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16 August 2023 Research on the construction of knowledge graph in the field of high speed rail vehicle equipment faults
Zhifan Lv, Qinghua Zhou
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Proceedings Volume 12787, Sixth International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2023); 127872I (2023) https://doi.org/10.1117/12.3004575
Event: 6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023), 2023, Shenyang, China
Abstract
In the daily maintenance and fault diagnosis of high-speed rail on-board equipment, a large amount of equipment fault data analysis has been accumulated, but the information of these fault analysis is too scattered to be effectively used by staff. In this paper, the construction of knowledge map in the field of high-speed rail vehicle equipment fault is preliminarily explored, and the knowledge map of high-speed rail vehicle equipment fault is constructed by combining top-down and bottom-up methods. In the process of entity extraction, this paper uses BERT+BiLSTM-CRF entity recognition model to extract entities. Through comparative analysis, BERT+BiLSTM-CRF model has a good effect of entity identification, and can identify and extract fault entities. Finally, a certain scale of vehicle-mounted equipment fault knowledge map is constructed according to the fault data of high-speed rail vehicle, which can effectively realize the structured storage and visual display of fault data and facilitate the guidance of vehicle-mounted equipment fault maintenance.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Zhifan Lv and Qinghua Zhou "Research on the construction of knowledge graph in the field of high speed rail vehicle equipment faults", Proc. SPIE 12787, Sixth International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2023), 127872I (16 August 2023); https://doi.org/10.1117/12.3004575
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KEYWORDS
Data storage
Visualization
Data modeling
Performance modeling
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