An improved two-dimensional multiple signal classification approach for impact localization on a composite structure

2015 ◽  
Vol 14 (5) ◽  
pp. 385-401 ◽  
Author(s):  
Yongteng Zhong ◽  
Shenfang Yuan ◽  
Lei Qiu
Keyword(s):  
Composite Structure ◽  
Signal Classification ◽  
Two Dimensional ◽  
Multiple Signal Classification ◽  
Classification Approach ◽  
Multiple Signal ◽  
Impact Localization

Study of High Resolution DOA Estimation Based on Vector-Hydrophone

2014 ◽  
Vol 926-930 ◽  
pp. 1795-1799
Author(s):  
Hao Zhou ◽  
Zhi Jie Huo
Keyword(s):  
Doa Estimation ◽  
Spatial Spectrum ◽  
Classification Algorithm ◽  
Signal Classification ◽  
Two Dimensional ◽  
Multiple Signal Classification ◽  
Variance Matrix ◽  
Multiple Signal ◽  
Vector Hydrophone ◽  
Eigen Decomposition

Vector-hydrophone can simultaneously measure acoustic pressure and orthogonal components of the particle velocity. The 180o ambiguity in DOA estimation can be eliminated using information obtained by vector hydrophone array. Multiple signal classification algorithm is a method that takes the eigen-decomposition of data co-variance matrix to obtain the estimation of signal spatial spectrum. The two-dimensional DOA of acoustic sources is estimated based on multiple signal classification algorithm using the vector-hydrophone uniform linear array. Simulation results show that better DOA resolution performance can be obtained from vector hydrophones. Furthermore, the paper takes the de-correlation of correlated sources using spatial smoothness technology to obtain perfect performance of two-dimensional DOA estimation.

scholarly journals Multiple Signal Classification-Based Impact Localization in Composite Structures Using Optimized Ensemble Empirical Mode Decomposition

2018 ◽  
Vol 8 (9) ◽  
pp. 1447 ◽  
Author(s):  
Yongteng Zhong ◽  
Jiawei Xiang ◽  
Xiaoyu Chen ◽  
Yongying Jiang ◽  
Jihong Pang
Keyword(s):  
Composite Structures ◽  
Sensor Array ◽  
Ensemble Empirical Mode Decomposition ◽  
Signal Classification ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Multiple Signal ◽  
Mode Decomposition ◽  
The Impact ◽  
Impact Localization

Multiple signal classification (MUSIC) algorithm-based structural health monitoring technology is a promising method because of its directional scanning ability and easy arrangement of the sensor array. However, in previous MUSIC-based impact location methods, the narrowband signals at a particular central frequency had to be extracted from the wideband Lamb waves induced by each impact using a wavelet transform. Additionally, the specific center frequency had to be obtained after carefully analyzing the impact signal, which is time consuming. Aiming at solving this problem, this paper presents an improved approach that combines the optimized ensemble empirical mode decomposition (EEMD) and two-dimensional multiple signal classification (2D-MUSIC) algorithm for real-time impact localization on composite structures. Firstly, the impact signal at an unknown position is obtained using a unified linear sensor array. Secondly, the fast Hilbert Huang transform (HHT) with an optimized EEMD algorithm is introduced to extract intrinsic mode functions (IMFs) from impact signals. Then, all IMFs in the whole frequency domain are directly used as the input vector of the 2D-MUSIC model separately to locate the impact source. Experimental data collected from a cross-ply glass fiber reinforced composite plate are used to validate the proposed approach. The results show that the use of optimized EEMD and 2D-MUSIC is suitable for real-time impact localization of composite structures.

scholarly journals The iterative search approach DOA estimation of monostatic L-shaped array MIMO radar

2018 ◽  
Vol 12 (2) ◽  
pp. 101-109
Author(s):  
Guan Jishi ◽  
Shi Yaowu ◽  
Deng Lifei ◽  
Zhu Lanxiang ◽  
Shi Hongwei
Keyword(s):  
Doa Estimation ◽  
Mimo Radar ◽  
Classification Algorithm ◽  
Signal Classification ◽  
Two Dimensional ◽  
Iterative Search ◽  
Multiple Signal Classification ◽  
Multiple Signal ◽  
Searching Method ◽  
Search Approach

In the DOA estimation of monostatic L-shaped array MIMO radar, Multiple Signal Classification algorithm is efficient. But the peak searching process of Multiple Signal Classification algorithm needs large amount of spectrum calculation. Focusing on the spectrum peak searching process of Multiple Signal Classification, an iterative search approach to reduce the calculation amount is proposed. The first- and second-order derivatives of Multiple Signal Classification spectrum functions are achieved and the calculation amount is analyzed. Two-dimensional Newton iteration methods are applied with multisearching threads and derivation information. The searching approach can greatly reduce the computational complexity of Multiple Signal Classification spectrum peak searching. The total calculation amount of the first and second derivatives is about 15 times of the spectrum function. However, in the two-dimensional searching, especially in the high accuracy processes, the amount of searched points can be reduced by ten hundreds times, and the computation is much lower than the common spectrum peak searching method. The simulation results show that when the search thread number reaches 100, the searching process can effectively achieve the entire spectrum peak and get the correct DOA estimation.

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