Analytical Approach to Sampling Estimation of Underwater Tunnels Using Mechanical Profiling Sonars

Area of Science:

• Engineering
• Robotics
• Geophysics

Background:

• Hydroelectric power plants rely on extensive tunnel systems for water flow.
• Flooded tunnels pose inspection challenges due to their size and inaccessibility.
• Tunnel integrity is critical to prevent catastrophic failures and operational disruptions.

Purpose of the Study:

• To investigate the resolution of 3D tunnel maps generated by Unmanned Underwater Vehicles (UUVs) equipped with mechanical profiling sonars.
• To analyze the impact of sensor synchronization and occlusion on map quality.
• To derive analytical equations for estimating sampling resolution in underwater tunnel mapping.

Main Methods:

• Utilizing Unmanned Underwater Vehicles (UUVs) with mechanical profiling (scanning) sonar sensors.
• Developing analytical models to determine sampling resolution based on sonar parameters.
• Conducting experiments in simulated environments with multiple sonar sensors.
• Performing field tests within a large-scale power plant tunnel.

Main Results:

• Derived analytical equations for estimating underwater tunnel sampling resolution using sonar.
• Demonstrated the feasibility of generating 3D tunnel maps with multiple synchronized sonar sensors.
• Identified challenges related to sensor synchronization and occlusion in multi-sonar mapping.
• Presented the first 3D map of a large power plant tunnel using a single sonar sensor.

Conclusions:

• Unmanned Underwater Vehicles (UUVs) with sonar offer a viable solution for inspecting flooded hydroelectric tunnels.
• Multi-sensor sonar systems can enhance the resolution and reliability of 3D tunnel mapping.
• Further research is needed to optimize sensor synchronization and mitigate occlusion effects for improved mapping accuracy.