Search query: Microphone array structure

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abstract: Fluctuating pressure (p' of a large scale vortical structure generated in a semiconductor single wafer spin cleaner was detected by using microphone array. Twelve microphones were installed on the exhaust cover under the rotating disk of the cleaner with their interval of 7.5deg or 15deg. Power spectrum densities (PSD) of p' were compared with those of fluctuating velocity measured by PIV for various rotation angular velocities to identify fluctuations due to convection of the large scale vortical structure. Good agreement of PSDs indicates that the large scale structure could be detected by using microphone. Cross correlation of p' measured at different positions revealed that the large scale structure convected to the downstream in the rotational direction of the disk. The convection speed was about 12 of the angular velocity of the rotating disk. Number of the vortex in the large scale structure was also evaluated from the time series p' data. Time space contour map was made for p' based on the data measured at the different angular position, and showed periodical swept strip patterns. Presences of the strip patterns indicate the pressure disturbances were stably convected to the downstream. From this time space map, two dimensional Fourier transform efficiently extracted the number of vortices in the large scale structure.
author_names: Toshinori Kouchi

Yu Miyoshi

Yusuke Nakano

Yasunori Nagata

Shinichiro Yanase
title: Large scale vortical structure detection using microphone array in a semiconductor single wafer spin cleaner
year: 2017

abstract: PURPOSE: A microphone array structure, a method and an apparatus for forming a beam having a constant reflectivity and a method and an apparatus for estimating the direction of a sound source employing the same are provided to improve the recognition rate of the sound. CONSTITUTION: An apparatus for forming a beam having a constant reflectivity by employing the microphone array structure includes a microphone array(211) a beam forming unit(231) a filtering unit(251) and an adding unit(271) The microphone array(211) is provided with a first sub array(213) a second sub array(215) and a third sub array(215) The first sub array(213) is placed at a predetermined position of the flat plate. And, the second sub array(215) and the third sub array(217) are located at the position corresponding to the first to ith predetermined distance vertical to the extending line of the first sub array(213) and the central axis of the flat plate in response to the first to ith target frequencies of each sub array.
title: Microphone array structure, method and apparatus for beamforming with constant directivity and method and apparatus for estimating direction of arrival, employing the same
year: 2003

abstract: Various microphone array geometries (e.g. linear, circular, square, cubic, spherical, etc. have been used to improve the positioning accuracy of sound source localization. However, whether these array structures are optimal for various specific localization scenarios is still a subject of debate. This paper addresses a microphone array optimization method for sound source localization based on TDOA (time difference of arrival) The geometric structure of the microphone array is established in parametric form. A triangulation method with TDOA was used to build the spatial sound source location model, which consists of a group of nonlinear multivariate equations. Through reasonable transformation, the nonlinear multivariate equations can be converted to a group of linear equations that can be approximately solved by the weighted least square method. Then, an optimization model based on particle swarm optimization (PSO) algorithm was constructed to optimize the geometric parameters of the microphone array under different localization scenarios combined with the spatial sound source localization model. In the optimization model, a reasonable fitness evaluation function is established which can comprehensively consider the positioning accuracy and robustness of the microphone array. In order to verify the array optimization method, two specific localization scenarios and two array optimization strategies for each localization scenario were constructed. The optimal array structure parameters were obtained through numerical iteration simulation. The localization performance of the optimal array structures obtained by the method proposed in this paper was compared with the optimal structures proposed in the literature as well as with random array structures. The simulation results show that the optimized array structure gave better positioning accuracy and robustness under both specific localization scenarios. The optimization model proposed could solve the problem of array geometric structure design based on TDOA and could achieve the customization of microphone array structures under different specific localization scenarios.
author_names: Haitao Liu

