Research on image recognition of power control system based on BHS-CTPN and AA-CRNN

Symposium on Advances in Electrical, Electronics and Computer Engineering Pub Date : 2023-05-31 DOI:10.1117/12.2680450

Dali Xue, Desheng Wang, S. Zhou, Fan Chen, Datie Huang

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Abstract

With the continuous increase of the power grid scale, the amount of information handled by regulators is increasing. In order to solve the problem that all kinds of information and data cannot be exchanged, and to effectively control all kinds of events, the State Grid Ruian Power Supply Company has developed a set of intelligent control auxiliary system. Based on this, this paper proposes an image recognition method for power regulation and control system based on BHS-CTPN and AA-CRNN to detect and identify the content of the power regulation and control interface. The experiment shows that the method proposed in this paper can automatically identify and process the alarm information and dynamic operation data in combination with the intelligent regulation and control auxiliary system, and achieve full response to all kinds of information. Under the premise of ensuring security, the optimization of power grid operation management mode is realized, and the dispatching ability and response efficiency of power grid alarm are improved.

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基于BHS-CTPN和AA-CRNN的功率控制系统图像识别研究

随着电网规模的不断扩大，监管机构处理的信息量也在不断增加。为了解决各种信息和数据不能交换的问题，有效地控制各种事件，国网瑞安供电公司开发了一套智能控制辅助系统。基于此，本文提出了一种基于BHS-CTPN和AA-CRNN的功率调节与控制系统图像识别方法，以检测和识别功率调节与控制界面的内容。实验表明，本文提出的方法可以结合智能调控辅助系统对报警信息和动态运行数据进行自动识别和处理，实现对各类信息的充分响应。在保证安全的前提下，实现了电网运行管理模式的优化，提高了电网报警的调度能力和响应效率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Symposium on Advances in Electrical, Electronics and Computer Engineering

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