Study On Polarization Characteristics And Defect Detection Method Of Electroluminescence In Crystalline Silicon Photovoltaic Modules

The rapid development of photovoltaic modules has put forward higher requirements for their defect detection technology.Due to the advantages of simple operation,low cost,good repeatability,and fast detection speed,electroluminescence detection method is the most widely used method,which have become a standard in the photovoltaic industry.However,this method still has some shortcomings,mainly manifested in the inevitable impact of background interference and random noise caused by ambient stray light and camera imaging characteristics during the generation and transmission of electroluminescent images,resulting in blurred images and poor imaging quality.Moreover,the difference in luminous intensity between the defective edge of the photovoltaic module and the normal part in the electroluminescent image is not significant,and only reflects low-frequency information.It is difficult to extract the geometric features of the defect surface,and there are difficulties in quantitative evaluation of defects.Physically,the emitted light from electroluminescence is essentially an electromagnetic wave.The magnetic field and electric field are orthogonal to each other and perpendicular to the propagation direction of photons so that electroluminescence has polarization characteristics.Using polarization imaging technology can enhance the edge contour and texture details of infrared images,the accuracy of target detection in complex environments is improved.Therefore,based on electroluminescence,this paper introduces polarization imaging technology and proposes the electroluminescence polarization defect detection method for crystalline silicon photovoltaic modules inspection.The main research contents are as follows:The first is the theoretical basis.Firstly,the research background and the commonly used detection methods for photovoltaic modules are introduced,followed by a detailed introduction to electroluminescence imaging technology and a review of relevant literature on electroluminescence polarization detection in recent years.Then,the composition and optical characteristics of photovoltaic cells and photovoltaic modules are introduced.Based on the mathematical model of electroluminescence of crystalline silicon photovoltaic cells,the detection principle and influencing factors of electroluminescence are analyzed.Finally,the polarization characteristics of light are introduced and common expressions of polarized light are given.The second is the study of polarization characteristics of electroluminescence in crystalline silicon photovoltaic modules.The polarization generation mechanism of crystalline silicon photovoltaic modules is studied,and the polarization transmission model of photovoltaic modules is explored.The impact of emission angle,bias voltage,and other factors on polarization characteristics is analyzed.A polarizing imaging system for electroluminescence of photovoltaic modules was built.Taking typical monocrystalline silicon photovoltaic panels and polycrystalline silicon photovoltaic panels as research objects,the factors affecting the polarization characteristics of electroluminescence were experimentally verified by changing the magnitude of the forward bias voltage and the emission angle.The results show that the electroluminescence process of photovoltaic modules has polarization characteristics,and is related to the external forward bias voltage and emission angle.The electroluminescence intensity of photovoltaic modules continuously rises to saturation with the increase of forward bias voltage,which is consistent with the theoretical mathematical model.The polarization degree of electroluminescence increases with the increase of emission angle,and first increases and then decreases rapidly with the increase of bias voltage.The third is the study of electroluminescence polarization characteristics in defective photovoltaic modules.Firstly,based on different production stages,various defects are summarized,and the impact of defects on the optical characteristics of photovoltaic modules is explored.The polarization transmission model of photovoltaic module electroluminescence is studied,and it is concluded that the polarization degree of photovoltaic module defect locations is related to factors such as roughness,emissivity,and so on.Then,using a three-dimensional topography instrument,the surface topography changes of photovoltaic modules were studied,and it was concluded that the presence of defects would affect the surface roughness of photovoltaic modules.Then,a polarization detection platform for electroluminescence of defective photovoltaic modules was built to experimentally explore the impact of different defects on the degree of polarization.The experimental results showed that the degree of polarization image can reflect the different degrees of defects.Finally,various defects were characterized and evaluated,and the characteristics and judgment methods of each defect in electroluminescence polarization images were described in detail.Visual detection of defects such as cracks,scratches,broken grids,and missing corners was achieved.Fourth,a defect detection method for electroluminescence polarization image fusion using Laplace pyramid and guided filter is proposed.Firstly,the obtained infrared light intensity image and the degree of polarization image are subjected to Laplace pyramid decomposition to obtain high and low frequency layered images.Then,guided filtering is used to enhance the high-frequency detail components.Then,the high-frequency and low-frequency parts are fused using the rules of maximum regional energy and weighted average regional energy,respectively.Finally the fused image is reconstructed.The results show that the overall brightness and contrast of the fused image are stronger,the edge texture information is richer,the defect characteristics of photovoltaic modules in the fused image are more prominent,and objective evaluation indicators such as information entropy,average gradient,standard deviation,and edge strength are significantly improved.The results are superior to other fusion methods,which verifies the effectiveness of the method.Figure [45] table [5] reference [81]...