Three‐dimensional application of improved equivalent source method for noise source identification

2016 ◽  
Vol 52 (17) ◽  
pp. 1501-1503
Author(s):  
Shu Li ◽  
Zhongming Xu ◽  
Yansong He ◽  
Zhifei Zhang ◽  
Qinghua Wang
2016 ◽  
Vol 2016 ◽  
pp. 1-13
Author(s):  
Zhongming Xu ◽  
Qinghua Wang ◽  
Yansong He ◽  
Zhifei Zhang ◽  
Shu Li ◽  
...  

Near-field acoustical holography (NAH) based on the equivalent source method (ESM) is an efficient method applied for noise source identification. Asl2-norm-based regularization cannot produce a satisfactory solution of the ill-conditioned problem in high frequency, the conventional ESM is restricted to relatively low frequency, and the resolution of conventional ESM in middle to high frequency remains a limitation open to investigation. This article presents an algorithm known as improved functional equivalent source method (IFESM), designed to enhance the resolution of conventional ESM. This method is developed in the framework of wideband acoustical holography (WBH) combining with functional beamforming (FB). Through numerical simulations, it is proved that the proposed method can localize noise with higher resolution compared with WBH and conventional ESM, and the ghosts on noise source map can be suppressed effectively. The validity and the feasibility of the proposed method are manifested by experiments including single-source and coherent-source localization.


2020 ◽  
Vol 68 (1) ◽  
pp. 59-71
Author(s):  
Chen Liangsong ◽  
He Yansong ◽  
Niu Xiyuan ◽  
Bao Jian ◽  
Li Wei

Near-field acoustical holography (NAH) based on equivalent source method (ESM) is an efficient technique for sound source identification. Conventional ESM with Tikhonov regularization (TRESM), ESM based on CVX MATLAB toolbox (CVX) and wideband acoustic holography (WBH) are commonly used methods for calculating equivalent source strengths. However, all of them have their respective limitations. To address some of these, an alternating iterative algorithm for sound source identification based on equivalent source method (AIESM) is proposed in this article, which is a combination of alternating direction method and a non-monotone line search technique. The method makes use of sparse regularization under the principle of compressive sensing (CS) to calculate equivalent source strengths. Moreover, inspired by the idea of functional beamforming (FB), AIESM with order n can yield an improved dynamic range when detecting the source location. Numerical simulations are carried out at different frequencies, and the results suggest that the computational efficiency of the proposed method is close to that of TRESM. In addition, AIESM has a better reconstruction accuracy than TRESM and WBH in a relatively wide frequency range. Compared with ESM based on CVX, AIESM is slightly better in reconstruction accuracy and has a higher computational efficiency. Meanwhile, AIESM with order n can provide more accurate source position and better resolution. The validity and practicality of the proposed method are further supported by experimental results.


2018 ◽  
Vol 140 (6) ◽  
Author(s):  
Chuan-Xing Bi ◽  
Yong-Chang Li ◽  
Rong Zhou ◽  
Yong-Bin Zhang

The equivalent source method (ESM) and monopole time reversal method (MTRM) are two popular techniques for noise source localization. These two methods have some similar characteristics, such as using the pressure field measured by a microphone array as the input and using similar propagation matrices obtained from the Green's function. However, the spatial resolutions of results obtained by these two methods are different. The aim of this paper is to reveal the reason resulting in this difference from a theoretical analysis and compare the performance of these two methods using results from numerical simulations and experiments. Using the singular value decomposition (SVD) technique, the difference between the two methods is found to be only the diagonal matrices of singular values, and the two methods are equivalent after simply replacing the diagonal matrix in the MTRM with its inverse. Comparison of the results demonstrates that the ESM can calculate the real source strength and obtain a high spatial resolution due to the significant amplification of evanescent waves in the inverse process. However, it does not work when the signal-to-noise ratio (SNR) is low or the measurement distance is large. The performance of ESM under these situations can be significantly improved by introducing a regularization procedure. While the MTRM fails to calculate the real source strength and locate the source at low frequencies due to the loss of information of evanescent waves, it works well at high frequencies even with a low SNR and a large measurement distance.


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