A Review of Array Techniques for Noise Source Location

Christensen, Jacob Højgaard; Hald, Jørgen; Mørkholt, Jakob; Schuhmacher, Andreas; Blaabjerg, Claus

doi:10.4271/2003-01-1691

Cited by 11 publications

(13 citation statements)

References 2 publications

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“…Once defined the calculation grid, the simplest algorithm that can be used is the delay-and-sum one. With this algorithm, it is possible to define the minimum working frequency for a 30° opening angle as [12].…”

Section: Methodsmentioning

confidence: 99%

“…being f T [Hz] the sidelobe threshold frequency [12]. The frequency range obtained can be used for the case of the beamforming delay-and-sum algorithm and could be increased if other algorithms (such as minimum variance or Capon [15], clean-SC [16], DAMAS [17], beamforming through using eigenvalues and eigenvectors [18], MUSIC [19], or orthogonal beamforming [20]) are used.…”

Section: Methodsmentioning

confidence: 99%

“…• The distance between the array and the acoustic field-SONAH technique requires near-field measurements close to the surface [6], whereas beamforming technique does the measurements in the far field [12].…”

Section: Introductionmentioning

confidence: 99%

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In Situ Detection of Leakages in Partition Elements through SONAH and Beamforming Techniques

Ballesteros¹,

Fernández²

2019

Acoustics of Materials

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Airborne sound insulation in buildings, whether in fixed partition elements, like partitions or party walls, or mobile elements, like doors or screens, is always related to the performance of the weakest element involved. In situ assessment of airborne sound insulation in building elements can be carried out by pressure techniques or sound intensity techniques. Sound pressure techniques are very quick but fail to discriminate the sound insulation contribution of each building element involved. Sound intensity techniques, on the other hand, allow to determine the sound transmission of each element and also to discriminate indirect transmissions up to a certain degree. In order to find areas with high sound transmission, such as leakages or weakened regions, a large number of measurements on the building element surface have to be performed. Moreover, the sound intensity technique is very timeconsuming, because it is necessary to carry out the measurement in each grid point defined. This chapter describes the use of beamforming and SONAH techniques to detect areas with lower airborne sound insulation in a building element. These techniques unify the advantages of both, pressure and sound intensity techniques, allowing the quick visualization of leakages or weakened areas of different building elements.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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In Situ Detection of Leakages in Partition Elements through SONAH and Beamforming Techniques

Ballesteros¹,

Fernández²

2019

Acoustics of Materials

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“…The acoustic field inverse problem can be solved quickly and efficiently to achieve sound field reconstruction and noise source identification by microphone array technology [1][2][3][4] . At present, a variety of algorithms have been used to solve the acoustic inverse problem, such as: Beamforming [5][6][7] , NAH [8,9] , statistically optimized near-field acoustical holography (SONAH) [10][11][12] , inverse boundary element method (IBEM) [13,14] , Helmholtz equation-least squares (HELS) [15,16] , Bayesian approach [17,18] and ESM [19,20] . These algorithms have different assumptions and application scopes in terms of source surface structure, sources spatial distribution, array geometry, propagation type and source frequency range [21] .…”

Section: Introductionmentioning

confidence: 99%

“…Among these algorithms, Beamforming, whose spatial resolution is inversely proportional to the ratio of the array size and the wavelength, assumes that the monopoles have sparse distribution in space. This method is suitable for middle and long distances measurement using irregular array or random array, and has good performance for middle and high frequency noise source identification [5] . In the near field, NAH has good performance for low frequency noise source identification under the assumption that the propagation of acoustic wave is in the free field.…”

Section: Introductionmentioning

confidence: 99%

Application of Bayesian Regularization Criterion in near Field Acoustic Holography Based on Equivalent Source Method

Chu

Ping

Cai

et al. 2015

Noise & Vibration Worldwide

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In order to choose an optimal regularization parameter for near field acoustic holography (NAH) based on equivalent source method (ESM), Bayesian regularization criterion method was introduced to solve the inverse problem. Comparison simulations were conducted with generalized cross validation method (GCV), L-curve method and Hald regularization formula method at various sound source frequencies, hologram distances, and Signal-to-Noise Ratios (SNR). The results show that GCV, L-curve, and Hald regularization formula method cannot achieve the optimal regularization parameter at large hologram distances, high noise levels, high frequencies and input SNR errors. However, Bayesian regularization criterion method is not affected by these restrictions and has excellent reconstruction performance in wide frequency band. Further experiment validates the correctness and effectiveness of the application of Bayesian regularization criterion method in ESM-based NAH, thus providing a new guidance for the solving of inverse problem in ESM-based NAH.

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Mathematical models for the improvement of detection techniques of industrial noise sources from acoustic images

Asdrubali

Baldinelli

Bianchi

et al. 2021

Math Methods in App Sciences

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In this paper, a procedure for the detection of the sources of industrial noise and the evaluation of their distances is introduced. The above method is based on the analysis of acoustic and optical data recorded by an acoustic camera. In order to improve the resolution of the data, interpolation and quasi interpolation algorithms for digital data processing have been used, such as the bilinear, bicubic, and sampling Kantorovich (SK). The experimental tests show that the SK algorithm allows to perform the above task more accurately than the other considered methods.

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A Review of Array Techniques for Noise Source Location

Cited by 11 publications

References 2 publications

In Situ Detection of Leakages in Partition Elements through SONAH and Beamforming Techniques

In Situ Detection of Leakages in Partition Elements through SONAH and Beamforming Techniques

Application of Bayesian Regularization Criterion in near Field Acoustic Holography Based on Equivalent Source Method

Mathematical models for the improvement of detection techniques of industrial noise sources from acoustic images

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