers: Fracture mechanics approach. International Journal of Fracture, 155(1), 67–74.

    Article  Google Scholar 

  10. Chiou, Y. C., Liu, J. Z., & Liang, Y. T. (2011). Micro crack detection of multi-crystalline silicon solar wafer using machine vision techniques. Sensor Review, 31(2), 154–165.

    Article  Google Scholar 

  11. Kajari-Schroder, S., Kunze, I., Eitner, U., & Köntges, M. (2011). Spatial and orientational distribution of cracks in crystalline photovoltaic modules generated by mechanical load tests. Solar Energy Materials and Solar Cells, 95(11), 3054–3059.

    Article  Google Scholar 

  12. Wieghold, S., Morishige, A. E., Meyer, L., Buonassisi, T., & Sachs, E. M. (2017). Crack detection in crystalline silicon solar cells using dark- field imaging. In Proceedings of 7th international conference on silicon photovoltaics, silicon PV2017, Elseveir Energy Procedia (Vol. 124, pp. 526–531).

    Article  Google Scholar 

  13. Wansleben, S. (2011). Not falling through the crack. Available: http://www.pv-magazine.com/archive/articles/beitrag/not-falling-through-the-cracks100002343/#ixzz2XlDuI4Bt. Accessed 11 Feb 2018.

  14. Breitenstein, O., Bauer, J., Altermatt, P. P., & Ramspeck, K. (2010). Influence of defects on solar cell characteristics. Solid State Phenomena, 156, 1–10.

    Google Scholar 

  15. Grunow, P., Clemens, P., Hoffmann, V., Litzenburger, B., & Podlowski, L. (2005). Influence of micro cracks in multi-crystalline silicon solar cells on the reliability of PV modules. In Presented at the 20th European PV solar energy conference, Barcelona, Spain, June 6–10, 2005.

  16. Köntges, M., Kajari-Schröder, S., Kunze, I., & Jahn, U. (2011). The risk of power loss in crystalline silicon based photovoltaic modules due to micro-cracks. Solar Energy Materials and Solar Cells, 95, 1131–1137.

    Article  Google Scholar 

  17. Kropp, T., et al. (2018). Quantitative prediction of power loss for damaged photovoltaic modules using electroluminescence. Energies, 11(5), 1172.

    Article  Google Scholar 

  18. Abdelhamid, M., Singh, R., & Omar, M. (2013). Review of microcrack detection techniques for solar cells. IEEE Journal of Photovoltaics, 4, 2156–3381.

    Google Scholar 

  19. Bauer, J., Frühauf, F., & Breitenstein, O. (2017). Quantitative local current-voltage analysis and calculation of performance parameters of single solar cells in modules. Solar Energy Materials and Solar Cells, 159, 8–19.

    Article  Google Scholar 

  20. Dhimish, M., et al. (2017). The impact of cracks on photovoltaic power performance. Journal of Science: Advanced Materials and Devices, 2(2), 199–209.

    Google Scholar 

  21. Mallor, F., León, T., De Boeck, L., Van Gulck, S., Meulders, M., & Van der Meerssche, B. (2017). A method for detecting malfunctions in PV solar panels based on electricity production monitoring. Solar Energy, 153, 51–63.

    Article  Google Scholar 

  22. Tsai, D. M., Chang, C. C., & Chao, S. M. (2010). Micro-crack inspection in heterogeneously textured solar wafers using anisotropic diffusion. Image and Vision Computing, 28(3), 491–501.

    Article  Google Scholar 

  23. Stankovic, J. A. (2014). Research directions for the Internet of Things. IEEE Internet of Things Journal, 1(1), 3–9.

    Article  MathSciNet  Google Scholar 

  24. Zanella, A. (2014). Internet of Things for smart cities. IEEE Internet of Things Journal, 1(1), 22–32.

    Article  Google Scholar 

  25. Jin, J., Gubbi, J., Marusic, S., & Palaniswami, M. (2014). An information framework for creating a smart city through Internet of Things. IEEE Internet of Things Journal, 1(2), 112–121.

    Article  Google Scholar 

  26. Kishore, P., et al. (2017). Internet of Things based low-cost real-time home automation and smart security system. International Journal of Advanced Research in Computer and Communication Engineering, 6, 505–509.

    Article  Google Scholar 

  27. Bin, L., Xianghao, H., & Shuai, F. (2011). Automatic inspection of surface crack in solar cell images. In Proceedings of control and decision conference, 2011 Chinese (pp. 993–998).

  28. Ko, S. S., Liu, C. S., & Lin, Y. C. (2013). Optical inspection system with tunable exposure unit for micro-crack detection in solar wafers. Elsevier Optik, 124, 4030–4035.

    Article  Google Scholar 

  29. Rueland, E., Herguth, A., Trummer, A., Wansleben, S., & Fath, P. (2005). Micro- crack detection an other optical characterization techniques for in-line inspection of wafers and cells. In Proceedings of 20th European photovoltaic solar energy conference, Barcelona, Spain, 2005.

  30. Zhuang, F., Yanzheng, Z., Yang, L., Qixin, C., Mingbo, C., Jun, Z., & Lee, J. (2004). Solar cell crack inspection by image processing. In Proceedings of international conference on business of electronic product reliability and liability.

  31. Yang, W. (2009). Short-time discrete wavelet transform for wafer microcrack detection. In Proceedings of IEEE international symposium on industrial electronics, Seoul, Korea, 2009.

  32. Rakotoniaina, J. P., Breitenstein, O., Al Rifai, M. H., Franke, D., & Schnieder, A. (2004). Detection of cracks in silicon wafers and solar cells by lock-in ultrasound thermography. In Proceedings of PV solar conference, Paris, France, 2004.

  33. Belyaev, A., Polupan, O., Ostapenko, S., Hess, D. P., & Kalejs, J. P. (2006). Res-onance ultrasonic vibration diagnostics of elastic stress in full-size silicon wafers. Semiconductor Science and Technology, 21, 254–260.

    Article  Google Scholar 

  34. Fuyuki, T., Kondo, H., Yamazaki, T., Takahashi, Y., & Uraoka, Y. (2005). Photographic surveying of minority carrier diffusion length in polycrystalline silicon solar cells by electroluminescence. Applied Physics Letters, 86, 262108–262110.

    Article  Google Scholar 

  35. Trupke, T., Bardos, R. A., Schubert, M. C., & Warta, W. (2006). Photoluminescence imaging of silicon wafers. Applied Physics Letters, 89(4), 044107.

    Article  Google Scholar 

  36. Tsai, D. M., Wu, S. C., & Chiu, W. Y. (2012). Defect detection in solar cells using fourier image reconstruction. Elsevier Solar Energy Materials and Solar Cells, 99, 250–262.

    Article  Google Scholar 

  37. Desai, A., Injmulwar, P., Karadkhedkar, S., Gaikwad, V., & Chopde, A. (2016). Detection of microcracks in solar cell images. In Proceedings of national conference on ACCET, Pune, India, 2016.

  38. Tsai, D. M., Wu, S. C., & Chiu, W. Y. (2013). Defect detection in solar modules using ICA basis images. IEEE Transactions on Industrial Informatics, 9, 1551–3203.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rashmi Chawla.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chawla, R., Singal, P. & Garg, A.K. A Mamdani Fuzzy Logic System to Enhance Solar Cell Micro-Cracks Image Processing. 3D Res 9, 34 (2018). https://doi.org/10.1007/s13319-018-0186-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s13319-018-0186-7

Keywords

Navigation