| KEYWORD |
Area Architecture
Advancement of Optical Motion Magnification for Vibration-based Assessment of Hydropower Systems
Thesis abroad
keywords COMPUTER VISION, DAMAGE DETECTION, HYDROPOWER SYSTEM, MACHINE LEARNING, MOTION ANALYSIS, STRUCTURAL ANALYSIS
Reference persons MARCO CIVERA, CECILIA SURACE
External reference persons Prof Alessandro Sabato, University of Massachusetts Lowell
Thesis type RESEARCH / EXPERIMENTAL
Description Computer Vision technologies, such as Optical Motion Magnification, are becoming more important in structural health monitoring and condition monitoring. The possibility of quantifying movements not visible to the naked eye using normal video cameras has increased the scientific community's interest in these systems.
The object of the thesis is the definition of a methodology for the use of Optical Motion Magnification to measure the vibrations of engines and turbines for the generation of electrical energy caused by mass imbalances or structural damage.
Specifically, starting from in-situ measurements carried out on energy generation systems (e.g. hydroelectric, wind, co-generation), the candidate will have to define a procedure to determine the dynamic response of the machinery under study, monitoring the system over time to identify damaged parts, and define a metric to classify the condition of the inspected parts/machinery.
The work involves an evaluation of the system in the laboratory (with predefined and known boundary conditions) and the possibility of testing the developed system in active hydroelectric plants in the region around Lowell, Massachusetts.
Required skills MATLAB, possibly prior knowledge of Machine Learning algorithms
Notes Average grade required: >= 27/30 and knowledge of the English language at least B2/C1 level
Deadline 23/11/2024
PROPONI LA TUA CANDIDATURA