基于深度学习的变电设备缺陷图像识别与分类技术研究

Research on defect image recognition and classification of substation equipment based on deep learning

摘要: 本文提出了一种基于深度学习的变电设备缺陷图像识别与分类技术，通过预处理和数据增强，采用卷积神经网络模型进行训练和优化，构建了高精度的图像分类模型。实验结果表明，该技术在变电设备缺陷分类任务中表现出较高的准确率和鲁棒性。

Abstract: This paper proposes a deep learning-based defect image recognition and classification technology for substation equipment. The experimental results show that the image recognition method based on deep learning shows high accuracy and robustness in the fault classification task of substation equipment.