Numerical simulation and experimental study of flow field measurement based on acoustic tomography method
Flow velocity is an important basis for realizing online monitoring and precise control of industrial production processes.In order to accurately measure the distribution of the flow field,a reconstruction method based on the combination of radial basis function and equilibrium optimizer(RBF-EO)algorithm is proposed.The radial basis function is used to approximate and establish the model for reconstructing the acoustic velocity field,and the equilibrium optimizer algorithm is used to solve the ill-posed equations in the reconstruction problem.Numerical simulation and noise resistance test of the algorithm were conducted on a typical four-corner tangential velocity field model,and the algorithm was compared with traditional reconstruction methods such as Tikhonov algorithm,SVD decomposition method,and gray wolf optimization algorithm.The simulation results showed that the algorithm can well reconstruct the flow field distribution with higher reconstruction performance and better noise resistance.Finally,the acoustic measurement experiment of the flow field in the measurement area of 1.05 m×1.05 m was carried out in the laboratory.The results were compared with the strip display and anemometer,and the average relative error is 9.77％between RBF-EO algorithm and anemometer measurement results at 8 measurement points,which verifies the reliability of the acoustic flow field measurement method in this paper.
acoustic methodflow field measurementacoustic tomographyequilibrium optimizerradial basis function
万方数据
维普
