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- W4385688971 abstract "Hydropower station monitoring system collects a large number of system running signals, and it is critical to intelligently monitor these signals and timely process them, which can ensure the safe and stable operation of hydropower stations. However, it is quite challenging to achieve intelligent monitoring efficiency. There are problems such as various device types, complicated signal information and difficult extraction of latent knowledge. In this paper, we propose a novel intelligent monitoring framework of hydropower signals based on knowledge graph. Specifically, we first collect amount of operational unstructured log text data from a real-world hydropower monitoring system, and then propose a hydropower signal knowledge graph (HSKG) construction method by combining the semantic parsing technology and expertise in the field of hydropower operation. We further propose a BERT-BiGRU-CRF model for automatic entity extraction of collected data. Finally, we develop an intelligent signal analysis model based on the constructed HSKG. The experimental results on real-world datasets evaluate the effectiveness and efficiency of our method for intelligent hydropower signal monitoring." @default.
- W4385688971 created "2023-08-10" @default.
- W4385688971 creator A5074619284 @default.
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- W4385688971 date "2023-02-01" @default.
- W4385688971 modified "2023-09-27" @default.
- W4385688971 title "Intelligent Monitoring of Hydropower Signals Based on Knowledge Graph" @default.
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- W4385688971 doi "https://doi.org/10.1109/dsde58527.2023.00022" @default.
- W4385688971 hasPublicationYear "2023" @default.
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