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首页> 外文会议>IEEE International Conference on Advanced Power System Automation and Protection >Transfer Learning Based Equivalent Magnetization Hysteresis Recognition Algorithm for Transformer Protection
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Transfer Learning Based Equivalent Magnetization Hysteresis Recognition Algorithm for Transformer Protection

机译：基于转移学习的变压器保护等效磁化磁滞识别算法

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Power transformer is a key equipment of power system, and transformer protection is still an important research hotspot for the safe operation of the electric power system. Kinds of transform protection algorithms have been proposed including many artificial intelligence (AI) algorithms. But the requirement of big data limits the generalization of AI algorithms. Different types of ferromagnetic material have the same shape of magnetization hysteresis which is an effective indicator for transformer protection. We propose transfer learning based equivalent magnetization hysteresis recognition algorithm for transformer protection which use little trial/real data with simulation data to solve the few-shot problem. In our experiments, we validate that the proposed algorithm can reach an improved accuracy compared with other two mentioned in the article.
机译：电力变压器是电力系统的关键设备，变压器保护仍然是电力系统安全运行的重要研究热点。已经提出了包括许多人工智能（AI）算法在内的各种变换保护算法。但是大数据的需求限制了AI算法的推广。不同类型的铁磁材料具有相同的磁化磁滞形状，这是变压器保护的有效指标。我们提出了基于转移学习的变压器保护等效磁化磁滞识别算法，该算法使用很少的试验/实际数据和仿真数据来解决短路问题。在我们的实验中，我们验证了与本文中提到的其他两种算法相比，该算法可以达到更高的精度。

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