Measurement and testing report standard traceability knowledge base construction technology

Jin Wang; Yunlong Gu; Bo Peng; Li Wang

doi:10.1117/12.3033853

13 June 2024 Measurement and testing report standard traceability knowledge base construction technology

Jin Wang, Yunlong Gu, Bo Peng, Li Wang

Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 131802G (2024) https://doi.org/10.1117/12.3033853
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China

Abstract

The test and inspection business of metrology field and laboratory in the electric power field faces the problems of low degree of automation of experimental data flow, high degree of heterogeneity of sensor transmission signals, low degree of resource management sharing and low degree of intelligence. In the paper, the CTC algorithm is used for report recognition, and deep learning is used to achieve the layout analysis of the report in different formats, and to complete the multi-mode data metrology testing image recognition processing and the construction of the knowledge base. The experimental results show that the image recognition technology proposed in the article can effectively extract the data in metrology inspection images and form a knowledge base.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jin Wang, Yunlong Gu, Bo Peng, and Li Wang "Measurement and testing report standard traceability knowledge base construction technology", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 131802G (13 June 2024); https://doi.org/10.1117/12.3033853

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KEYWORDS

Semantics

Detection and tracking algorithms

Data modeling

Performance modeling

Standards development

Education and training

Feature extraction

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