Start date:
11/01/2022
End date:
04/30/2024
Machine Learning models to analyze the performance of hydraulic dams
MOLINO is a tool that was designed and developed as an analytical and predictive algorithmic solution for the monitoring of the auscultation data of hydraulic dams. It obtains data, indicators and various elements that allows the user to make decisions aimed at the predictive maintenance of infrastructures and the improvement of safety.
Activities
The objective of the project is to be addressed by CIC’s research team by carrying out the following activities:
- Design and development of predictive algorithm SW modules based on the monitoring and analysis of hydraulic dam auscultation data.
- Assessing the effectiveness of advanced Machine Learning (ML) techniques for improving operational safety, increasing the service life of dams, reducing maintenance costs and contributing to greater efficiency in the management and operation of hydraulic infrastructures. To this end, critical variables such as water levels, water pressures, water temperatures and other relevant physical factors will be analyzed to identify patterns and detect potential risks.
- Design and development of a user interface to assist in the decision making process related to preventive maintenance of dam infrastructures, ensuring their structural integrity and safe operation.
Funding
This project is co-financed by the Government of Cantabria through the call for grant applications INNOVA 2022 from the Regional Ministry of Industry, Tourism and Innovation, Innovation as well as the Regional Ministry of Transport and Commerce.
