Hydroelectric Power Plant Penstock Cavitation Monitoring.

Cavitation damage in penstock and turbine runner causing unplanned downtime.

REF: ENR-09
Energy & Infrastructure

Operational
Mechanism.

Technical details of field integration, data flow, and autonomous decision algorithms.

Edge Hardware

High Frequency Acoustic Sensor Array
Ultrasonic Thickness Gauge
Thermal Camera
Vibration Accelerometer

Artificial Intelligence

Navigation (SLAM)

Inclined and wet surface SLAM navigation along penstock pipeline

Perception & Analysis

Cavitation Frequency Analysis and Pipe Wall Thickness Trend Prediction (Predictive)

Autonomous Workflow

The robot patrols along the HPP penstock pipeline; acoustic sensors continuously listen for ultrasonic frequencies caused by cavitation.

Ultrasonic thickness gauge periodically measures pipe wall thickness, calculates wear trend, and predicts remaining life.

Vibration accelerometer and thermal camera data are correlated to evaluate turbine runner and lateral wear risk.

Alarm transmitted to SCADA when cavitation level exceeds critical threshold; turbine operating parameters automatically optimized.

Operational ROI.
Strategic Decision.

EXPECTED BALANCE IMPACT

Annual $88,000 maintenance and yield optimization savings. ROI: 4.4x | Payback: 1.0 Years.

Extends life by 3+ years by deferring average $350K turbine runner replacement cost through early cavitation detection.

Review Your Custom
Autonomous Operation
Plan On-Site.

Our engineers are ready to present this robotic integration plan, specially simulated for your facility, to your team. Let's confidently launch your business's digital transformation.