This paper proposes a deep-learning-based wireless sensor system that uses an embedded two-dimensional (2D) light-emitting diode (LED) array to display measured sensor data and remote data transmission to detect nuclear power plant (NPP) equipment defects. The frequent use of electromagnetic waves often interferes with the operation of NPP. Therefore, we devised a wireless image transmission network using a 2D LED array panel that includes a sensor module and a camera to capture LED array images. Based on the experimental results, the proposed method adopting deep-learning-based LED array data extraction produces reliable digital data restoration performance in terms of classification accuracy, even in a complex noise environment.

中文翻译：

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使用远程发光二极管阵列数据传输基于深度学习的核电站故障检测

本文提出了一种基于深度学习的无线传感器系统，该系统使用嵌入式二维 (2D) 发光二极管 (LED) 阵列来显示测量的传感器数据和远程数据传输，以检测核电站 (NPP) 设备缺陷。电磁波的频繁使用往往会干扰核电厂的运行。因此，我们设计了一个使用 2D LED 阵列面板的无线图像传输网络，该面板包括一个传感器模块和一个摄像头来捕捉 LED 阵列图像。基于实验结果，所提出的方法采用基于深度学习的 LED 阵列数据提取，即使在复杂的噪声环境下，在分类精度方面也能产生可靠的数字数据恢复性能。