Thia Kirubarajan

Qian Xiao
title: Arbitrary Microphone Array Optimization Method Based on TDOA for Specific Localization Scenarios
venue: Sensors
year: 2019

abstract: When monitoring critical structures, fatigue fracture, deformations, holes and much more are cases of failure which must be detected at an early stage. Changes of the modal parameters (eigenfrequencies, attenuation ratios, and mode shapes) of the structure give information about the extent and the location of the deterioration. Conventional measurement methods (i.e. acceleration sensors, laser vibrometers, etc. for vibration analysis have the disadvantage that they can either "detune" the vibration modes due to their own weight and/or require a long measurement time due to punctual measurements. In contrast, the use of a suitable microphone array allows the high resolution acquisition of the entire surface vibration covered by the array. Thus, the modal parameters of interest are determined by measuring the pressure fluctuations in the near field of the structure. A commercial acoustic camera with 120 microphones (Fibonacci120, gfai tech GmbH) is used for this purpose. On the basis of artificially generated failure cases (load fracture, inhomogeneities, etc. on application oriented, large area structures, a method for the detection of failure cases using a microphone array is demonstrated.
author_names: Olaf Bolke

J H Heimann

Joaquin Garcia
title: Modal Analysis for damage detection in structures by non contact measurements with a commercial microphone array
year: 2019

author_names: Shun-ichi Ohshima
title: 353 An analytical study of the insertion effect of the 2 D microphone array structure in the sound field
year: 2005

abstract: In order to get a better application of noise source identification by using microphone array,this paper studied the noise source identification performances of different microphone sub arrays.Based on the beamforming principle,we designed a mathematic computational model of planar arbitrary sub array and proposed the general sound source localization calculating equations of this model.Then,we deduced and analyzed the acoustic positioning algorithm formula respectively for two microphone array,three microphone array and four microphone array.The paper also showed the matrix solution of the three microphone array.The sound source recognition of different types of microphone sub structure was comparatively analyzed.Finally,we did a comparable acoustic source localization testing by establishing small microphone arrays which have the same size and were composed of different sub array forms.The final test results validate the reliability of the proposed model and algorithm.And the study obtains the conclusion that the microphone array structure composed of regular triangle sub array has better performance of noise source identification.
author_names: Wu Bobo
title: Study on the Noise Source Identification Properties of Microphone Sub array Structure
year: 2013

abstract: The microphone array arrangement structure compartment (100) (150) includes a convex curved configuration (LM) of the plurality of microphones (11,12,13,14) These microphones (11,12,13,14) including a first microphone (11) a first microphone (11) in the direction of the shaft (DRl) towards the mouth of the driver (170) (171) The microphone array arrangement structure (100) further includes a cover (30,31,33) the cover (30,31,33) for receiving the microphone (11, 12) and having a plurality of apertures (21, 22,23,24) Surface of the shell (30,31,33) forming a hole (21,22,23,24) shaped convex curve (LC) a microphone (11, 12) respectively corresponding to the aperture fixed to the inside of the cover (31, 33)
title: The microphone array arrangement structure of the vehicle interior
year: 2012

author_names: Markus Christoph
title: Spherical microphone array including a sound diffracting structure with cavity
year: 2014

author_names: Michael Williams
title: The Psychoacoustic Testing of the 3 D Multiformat Microphone Array Design and the Basic Isosceles Triangle Structure of the Array and the Loudspeaker Reproduction Configuration
year: 2013

abstract: We proposed a spatial coherence based PSD estimation and source separation technique in [1] using a 32 channel spherical microphone array. While the proposed spherical microphone based method exhibited a satisfactory performance in separating multiple sound sources in a reverberant environment, the use of a large number of microphones remains an issue for some practical considerations. In this paper, we investigate an alternative array structure to achieve spatial coherence based source separation using a planar microphone array. This method is particularly useful in separating a limited number of sound sources in a mixed acoustic scene. The simplified array structure we used here can easily be integrated with many commercial acoustical instruments such as smart home devices to achieve better speech enhancements.
author_names: Abdullah Fahim

Prasanga N Samarasinghe

Thushara Dheemantha Abhayapala

Hanchi Chen
title: A Planar Microphone Array for Spatial Coherence Based Source Separation
venue: 2018 IEEE 20th International Workshop on Multimedia Signal Processing (MMSP)
year: 2018