SPEPC TECHNOLOGY
Solution
Reservoir Dam Safety Monitoring Solution
Background Introduction
Reservoir dams are the cornerstone of flood‑control safety, water‑supply security, and ecological health; their structural integrity directly affects the lives and property of downstream populations as well as the economic and social stability of the region.
As service life increases, extreme weather events become more frequent, and operational loads vary, dams face risks such as seepage anomalies, dam‑body deformation, and structural aging.
Traditional manual inspections and decentralized monitoring systems suffer from low efficiency, incomplete coverage, and delayed early warnings, making it difficult to meet the demands of refined, intelligent management in modern water‑conservation projects.
Accordingly, establishing an intelligent dam safety monitoring system that integrates comprehensive sensing, intelligent analysis, precise early warning, and efficient coordination—thereby shifting from “reactive response” to “proactive prevention”—has become a critical strategic task for enhancing the safety management of water‑related infrastructure and ensuring water security.
Solution Overview
This solution is a comprehensive smart water‑conservancy safety‑monitoring system that deeply integrates IoT, big data, artificial intelligence, and BIM/GIS technologies. The solution aims to enable the monitoring of reservoir dams… Digital monitoring and intelligent management across all factors and throughout the entire process. 。
The system deploys intelligent sensing devices—including GNSS receivers, vibrating-wire piezometers, radar water level gauges, rain gauges, video surveillance cameras, and array-type displacement sensors—at critical locations such as the dam body, foundation, spillway, and gate stations, enabling automated acquisition of multi‑parameter data on dam deformation (surface displacement and internal settlement), seepage (pore pressure, seepage rate, and phreatic line), water levels, rainfall, and video imagery.
Data is aggregated to the smart water‑conservation cloud platform via redundant communication networks, including 4G/5G, LoRa, and BeiDou. The platform leverages specialized analytical models and AI algorithms for in‑depth data mining and intelligent decision‑making, enabling real‑time assessment of safety conditions and proactive risk alerts.
Meanwhile, the platform integrates Rainfall monitoring, flood forecasting, operational scheduling simulation, and inspection & maintenance These services provide comprehensive technical support for the standardized, refined, and intelligent management and maintenance of reservoir dams.
FEATURES OF THE SOLUTION
All-weather, multi-parameter monitoring
High-Precision Deformation and Seepage Monitoring
Multi-source Fusion and Intelligent Early Warning
Digital Twin and 3D Visualization
“Technology-based prevention + human-based prevention” in highly efficient coordination
Redundant Communication and Low-Power Deployment
Rainfall Monitoring System
The integrated rainwater video monitoring station comprises rainfall monitoring in the reservoir area, water-level monitoring, AI-powered video surveillance, early-warning broadcasting, and a power supply system. By leveraging various intelligent sensing devices, it enables dynamic monitoring and real-time data collection of rainfall amounts, reservoir water levels, and regional intrusion detection and alerts, thereby achieving 24/7 remote automated monitoring and early warning.
Dam Safety Monitoring System
The main components of the dam safety monitoring system include the installation of deformation benchmarks, GNSS-based dam‑body displacement monitoring, piezometers (seepage pressure transducers), weirs for flow measurement, and other automated monitoring instruments, enabling 24‑hour online data acquisition and analysis of dam deformation, seepage pressure and flow, phreatic line position, and seepage discharge.
Deformation Monitoring
Typically, manual observations are conducted using installed observation piers; depending on the circumstances, GNSS‑based automated surface deformation monitoring may also be employed. Alternatively, GNSS‑based automated monitoring systems can be added alongside manual observations, with automation taking precedence and human oversight serving as a supplement, enabling comparative analysis of monitoring data and enhancing both efficiency and reliability.
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