Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (2/2 displayed)

  • 2016Iterative beamforming for identification of multiple broadband sound sources32citations
  • 2015Damping loss factor estimation of two-dimensional orthotropic structures from a displacement field measurement36citations

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Chart of shared publication
Antoni, Jérôme
1 / 9 shared
Wang, Xun
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Quost, Benjamin
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Cherif, Raef
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Atalla, Noureddine
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2016
2015

Co-Authors (by relevance)

  • Antoni, Jérôme
  • Wang, Xun
  • Quost, Benjamin
  • Cherif, Raef
  • Atalla, Noureddine
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article

Iterative beamforming for identification of multiple broadband sound sources

  • Chazot, Jean-Daniel
  • Antoni, Jérôme
  • Wang, Xun
  • Quost, Benjamin
Abstract

The reconstruction of broadband sound sources is an important issue in industrial acoustics. In this paper, a model comprising multiple incoherent Gaussian random sources is considered. The aim is to estimate locations and powers of the sound sources using the pressures measured by an array of microphones. Each measured pressure is interpreted as a mixture of latent signals emitted by different sound sources. Then, an Iterative Beamforming (IB) method is developed to estimate the source parameters. This approach is based on the Expectation-Maximization (EM) algorithm, a well-known iterative procedure for solving maximum likelihood parameter estimation. More specifically, IB iteratively estimates the source contributions and performs beamforming on these estimates. In this work, experiments on real data illustrate the advantage of IB with respect to classical beamforming and Near-field Acoustical Holography (NAH). In particular, the proposed method is shown to work over a wider range of frequencies, to better estimate the source locations, and is able to quantify the powers of the sources. Furthermore, experiments illustrate that IB can not only localize the sources on a given surface, but also accurately estimate their 3D locations.

Topics
  • impedance spectroscopy
  • surface
  • experiment
  • random