Ultrafast High-Resolution Solar Cell Cracks Detection Process

Abstract

This paper presents the advancement of an ultrafast high-resolution cracks detection in solar cells manufacturing system. The aim of the developed process is to (i) improve the quality of the calibrated image taken by a low-cost conventional electroluminescent (EL) imaging setup, (ii) proposing a novel methodology to enhance the speed of the detection of the solar cell cracks, and finally (iii) develop a proper procedure to decide whether to accept or reject the solar cell due to the existence of the cracks. The proposed detection process has been validated on various cracked/free-crack solar cell samples, evidently it was found that the cracks type, size and orientation are more visible using the proposes method, while the speed of calibrating the EL images are in the range of 0.1s to 0.3s, excluding the EL imaging time.

Investigating the Impact of Cracks on Solar Cells Performance: Analysis Based on Nonuniform and Uniform Crack Distributions

“…4(c), it is perceived that there is a uniform and marginal reduction of compared to the nonuniform crack distribution; this can be attributed to the lower localized increase of the series resistance. As an example, in the area labelled as "crack #1", the is equal to 36.91 mA/cm 2 , the corresponding loss being 5.1%, as calculated using (7). × 100 = 5.1% (7) As a result, the value is still positive; it indicates no reverse current flowing, which means no overheating is present in the solar cell.…”

“…Another interesting method proposed by Dhimish et al [6] exploits a digital-based algorithm called the "ORing method", by virtue of which the cracks size, location, orientation are more visible; at the same time, it takes up to 30 seconds to perform the calibration process. The same ORing method was also utilized by Dhimish & Mather [7], who further reduced the detecting and calibration time using an adjusted segmentation algorithm. The calibrated EL images can be processed within 0.1-0.3 seconds, excluding the EL imaging time, taking up to 5 seconds.…”

Mitigating Potential-Induced Degradation (PID) Using SiO2 ARC Layer

“…To perform the PID test on the solar cell samples, PIDcon PID-tester has been used. The main characteristics of this tester are that no climate chamber is necessary during the PID test and no lamination of the solar cells is required [25]. The leakage current, output power and I-V curve also can be measured using this device.…”

Deep Learning-Based Algorithm for Multi-Type Defects Detection in Solar Cells with Aerial EL Images for Photovoltaic Plants

“…In [19], a model is proposed to predict PV module electrical properties from EL image features using pixel intensity-based and machine learning-based classification algorithms. In [20], the detection of a crack in the PV module manufacturing system is presented and the proposed solution can identify the cells with cracks with high accuracy. In [21], the effect of crack distributions over a solar cell in terms of output power, short-circuit current density and open-circuit voltage was investigated.…”

“…The details of the previous work [12][13][14][15][16][17][18][19][20][21][22][23][24][25] are presented in Table 1. The limitations of these solutions can be summarized as follows: (1) Most images used in the previous studies are collected during the factory inspection and the resolution of the images captured during the factory inspection is generally much higher than those collected during the field inspection using the unmanned aerial vehicle (UAV).…”