Wind energy is one of the cleanest methods of producing electricity. It plays a major role in the transition towards green energy. It is estimated that the installed capacity of wind energy will cover more than 6 % of total global electricity demand by the end of 2019. As the dem
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Wind energy is one of the cleanest methods of producing electricity. It plays a major role in the transition towards green energy. It is estimated that the installed capacity of wind energy will cover more than 6 % of total global electricity demand by the end of 2019. As the demand grows the requirement for bigger wind turbine also grows. Each year larger wind turbine blades are being manufactured to satisfy the growing demand, resulting in high manufacturing cost and operation and maintenance cost. The main reasons for wind turbine blade failures are poor design, material failure, power regulator failure, extreme load buckling, lightning strikes, foreign object damage and human errors. The failure rate of the wind turbine blade is around 7 % compared to other components of wind turbine. So, an effective and proactive monitoring system for the wind turbine blades becomes necessary due to the large downtime associated with failure and high replacement cost. The main objective of this thesis is to use smeared crack modelling and integrating it with FEM tools (ANSYS 18.2) to identify the damage in the wind turbine blade. The concept that the modal parameters such as natural frequency, mode shape and damping will be affected when a structure is damaged, is used to identify and localize the damaged elements. First, spar cap - shear web assembly is modelled as simple "I" beam in ANSYS. The dimension of the blade is measured from the "NedWind 40 turbine" provided by LM Wind Power. The structure has been modelled using composite materials. The spar cap fibres are laid at 0 ̊ and the fibres of face sheet are laid at ± 45 ̊. One end of the structure is fixed to simulate the actual working conditions. Similarly, the material property of all parts was chosen to represent the actual wind turbine blade. Second, damage is introduced into the structure in the form of microscopic damping into the material property. To incorporate damping into the structure, the loss factor obtained from experiment is used. The damage modelling is done for different severity at different locations of the modelled structure. Third, the eigen value and eigen vector for different microscopic damping coefficient is extracted. Modal damping of the structure is calculated using the extracted eigen value. And eigen vector is used to calculate the phase angle of each elements. The phase angle of each element is plotted to localize the damaged elements. The results show that this method is suitable for identifying defects near the fixed end and in the midsection of a wind turbine blade. Also,1st flap wise and edge wise bending frequencies are suitable for identifying the defects near the fixed end and 2nd flap wise bending frequency is suitable for identifying the defect near the mid area.
