Reverse Noise-identify Mechanism And Technology Based On Phased Micphone Array

Beam forming is an important direction of array signal processing research in recent years, developed into an important method of noise sources, based on the microphone array direction principle。It can measure the spatial distribution of sound source to carry out sound source identification and the study of spatial sound field characteristics and spatial sound field reconstruction, now widely used in aerospace technology, automotive, trains, automobiles, sonar, seismic and other fields. In this paper, an reverse sound source identification method is presented on the basis of beam-forming technology so that a smaller array can be realized. The reverse sound source identification method is researched on the theory and engineering application. Experimental verification shows that this method can effectively improve the accuracy of test system, especially the low-frequency part. Compared with other high resolution's array test technology, this test technology does not need the apriori knowledge, and simultaneously the array system's array element number may be smaller than the acoustic source number.The realization of this test technique is based on first kind of integral operator equations to achieve. The solution of first kind of operator equations usually does not exist, or is not unique or non-continuous data-dependent, yet a unified solution method is not mature. Ill-posed state can be suppressed on mathematics, generally by means of regularization methods and optimal control theory. Through the Tikhonov regularization method, neural network and L-curve methods are applicated in order that first-kind integral equations have been studied based on beamforming operator kernel. The priori knowledge or network parameters to optimize are need in order to solve first kind of operator equations through the above-mentioned two kinds of algorithms, but it is difficult in engineering application.In Tikhonov regularization method, the determination of the regularization parameter and regular matrix are need. In the paper, matrix parameters iteration is used for solving first kind of operator equations and a priori knowledge is not used, so this is the further development of the Tikhonov regularization method, and the algorithm is applied successfully into the reverse acoustic source recognition.Finally, the paper carried out experimental verification of engineering applications and automotive noise source identification. Compared, the testing results is agreed with the actual noise sources situation, and is better than existing commercial test systems.