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《Journal of Applied Acoustics》 2020-03
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Ultrasonic sparse-TFM imaging using particle swarm optimization algorithm

SHEN Xiaowei;College of Automotive and Mechanical Engineering, Changsha University of Science and Technology;  
To reduce the amount of imaging data of the total focusing method in phased array ultrasonic detection and computing time for array sparse optimization, an array optimization algorithm for full focusing sparse array imaging is studied and its imaging results are verified by experiments. Aiming at the problem of a huge amount of full matrix data and long imaging time of total focusing method(TFM) imaging in the ultrasonic phased array inspection, this paper constructs a sparse array to reduce the data and improve the imaging efficiency while assuring the image quality. By using the main lobe width, the side lobe peak and the main lobe peak as the constraints to construct the fitness function, the particle swarm optimization(PSO)algorithm is used to obtain the sparse array elements position distribution and the matrix weight correction,and they are used for sparse-TFM imaging. Compare imaging with full elements of an array, the sparse array obtained by particle swarm optimization algorithm reduces the number of array elements by 56.25% and65.62%, respectively, and the data usage is reduced by 80.86% and 88.18%, respectively. In terms of array optimization, the computation time is reduced by 84.86% compared to the genetic algorithm.
【CateGory Index】: TB559
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