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Smart Inspection of Hydraulic Turbine Blades

Sponsor: Jonatan Ross 
Leaders: Fernando de Almada & Waldson Melo

How can we perform automated and efficient inspections of hydraulic turbine blades, reducing the need for shutdowns, avoiding the dewatering of the Generating Unit, and increasing the precision of wear monitoring?

Challenge Description:

The current inspection process for hydraulic turbine blades involves lengthy scheduled shutdowns and methods that do not enable short-term, continuous, and low-cost operational monitoring of wear progression. This scenario causes significant operational impacts, such as reduced hydraulic efficiency, extended unplanned downtime, operational difficulty in simultaneously addressing multiple units requiring corrective interventions, and failure risks that could compromise equipment integrity.

Furthermore, each facility presents unique characteristics—such as different types of erosion (cavitation or a combination of abrasion and cavitation) and turbine configurations (horizontal or vertical)—which require flexible and adaptable solutions. Traditional technologies like borescopy are used in this context, but they have limitations in terms of accuracy, physical intervention requirements, and the scope of analysis.

The purpose of this challenge is to seek innovative solutions to inspect turbine blades in new ways—reducing the need for extended downtime, improving the efficiency of erosion monitoring and maintenance planning processes, capturing precise wear data, and enhancing operational safety.

Solution Requirements

  • Ability to inspect without dewatering the machine (i.e., without the need for stoplog panel installation, dewatering the Generating Unit, or requiring personnel access to the turbine rotor area).
  • Accurate capture of wear measurements (length, width, and depth), with a maximum measurement error of ≤ 1 mm.
  • Flexible solution suitable for various turbine configurations (horizontal and vertical, Kaplan and Francis types).
  • Generation of technical reports to support decision-making regarding intervention needs.
  • Possibility of integration with existing maintenance and operations systems.
  • User-friendly and intuitive interface for users.

 

Possible Technologies:

Solutions may include, but are not limited to:

  • Remotely Operated Vehicles (ROVs) or Underwater Drones – Equipped with cameras and sensors to perform inspections in submerged or hard-to-access environments
  • Advanced Imaging and 3D Reconstruction Solutions – Such as underwater LIDAR, automated photogrammetry, or high-resolution 3D optical cameras.
  • Next-Generation Borescopy or Advanced Endoscopic Technologies – As long as they overcome the limitations of traditional approaches, offering greater accuracy, coverage, and reduced need for physical intervention.
  • Digital Twins and Numerical Simulation – Numerical modeling (Computational Fluid Dynamics, Finite Element Analysis, or a combination of both) for analyzing flow behavior, blade conditions, and predicting wear based on real operational data.
  • Artificial Intelligence for Data and Image Analysis – For automated diagnostics and classification of wear types.
  • Inductive Sensing-Based Measurement – Provided it delivers accurate readings and allows for effective mapping, considering the large dimensions of the turbines.

Business Impacts:

  • Increased inspection accuracy, with precise detection of blade wear.
  • Reduced operational costsby minimizing long and unplanned shutdowns.
  • Improved operational efficiencythrough greater turbine availability.
  • More accurate maintenance planningbased on real-time and continuous data.
  • Higher safety standardsby avoiding manual physical access in risky environments.

Expected Benefits:

  • Innovation in blade inspection processes, reducing human effort and time spent on the activity.
  • Prevention of critical failures, avoiding efficiency losses and emergency repair costs.
  • Extended equipment lifespanthrough more accurate and continuous monitoring.
  • Greater reliability in decision-making, supported by qualified data and structured historical records.
  • Contribution to the digital transformation of operations, using innovative technologies applied to predictive maintenance.

Deadline: The proposal submission form will be available until August 22, 2025.

Questions: For questions or additional information, send an email with the subject line containing the Title of this Challenge to: innovationgrid@eletrobras.com.

Hydraulic turbine blades | Wear monitoring | Automation | Cavitation erosion | Predictive maintenance | Underwater technology | Remotely operated vehicles (ROVs) | 3D reconstruction | Advanced boroscopy | Digital twins | Numerical simulation | Operational efficiency | Operation digitalization | Artificial Intelligence (AI) | Inductive sensing | Operational safety