Sparse Full Focus Optimization Algorithm Based on Improved Adaptive Genetic Algorithm

Ultrasonic phased array technology can achieve high precision imaging detection, but the widely used full matrix capture full focus imaging method has the disadvantage of long computation time resulting in low real-time performance. In order to meet the problems of real-time continuity and imaging resolution of full-focused ultrasonic array imaging, the traditional adaptive genetic algorithm has certain defects, and the algorithm is easy to fall into local optimal solution and search stagnation. Therefore, the Sigmoid function operator is introduced, and a sparse full-focusing algorithm based on the improved adaptive genetic algorithm is proposed. The performance of the array under the optimization algorithm is analyzed, and the full-focus scanning environment is established to perform imaging tests on the defects. Experiments show that compared with the full array and the traditional adaptive genetic algorithm, the improved optimization algorithm in this paper has better sidelobe suppression, the peak sidelobe level reaches -15.74dB, the main lobe width is -6dB standard, and the main lobe width of sparse array is consistent with that of the full array. When the sparse rate is 25%, the imaging efficiency increases by 34%. The quality of imaging performance is close to that of full array without loss of necessary defect information.