A temperature field reconstruction method for spacecraft leading edge structure with optimized sensor array

Aimed at monitoring the aerodynamic heating on the spacecraft leading edge structure, a temperature field reconstruction method for curved surface using a distributed sensor array is proposed in this paper. Limited by the sensor number and system weight, a sparse sensor array is usually used to measure the temperatures at the discrete positions. Considering the majority of heat energy transfers on the leading edge surface rather than the hollow inside or thermal insulation material, the temperature field on the curved surface of leading edge structure can be reconstructed through inverse distance weighting (IDW) method with improved accuracy by introducing arc-length distances rather than straight-line distances. Furthermore, the non-dominated sorting genetic algorithm II (NSGA-II) is employed to optimize the distribution of the sensor array. Taking a three-dimensional spacecraft leading edge structure as an example, a finite element model is used to validate the proposed method. The influences of search radius and random initial population inputs on the optimized results are investigated. The results show that the use of search radius plays an important role in optimizing the arrangement of sensor array.