Moving Accelerometers to the Tip: Monitoring of Wind Turbine Blade Bending Using 3D Accelerometers and Model-Based Bending Shapes

Abstract

Increasing the length of wind turbine blades for maximum energy capture leads to larger loads and forces acting on the blades. In particular, alternate bending due to gravity or nonuniform wind profiles leads to increased loads and imminent fatigue. Therefore, blade monitoring in operation is needed to optimise turbine settings and, consequently, to reduce alternate bending. In our approach, an acceleration model was used to analyse periodically occurring deviations from uniform bending. By using hierarchical clustering, significant bending patterns could be extracted and patterns were analysed with regard to reference data. In a simulation of alternate bending effects, various effects were successfully represented by different bending patterns. A real data experiment with accelerometers mounted at the blade tip of turbine blades demonstrated a clear relation between the rotation frequency and the resulting bending patterns. Additionally, the markedness of bending shapes could be used to assess the amount of alternate bending of the blade in both simulations and experiment.s The results demonstrate that model-based bending shapes provide a strong indication for alternate bending and, consequently, can be used to optimise turbine settings.

Digital Twins for Wind Energy Conversion Systems: A Literature Review of Potential Modelling Techniques Focused on Model Fidelity and Computational Load

“…However, accelerometers placed along the blades can provide useful data on the force distribution [70]. These data can be fed to a high fidelity numerical model, e.g., a Finite Element Method (FEM) structural model as used for modal analysis of the blades in [71,72].…”

“…Nevertheless, it allows combining the merits of different modelling techniques eventually leading to a more realistic virtual replica. Computational Fluid Dynamics [69] FEM structural blade model [70][71][72] Large Eddy Simulation (LES) [78][79][80] FEM model of turbine shaft [103] FEM model of the tower and support structure [89,90] Electromagnetic FEM [109][110][111] Dynamic switching models [127][128][129] Conduction and switching loss models [130,131] Transient wide-bandgap component models [132] Full pitch drivetrain models [150][151][152][153] Full yaw drivetrain models [154,155] Blade-Element Momentum [57] Extensions -Tip losses [60,61] -Dynamic stall [62,63] -Blade flexibility [64,65] -Tower and nacelle flow disturbance [66] -Gaussian [82] or Curl [83] wake model Surrogate models [73][74][75] Multi-body drivetrain model [101,102] Multi-body tower and foundation model [84][85][86]<...>…”

Vibration-Based Fingerprint Algorithm for Structural Health Monitoring of Wind Turbine Blades

“…Those two aspects intertwine, i.e., a reduction of blade bending and loads, reduces vibrations and vice versa. This study solely focused on monitoring blade vibrations; however, our proposed sensing principle is also suited for monitoring blade bending as studied in [4]. In general, blade vibrations refer to global properties, e.g., eigenfrequencies, and local properties, e.g., increased vibrations due to fluttering at the blade tip.…”

Precision blade deflection measurement system using wireless inertial sensor nodes

“…Loss and Bergmann 19 employed accelerometer measurements and pattern recognition algorithms to describe alternating blade bending resulting from wind shear, gravitational effects, yaw, and tower shadow. Measurements were taken by three long‐term surveys on an operating wind turbine with 60‐m blade length and are in great accordance with simulated model‐based bending shapes.…”