Optimization of Helicopter Rotor Airfoil Wind Tunnel Test Model Based on Intelligent Algorithm

Abstract

The helicopter rotor wing wind tunnel test model is the basic equipment for helicopter wind tunnel test research. On the premise of meeting the requirements of corresponding strength, stiffness, natural frequency and stability, the model mass needs to be light enough to meet the requirements of heave vibration test. To this end, this paper proposes the structure of aluminum alloy skeleton + carbon fiber reinforced composite skin, and in order to obtain good performance, the following steps are used to optimize the parameters of the test model structure: 1. Establish an RBF neural network approximation model; 2. Use multiple island genetic algorithm (MIGA) and the sequential quadratic programming algorithm (SQP) are combined to optimize the thickness of the skeleton and composite materials. The optimization results show that the quality of the model is reduced by 34.05% under the condition that the corresponding requirements of strength, stiffness, natural frequency and stability are met.

Stock Quantitative Intelligent Investment Model Based on Machine Learning Algorithms

“…When the sample size is not large, selecting too many categories can result in too few days for some categories. For the above reasons, the author directly assumes that there are four categories of implicit states [16].…”