Implementation of Artificial Intelligence in Bending Analysis of Propeller/Fan Blade

The bending of the blade is one of the dominating factors in the manufacturing considerations as it directly impacts the performance of propeller in terms of propulsion efficiency. The blade moulding equipment developed in-house has extensive control over the bending. After understanding the working mechanism of the instrument, a simplified model is created to perform the numerical analysis over the blade to inspect the nature of deformation. The theoretical and numerical analysis is performed assuming the contact between the rods of the equipment, and the blade is frictionless. The region of the bent propeller blade is scanned to know the deviation error. The AI tool to predict the required force per region for the blade the reformation was employed. Also, numerous factors contribute to the effect of net spring back occurs in the metal sheet. However, because of the limitations on the availability of the literature regarding formulation to add strain hardening and sheet preheating effects, one needs to approximate the solution. To approximately predict spring-back, factors such as bending force, material properties, sheet thickness, and boundary (support) conditions considered in the theoretical analysis and testing. The performance measurement was carried out for the same blade after the reformation and was found equally efficient (maximum error up to 7%). The error is caused due to the dent marks over the region and restored profile error.