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

Dali Xue; Desheng Wang; Shuqing Zhou; Fan Chen; Datie Huang

doi:10.1117/12.2680450

31 May 2023 Research on image recognition of power control system based on BHS-CTPN and AA-CRNN

Dali Xue, Desheng Wang, Shuqing Zhou, Fan Chen, Datie Huang

Proceedings Volume 12704, Eighth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2023); 127042U (2023) https://doi.org/10.1117/12.2680450
Event: 8th International Symposium on Advances in Electrical, Electronics and Computer Engineering (ISAEECE 2023), 2023, Hangzhou, China

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.

Citation Download Citation

Dali Xue, Desheng Wang, Shuqing Zhou, Fan Chen, and Datie Huang "Research on image recognition of power control system based on BHS-CTPN and AA-CRNN", Proc. SPIE 12704, Eighth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2023), 127042U (31 May 2023); https://doi.org/10.1117/12.2680450

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KEYWORDS

Detection and tracking algorithms

Control systems

Power grids

Convolution

Image processing

Feature extraction

Evolutionary algorithms

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