Acoustic imaging of sound sources - a junior year student research project

Bischof, Günter

doi:10.1109/fie.2008.4720258

Cited by 4 publications

(5 citation statements)

References 8 publications

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“…Nevertheless, we have the values only at the time points which are the integer multiples of the sample period. The solution can be either reconstruction and resampling of the signal or rather using the interpolation methods [9].…”

Section: Implementation Of Fractional Delaymentioning

confidence: 99%

Sound source localization with DAS beamforming method using small number of microphones

Kurc

Mach

Orlovsky

et al. 2013

2013 36th International Conference on Telecommunications and Signal Processing (TSP)

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Localization of the sound source using microphone arrays is largely done by Acoustical Holography or Beamforming method. In this paper we present an implementation of DelayAnd-Sum algorithm for beamforming computation using various microphone arrays. A MATLAB code was implemented for postprocessing of obtained acoustic signals. There is also included a description of the fractional delay filter implementation to delay the signal samples by racional values of sample period. The goal of this paper was comparing the accuracy of the source localization with the microphone arrays using small number of microphones. The results of the localization of several noise sources by the different types of arrays is presented.

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Section: Implementation Of Fractional Delaymentioning

confidence: 99%

Sound source localization with DAS beamforming method using small number of microphones

Kurc

Mach

Orlovsky

et al. 2013

2013 36th International Conference on Telecommunications and Signal Processing (TSP)

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“…have learned to use higher order thinking skills; can apply theoretical knowledge in practice; are able to work in teams with strangers; are able to be responsible for and to advance their work results; are motivated to develop methods and connect new learning to past performances (i.e. project work 1,2,3,5 ); can think holistically; can cope positively with problems and act to find a solution.…”

Section: Figure 1: Timelinementioning

confidence: 99%

“…They are asked to evaluate student's competence in the subject area, motivation, goal orientation, team capabilities, ability to think holistically, creativity, performance according to workload, and positive thinking. Figure 5 shows the external evaluations of 40 randomly selected assessments of two consecutive internship years (IS 2007 andIS 2008). The best mark is 1 (excellent) and the poorest is 5.…”

Section: Evaluation Of the Industrial Internshipmentioning

confidence: 99%

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Industrial Internships: The Final Part Of A Three Phase Multisubject Experiment In Project Based Learning In Vehicle Technology Studies

Bratschitsch¹,

Millward-Sadler²

2009 Annual Conference &Amp; Exposition Proceedings

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Bratschitsch is head of the Department of Vehicle Technologies (Automotive and Railway Engineering) and teaches Electrics, Electronics and Methods of Signal Processing at the University of Applied Sciences Joanneum in Graz (Austria). She is also a visiting lecturer at the Faculty of Transport of the Technical University of Sofia (Bulgaria). She graduated with a degree in Medical Electronics as well in Technical Journalism from the Technical University of Sofia and received her PhD from the Technical University of Graz (Austria). She gained industrial experience in automation of control systems, engineering of electronic control systems and software development. Her R&D activities comprise design of signal processing and data analysis methods, modeling, simulation and control of automotive systems as well as Engineering Education.

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“…This leads to the condition that the spacing between any pair of microphones in the array should not exceed half of the smallest wavelength present in the signal. Spatial aliasing can also be avoided when the array geometry is totally non-redundant, that is, no difference vector between any two sensor positions is repeated[20]. For non-redundant…”

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confidence: 99%

Acoustic Imaging Using a 64-Node Microphone Array and Beamformer System

Feng¹

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Acoustic imaging is difficult to achieve in environments with a large amount of noise and reverberation. Microphone arrays, as a branch of array signal processing, offer an effective approach to obtaining a clean recording of desired acoustic signals in these environments. In this thesis, we have designed, implemented, and evaluated a 64-node microphone array system for acoustic imaging. We have applied a delay-and-sum beamforming algorithm for sound source amplification in a noisy environment, and have explored the uses of the array and beamformer by generating the sound intensity map to reconstruct the acoustic scene of interest. Our experimental results show a mean error of 1.1 degrees for sound source localization, and a mean error of 13.1 degrees for source separation. In addition, we also used the system to image seven different materials with audible sound, and obtained their reconstructed acoustic maps as well as frequency response curves, from which we are able to detect the differences between textures based on their acoustic response powers.

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Acoustic imaging of sound sources - a junior year student research project

Cited by 4 publications

References 8 publications

Sound source localization with DAS beamforming method using small number of microphones

Sound source localization with DAS beamforming method using small number of microphones

Industrial Internships: The Final Part Of A Three Phase Multisubject Experiment In Project Based Learning In Vehicle Technology Studies

Acoustic Imaging Using a 64-Node Microphone Array and Beamformer System

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