LiDAR-Driven Modal Identification for Wind Turbine Faults

Association Bernard Gregory; Lyon; Sur place; EUR 23 000 - 28 000; Plein temps

Résumé du poste

Association Bernard Gregory is seeking candidates for a PhD position focused on modal identification methods using LiDAR-based full-field measurements. The project addresses fault detection in both onshore and offshore wind turbines, integrating OMA techniques with LTP system modeling.

The role requires a University Master degree in Applied Mathematics or Mechanical Engineering and English at CEFR B2 level.

Qualifications

• University Master degree in Applied Mathematics or Mechanical Engineering.
• English level B2 (CEFR).

Responsabilités

• Develop modal identification methods for LiDAR-based measurements.
• Integrate modeling of Linear Time-Periodic (LTP) systems for rotating structures like wind turbines.
• Define detectability thresholds for wind turbine defects under uncertainty.

Connaissances

System identification

OMA

SSI

LiDAR

Video analysis

UAV

SHM

Wind turbines

LTP systems

Formation

Master degree in Applied Mathematics or Mechanical Engineering

Outils

LiDAR

Video

UAV

Description du poste

Association Bernard Gregory is seeking candidates for a PhD position focused on modal identification methods using LiDAR-based full-field measurements. The project addresses fault detection in both onshore and offshore wind turbines, integrating OMA techniques with LTP system modeling.

The role requires a University Master degree in Applied Mathematics or Mechanical Engineering and English at CEFR B2 level.