Detection of Micro-Cracks in Electroluminescence Images of Photovoltaic Modules

2020 ◽  
Author(s):  
Natasha Mathias ◽  
Farheen Shaikh ◽  
Chirayu Thakur ◽  
Sweekrithi Shetty ◽  
Pratibha Dumane ◽  
...  
Keyword(s):  
Photovoltaic Modules ◽  
Micro Cracks

scholarly journals Solar Cell Cracks and Finger Failure Detection Using Statistical Parameters of Electroluminescence Images and Machine Learning

2020 ◽  
Vol 10 (24) ◽  
pp. 8834
Author(s):  
Harsh Rajesh Parikh ◽  
Yoann Buratti ◽  
Sergiu Spataru ◽  
Frederik Villebro ◽  
Gisele Alves Dos Reis Benatto ◽  
...  
Keyword(s):  
Machine Learning ◽  
Failure Detection ◽  
Machine Learning Algorithms ◽  
Feature Descriptor ◽  
Statistical Parameters ◽  
Photovoltaic Modules ◽  
Micro Cracks ◽  
Wide Range ◽  
Different Types ◽  
Module Performance

A wide range of defects, failures, and degradation can develop at different stages in the lifetime of photovoltaic modules. To accurately assess their effect on the module performance, these failures need to be quantified. Electroluminescence (EL) imaging is a powerful diagnostic method, providing high spatial resolution images of solar cells and modules. EL images allow the identification and quantification of different types of failures, including those in high recombination regions, as well as series resistance-related problems. In this study, almost 46,000 EL cell images are extracted from photovoltaic modules with different defects. We present a method that extracts statistical parameters from the histogram of these images and utilizes them as a feature descriptor. Machine learning algorithms are then trained using this descriptor to classify the detected defects into three categories: (i) cracks (Mode B and C), (ii) micro-cracks (Mode A) and finger failures, and (iii) no failures. By comparing the developed methods with the commonly used one, this study demonstrates that the pre-processing of images into a feature vector of statistical parameters provides a higher classification accuracy than would be obtained by raw images alone. The proposed method can autonomously detect cracks and finger failures, enabling outdoor EL inspection using a drone-mounted system for quick assessments of photovoltaic fields.

The risk of power loss in crystalline silicon based photovoltaic modules due to micro-cracks

2011 ◽  
Vol 95 (4) ◽  
pp. 1131-1137 ◽  
Author(s):  
M. Köntges ◽  
I. Kunze ◽  
S. Kajari-Schröder ◽  
X. Breitenmoser ◽  
B. Bjørneklett
Keyword(s):  
Power Loss ◽  
Crystalline Silicon ◽  
Photovoltaic Modules ◽  
Micro Cracks ◽  
Silicon Based

Properties of Self-Compacting Cementitious Composite Materials Containing Cement Kiln Dust Powder

2020 ◽  
Vol 38 (6A) ◽  
pp. 879-886
Author(s):  
Ahmed S. Kadhim ◽  
Alaa A. Atiyah ◽  
Shakir A. Salih
Keyword(s):  
Composite Materials ◽  
Total Porosity ◽  
Cement Kiln Dust ◽  
Cement Kiln ◽  
Cementitious Composite ◽  
Cement Dust ◽  
Micro Cracks ◽  
Load Carrying ◽  
Sustainable Materials ◽  
Kiln Dust

This paper aims to investigate the influence of utilization micro cement kiln dust as a sustainable materials additive in order to reduce the voids and micro cracks in the cementitious mortar materials which cause a drastic reduction in the load carrying capacity of the element. Its therefore very important to decrease the pores and enhance the mechanical strength of the cementitious composite materials. In this article, the properties of self-compacting mortar containing micro cement dust additive was experimentally assessed. Micro cement dust powder was added to the self-compacting mortar in (1, 2, 3, 4 and 5 %) percentage by weight of cement to be used as cementitious sustainable materials. The experimental results indicated that the modification and enhancement of the workability of fresh mixture and the mechanical strengths of self-compacting mortar were increased as micro cement dust additives increases. Also; the water absorption and total porosity were decreased with increases of micro cement dust powder.

Temperature and Humidity Dependent Reliability Analysis of RGB LED Chips

2006 ◽  
Author(s):  
Jun-Xian Fu ◽  
Shukri Souri ◽  
James S. Harris
Keyword(s):  
Reliability Analysis ◽  
Printed Circuit Board ◽  
Light Emitting Diode ◽  
Circuit Board ◽  
Light Emitting ◽  
Printed Circuit ◽  
Root Cause ◽  
Micro Cracks ◽  
Temperature And Humidity

Abstract Temperature and humidity dependent reliability analysis was performed based on a case study involving an indicator printed-circuit board with surface-mounted multiple-die red, green and blue light-emitting diode chips. Reported intermittent failures were investigated and the root cause was attributed to a non-optimized reflow process that resulted in micro-cracks and delaminations within the molding resin of the chips.

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