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Orthogonal modulation based light beam induced current method for anti-noise defect detection in photovoltaic cells

解调 调制(音乐) 噪音(视频) 信号(编程语言) 灵敏度(控制系统) 光学 还原(数学) 固定模式噪声 采样(信号处理) 计算机科学 材料科学 频道(广播) 梁(结构) 信噪比(成像) 电子工程 探测器 图像传感器 人工智能 声学 数学 物理 电信 工程类 几何学 图像(数学) 程序设计语言
作者
Dongwen Gan,Quan Lei,Fan Zhu,Kai Xie,Junmei Bai
出处
期刊:Solar Energy [Elsevier BV]
卷期号:245: 158-164 被引量:4
标识
DOI:10.1016/j.solener.2022.08.058
摘要

In this paper, orthogonal modulation theory is introduced into light beam-induced current (LBIC) scanning to develop an orthogonal modulation-based LBIC (OMLBIC) method that is proposed for anti-noise defect detection applications in photovoltaic cells. In the proposed method, the response signal from the scanning area is treated similarly to the characteristics of a communication channel; first, orthogonal structured light patterns are generated to illuminate the scanning area surface, the combined current output of the entire device is then measured for each pattern, and demodulation is finally performed to extract the signal precisely from the noise. The feasibility of the proposed method and its detection performance were evaluated. The experimental results indicate that the proposed method can cause a maximum mean square error (MSE) reduction of 16,384 times with 128 × 128 scanning points, and it provides an enhanced direct link between the inherent spatial non-uniformities and the overall current map for the sample. When compared with the conventional LBIC method, the OMLBIC method provided increased consistency during noisy scanning, greater detail in defect detection, and a reduction in the sensitivity to noise, without requiring any time-consuming increase in sampling or hardware upgrades. The association between the noise elimination effect and the size of the structured light pattern was also studied to provide a superior system configuration. The proposed method shows major potential for improvement in the defect detection accuracy and classification of photovoltaic cells in industrial applications.
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