Sensitivity analysis of sensor location for damage detection in a wind turbine blade

Samuel da Silva (1) , Bruna Silveira Pavlack (1) , João Pedro Norenberg (1) , Americo Cunha Jr (2) , David García Cava (3)

1 UNESP - Universidade Estadual Paulista Júlio de Mesquita Filho = São Paulo State University
2 UERJ - Universidade do Estado do Rio de Janeiro [Brasil] = Rio de Janeiro State University [Brazil] = Université d'État de Rio de Janeiro [Brésil]
3 Edin. - University of Edinburgh

This work performs the sensitivity analysis of sensors located in a damaged composite wind turbine blade to identify the sensors with the most significant influence on a global damage index (DI). The methodology used obtains DIs from data-driven vibration Structural Health Monitoring (VSHM). First, a global DI with data from the sensors is used. From this global DI, the Polynomial Chaos–Kriging method is used to obtain a metamodel that quantifies the damage severity as a function of the DI. Subsequently, the global sensitivity analysis (GSA) is performed to analyse the influence of each sensor on the DI. The GSA method used is the Sobol’ indices. The results obtained from the sensitivity analysis of the sensors are satisfactory because the Sobol’ indices show that the sensors located in the damage path have greater sensitivity and influence on the DI. Studies of this nature are critical, as they make it possible to optimise the location of sensors for better damage detection and contribute to cost reduction.

Mots clés: sensitivity analysis; Sobol' indices; damage features; detection damage; composite wind turbine blade

Domaines: Vibrations [physics.class-ph]; Mécanique des solides [physics.class-ph]; Mécanique des structures [physics.class-ph]; Statistiques [math.ST]; Probabilités [math.PR]; Génie mécanique [physics.class-ph]

Samuel da Silva, Bruna Silveira Pavlack, João Pedro Norenberg, Americo Cunha Jr, David García Cava. Sensitivity analysis of sensor location for damage detection in a wind turbine blade. 6th Brazilian Conference on Composite Materials (BCCM 2022), Aug 2022, Ouro Preto, Brazil. ⟨hal-03754827⟩