Abstract In this study, we propose using an unmanned aerial vehicle infrared thermal imager to obtain infrared video, and using image processing technology to process the acquired video. Moreover, based on research regarding traditional algorithms, an improved super green algorithm is proposed, and a feature analysis is conducted according to the actual situation. In this study, an effective identification model was designed for the most common types of faults, the most common electrical equipment components for research were collected, tests for analyzing the effectiveness of the algorithm were designed, and relevant data and images were recorded. The research shows that the proposed algorithm has validity, and can provide a theoretical reference for subsequent related research.

中文翻译：

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基于改进超绿色算法的电力设备故障识别图像处理

摘要 在本研究中，我们提出使用无人机红外热像仪获取红外视频，并利用图像处理技术对获取的视频进行处理。此外，在研究传统算法的基础上，提出了一种改进的超级绿色算法，并根据实际情况进行了特征分析。本研究针对最常见的故障类型设计了有效的识别模型，收集了最常见的用于研究的电气设备部件，设计了分析算法有效性的测试，并记录了相关数据和图像。研究表明，该算法具有有效性，可为后续相关研究提供理论参考。