Research on Fault Warning System for Hydroelectric Facilities Based on Cloud Computing and GAN

Authors

  • Qiuyue Zhong YCIH (Yunnan Construction and Investment Holding Group) No.1 Water Resources and Hydropower Construction Co., Ltd., Kunming 650501, Yunnan, China
  • Jiangkuan Zhao School of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, Handan 056038, Hebei, China

Abstract

Because hydropower facilities are one of the country’s important energy infrastructures, the safety of their operations is crucial to social and economic development, the security of lives and property, and the protection of the ecological environment. Traditional safety management methods usually rely on manual monitoring and a single system, resulting in long response times, difficulty in information integration, and difficulty in timely capturing potential risks. This approach often has information islands and data fragmentation problems, and cannot achieve comprehensive, real-time monitoring and early warning of facilities, increasing the probability of safety hazards. This study designed and implemented a hydropower facility safety management platform based on cloud computing. A distributed storage structure was used to store collected data and separately build a Kafka transmission architecture to connect the various departments of the platform and speed up the information transmission within the platform. It used generative adversarial network (GAN) technology to identify faults and issue early warnings through the transmission architecture. The experimental results show that during the data transmission process, the average transmission accuracy is 94.6%, the average transmission completeness is 98.2%, and the average transmission synchronization is 97.8%. At the same time, when the platform load is low, the response time can be as short as 0.89 seconds. The evaluation of the platform’s early warning capability showed that the AUC value of fault identification is 0.92. This study analyzed key indicators such as throughput, latency, and CPU usage of the platform, and demonstrated that the proposed system can still maintain stable operation in high load and complex environments. Through the application of cloud computing and distributed technology, the proposed hydropower facility
safety management platform significantly improves warning capabilities and system stability, ensuring efficient operation of the platform in complex environments and providing intelligent and real-time solutions for the safety management of hydropower facilities

Keywords: Hydropower facility; cloud computing; security management platform; generative adversarial networks; early warning capability

Cite As

Q. Zhong, J. Zhao, "Research on Fault Warning System for Hydroelectric Facilities Based on Cloud Computing and GAN",
Engineering Intelligent Systems, vol. 34 no. 3, pp. 413-422, 2026.

 

Downloads

Published

2026-05-01

Issue

Vol. 34 No. 3 (2026): International Journal of Engineering Intelligent Systems

Section

Article

License

The submission of a paper implies that, if accepted for publication, it will not be published elsewhere in the same form, in any language, without the prior consent of the publisher. Before publication, authors are requested to assign copyright to CRL Publishing Ltd. This allows CRL to sanction photocopying, and to authorize the reprinting of issues or volumes according to demand. Authors' traditional rights will not be jeopardized by assigning Copyright in this way, as they retain the right to reuse the material following publication, and to veto third-party publication.