Water conservancy safety monitoring system and method based on big data

Abstract

The invention discloses a water conservancy safety monitoring system and method based on big data, and relates to the technical field of water conservancy safety, and the system comprises a monitoring node, a monitoring center, a safety analysis module and a threat evaluation module. The monitoring nodes are used for monitoring water flow information of seepage at specific positions of all areas of the water conservancy project and sending the information to the monitoring center. The monitoring center is used for preprocessing the current water flow information, transmitting the preprocessed water flow information to a safety analysis module for safety analysis, determining the safety condition of seepage at each position according to a deviation coefficient, performing early warning in time, and allocating corresponding engineers to perform maintenance and reinforcement, so that the safety of the water conservancy project is improved; and the threat evaluation module is used for performing seepage threat coefficient analysis on the seepage maintenance information with the timestamp stored in the database, determining a corresponding information acquisition instruction according to a seepage threat coefficient, and adjusting the acquisition frequency, so that an engineering area with high seepage threat is monitored in a focused manner, and the water conservancy safety monitoring efficiency is improved.

Description

technical field [0001] The invention relates to the technical field of water conservancy safety, in particular to a water conservancy safety monitoring system and method based on big data. Background technique [0002] Seepage occurs due to water level difference after dams and water buildings retain water, so that part of the water seeps into the dam body and foundation, forming a seepage field in the foundation, resulting in soil flow, piping or landslides; data show that water conservancy engineering accidents ( Especially dam accidents) are mostly caused by seepage. Therefore, it is very important to monitor the seepage state of water conservancy projects, but the existing water conservancy safety monitoring system cannot intelligently identify the key monitoring areas of engineering areas with high seepage threats, and improve Water conservancy safety monitoring efficiency; therefore, we propose a water conservancy safety monitoring system and method based on big data. ...

AI Technical Summary

Problems solved by technology

[0002] Seepage occurs due to water level difference after dams and water structures retain water, so that part of the water seeps into the dam body and foundation, forming a seepage field in the foundation, resulting in soil flow, piping or landslides; data show that water conservancy engineering accidents ( Especially dam accidents) are mostly caused by seepage. Therefore, it is very important to monitor the seepage state of water conservancy projects, but the existing water conservancy safety monitoring system cannot intelligently identify the key monitoring areas of engineering areas with high seepage threats, and improve Water conservancy safety monitoring efficiency; therefore, we propose a water conservancy safety monitoring system and method based on big data

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