Methods and apparatus for source location estimation from microphone-array time-delay estimates

2002 ◽  
Vol 111 (3) ◽  
pp. 1149
Author(s):  
Michael S. Brandstein
2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Antonio Canclini ◽  
Fabio Antonacci ◽  
Augusto Sarti ◽  
Stefano Tubaro

This manuscript addresses the problem of 3D source localization from direction of arrivals (DOAs) in wireless acoustic sensor networks. In this context, multiple sensors measure the DOA of the source, and a central node combines the measurements to yield the source location estimate. Traditional approaches require 3D DOA measurements; that is, each sensor estimates the azimuth and elevation of the source by means of a microphone array, typically in a planar or spherical configuration. The proposed methodology aims at reducing the hardware and computational costs by combining measurements related to 2D DOAs estimated from linear arrays arbitrarily displaced in the 3D space. Each sensor measures the DOA in the plane containing the array and the source. Measurements are then translated into an equivalent planar geometry, in which a set of coplanar equivalent arrays observe the source preserving the original DOAs. This formulation is exploited to define a cost function, whose minimization leads to the source location estimation. An extensive simulation campaign validates the proposed approach and compares its accuracy with state-of-the-art methodologies.


Author(s):  
Shun Takase ◽  
Kentaro Nishimori ◽  
Ryotaro Taniguchi ◽  
Takahiro Matsuda ◽  
Tsutomu Mitsui

2021 ◽  
Vol 2113 (1) ◽  
pp. 012042
Author(s):  
Yongshao Xu ◽  
Bingzheng Liu ◽  
Haotian Shang ◽  
Mingduo Wang

Abstract Rotating machinery often produces continuous impact during operation due to the change of load and speed, which shows the characteristics of unsteady state and time-varying. Its working state can not be comprehensively judged by a single vibration state parameter. Therefore, this paper proposes to use acoustic sensors to collect the fault noise signal of rotating machinery, and use the whole column of sensors to detect the fault noise signal. Based on the microphone array, this paper studies the adaptive beamforming algorithm (MVDR) to locate the fault source of rotating machinery in space. The effect of fault source location is verified by simulation and equipment measurement experiments. The acoustic sensor does not in contact with the equipment, which will not damage the generator set, but also provide more effective information for fault source location and fault diagnosis and analysis.


1992 ◽  
Vol 25 (15) ◽  
pp. 381-386
Author(s):  
J.F. Böhme ◽  
D. Kraus

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