Paper
27 September 2024 Research on intelligent safety monitoring system for water conservancy and hydropower engineering
Jiale Liu, Dangfeng Yang, Yuan Liu, Yong He, Fengyuan Jiang
Author Affiliations +
Proceedings Volume 13275, Sixth International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2024); 1327537 (2024) https://doi.org/10.1117/12.3037525
Event: 6th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2024), 2024, Wuhan, China
Abstract
The safety monitoring of hydroelectric projects holds significant importance for safety management during construction and the overall efficiency of the engineering works. Addressing the challenges of vast amounts of monitoring data, diverse data formats, and the complexity of engineering structures, where real-time monitoring is not feasible for most construction areas, an intelligent safety monitoring system for hydroelectric projects is proposed. This system achieves real-time monitoring throughout the entire process of engineering safety, primarily consisting of a monitoring data acquisition layer, a data transmission layer, a network service layer, and a digital resource layer. Additionally, it boasts comprehensive capabilities for engineering safety analysis and visual display. Successfully applied in engineering scenarios such as urban rail, hydropower stations, and dams, it has formed a comprehensive intelligent solution for the entire lifecycle of engineering safety monitoring, playing a crucial role in safeguarding the construction and safe operation of engineering projects. Therefore, it holds great potential for promotion and application.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Jiale Liu, Dangfeng Yang, Yuan Liu, Yong He, and Fengyuan Jiang "Research on intelligent safety monitoring system for water conservancy and hydropower engineering", Proc. SPIE 13275, Sixth International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2024), 1327537 (27 September 2024); https://doi.org/10.1117/12.3037525
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KEYWORDS
Safety

Engineering

3D modeling

Data modeling

Intelligence systems

Equipment

Data acquisition

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