Wind turbine structural dynamics through multi-sensor monitoring

This thesis investigates the structural dynamics of a utility-scale wind turbine using a comprehensive field-scale monitoring approach. Focusing on a Senvion MM92 wind turbine located in southern Italy, the study employs a multi-sensor system to collect high-resolution operational and structural dat...

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Bibliographic Details
Author: Valencia Hurtado, Santiago
Format: master thesis
Publication Date:2025
Country:España
Institution:Universitat Politècnica de Catalunya (UPC)
Repository:UPCommons. Portal del coneixement obert de la UPC
Language:English
OAI Identifier:oai:upcommons.upc.edu:2117/442781
Online Access:https://hdl.handle.net/2117/442781
Access Level:Embargoed access
Keyword:Wind turbines
Spectrum analysis
Aerogeneradors
Anàlisi espectral
Àrees temàtiques de la UPC::Energies::Energia eòlica::Aerogeneradors
Description
Summary:This thesis investigates the structural dynamics of a utility-scale wind turbine using a comprehensive field-scale monitoring approach. Focusing on a Senvion MM92 wind turbine located in southern Italy, the study employs a multi-sensor system to collect high-resolution operational and structural data under diverse wind and loading conditions. Key objectives include the identification of modal parameters, assessment of frequency-domain behavior using Power Spectral Density (PSD) analysis, and detection of potential resonance conditions via Campbell diagrams. The monitoring system integrates strain gauges, accelerometers, and environmental sensors strategically placed on blades, the tower, and the nacelle. Data processing pipelines are developed using Python to ensure calibration accuracy, synchronization, and automated signal analysis. Results reveal distinct dynamic response patterns across operational regimes and demonstrate the system’s capability to detect harmonic excitations, modal shifts, and shutdown-induced transient behavior. The findings validate the effectiveness of field-based spectral analysis in capturing realistic structural behavior and inform safer, more resilient turbine designs under evolving industry conditions.