Abstract

This manuscript discusses the development of a fusion-based method of visible and thermal acquisitions (Long Wave and Mid-Wave Infrared LWIR, MWIR) to evaluate scratches and shunts in poly-crystalline, Photo-Voltaic PV solar cells. The proposed technique enables non-destructive and real-time inspection of PV cells production-borne defects; using forward bias and reverse bias Electro-Luminescence EL modes. The thermal imagery of the cells is designed to expose the extent of scratches in both the LWIR and MWIR spectra and whether it acts as an emitter layer bringing the p-n junction to the cell surface; while the visible images (from a CCD detector) evaluate the scratch effect on the surface coating layer and hence its reflectivity. On the other hand, the shunts are detected as hot spots and classified as Ohmic and Non-Ohmic using the reverse and forward bias images of the MWIR imager. The acquired images coming from the three channels (LWIR, MWIR, Visible) are combined using two fusion algorithms suited for real-time applications (>30 Hz), specifically; Wavelet based fusion, and Principle Component Analysis PCA based fusion. The fused results are further judged based on several reported criteria mainly; cross entropy, mutual information, and the Signal to Noise Ratio SNR, highlighting the need for a unified fusion evaluation approach. The fusion of visible and thermal inputs provides accurate assessment of the PV cells scratches and shunts in contact-less and real-time fashion. The proposed fused imagery approach combines the information from visual inspection and thermal testing using spatially resolved scanning of the PV cell in real-time.

This work is licensed under a Creative Commons Attribution 4.0 License.