Multiobjective Optimization of Structure and Robustness of a Split Parallel Multicomponent Strain Sensor

Abstract

A novel split parallel multicomponent strain sensor structure layout is proposed based on the special requirements of the helicopter rotor airfoil wind tunnel test for measuring aerodynamic sensors. The sensor consists of two splits with the same configuration; the performance of the sensor not only depends on the split structure of the sensor but also depends on the assembly relationship between the splits. Three steps have been performed so as to enhance the technical performance of the sensor. First, the RBF neural network approximate model and the second-generation nondominated sorting genetic algorithm are used to optimize the split of sensor deterministically; secondly, the rotor airfoil wind tunnel test model and the sensor finite element system model are established, and the 6 σ robustness analysis is carried out; finally, the 6 σ robust multiobjective optimization has been carried out considering the sensor split processing errors and the assembly errors. The results show that, compared to initial designed sensors, the sensitivity of the three components of the sensor is increased by 285.46%, 284.95%, and 151.5%, respectively, and the maximum equivalent stress is reduced by 28.4%; the interference to the three components is reduced by 97.82%, 92.83%, and 99.8%, respectively, and the quality is reduced by 25.74%. Meanwhile, the quality level of the sensor was promoted, and the sensitivity of the response to assembly and manufacturing errors were reduced. These results exhibit that the structural layout, optimized path, and method in this strain sensor are suitable for the needs of helicopter rotor airfoil wind tunnel test.