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• The models, imaging algorithms, and applications are systematically compared, analyzed, and concluded in this paper to explore the differences between the PAD-DBF and FDD-DBF techniques and provide guidance on the application of the technology. • A large number of simulations are investigated to explore the imaging characteristics of two rotor aerodynamic dipole source imaging technologies under different testing conditions, including different analysis frequencies, axis directions, SNRs, and measured distances. • The two imaging techniques are applied to the semi-anechoic chamber test for rotating dipole sources and the actual BO105 rotor wind tunnel test, respectively, which is further used to compare and validate the imaging effectiveness and applicability of the two techniques. The acoustic imaging technology for rotating dipole sources has been one of the topics concerned. In recent years, two state-of-the-art imaging technologies for rotating dipole sources were proposed, including beamforming technologies based on the predefined axis direction (PAD-DBF) and frequency-domain deconvolution (FDD-DBF). However, a systematic comparison of these two imaging technologies does not currently exist. In this paper, the models and imaging algorithms are firstly systematically compared and analyzed to explore the differences between the two technologies and provide guidance on the application of the technology. Secondly, extensive simulations are investigated to analyze the performance of the two imaging technologies under different working conditions. Finally, the two imaging technologies are applied to the semi-anechoic chamber test for rotating dipole sources and the actual BO105 rotor wind tunnel test, respectively, which is further used to compare and validate the imaging effectiveness and applicability of the two technologies. The analysis shows that both technologies can effectively achieve rotating dipole source localization. The PAD-DBF technology can achieve a more accurate rotating dipole source location, higher imaging resolution at a lower time cost, and it can get more robust imaging results in the low signal-to-noise ratio (SNR) of the wind tunnel environment. In contrast, the FDD-DBF technology can get a more accurate sound source magnitude while effectively imaging the rotating dipole source. [ABSTRACT FROM AUTHOR]

It is valuable to improve the resolution and speed of acoustic beamforming in real-time measurement, especially fault location, noise mapping, and so on. However, multiplication of the power transfer matrix takes much time in the iteration of the deconvolution algorithm. This article proposes a novel method based on the convolution approximation and GPU platform to obtain acoustic imaging with a high resolution quickly. First, the power propagation matrix is approximated by a symmetric Toeplitz block Toeplitz (STBT) matrix, which can transform the product of matrix and vector into the convolution of two smaller patterns. Three different convolution kernels are derived for the convolution operation, including 2-D variant convolution kernel, 2-D invariant convolution kernel, and 1-D separable invariant convolution kernel. Then, the regularization deconvolution algorithm with the convolution kernel is derived. Besides, the relation between approximation error, time cost, and setting parameters is discussed. The results show that the separable invariant convolution kernel can obtain the fastest imaging and relatively accurate localization, while the time consumption of the variant kernel is the highest. Simulations and experiments are operated on the CPU and GPU to make a comparison, which validates that our proposed deconvolution-GPU implementation can significantly improve the computation speed for the matrix on a large scale. [ABSTRACT FROM AUTHOR]