Efficient Azimuthal Mode Analysis using Compressed Sensing

Behn, Maximilian; Kisler, Roman; Tapken, Ulf

doi:10.2514/6.2016-3038

Cited by 27 publications

(11 citation statements)

References 10 publications

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“…This method has been adopted in the identification of spinning modes for turbofan noise using microphone-array measurements. The required number of sensors can be much less than the number required by the sampling theorem as long as the incident fan noise is sparse in spinning modes [167][168][169].…”

Section: Compressive-sensing Beamformingmentioning

confidence: 99%

“…• Compressive-sensing beamforming: [163][164][165] assumes spatially sparse distributions of sound sources and requires a lower number of microphones. This inverse technique has been used to identify spinning modes of turbofan engines [167,168]. • Generalized inverse beamforming: [13] considers partially coherent sound sources using inversion techniques.…”

Section: Applicationsmentioning

confidence: 99%

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A review of acoustic imaging methods using phased microphone arrays

et al. 2019

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Phased microphone arrays have become a well-established tool for performing aeroacoustic measurements in wind tunnels (both open-jet and closed-section), flying aircraft, and engine test beds. This paper provides a review of the most wellknown and state-of-the-art acoustic imaging methods and recommendations on when to use them. Several exemplary results showing the performance of most methods in aeroacoustic applications are included. This manuscript provides a general introduction to aeroacoustic measurements for non-experienced microphone-array users as well as a broad overview for general aeroacoustic experts.

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Section: Compressive-sensing Beamformingmentioning

confidence: 99%

Section: Applicationsmentioning

confidence: 99%

A review of acoustic imaging methods using phased microphone arrays

et al. 2019

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“…Modern signal processing techniques such as deconvolution techniques [9], quantitative beamforming [10] and Compressed Sensing [11][12][13][14] remove the array sidelobe pattern and yield mode spectra with higher dynamic range and resolution. This is crucial when ring arrays with irregular sensor spacing are applied in order to analyse a larger mode range.…”

Section: Introductionmentioning

confidence: 99%

Investigation of Sound Generation and Transmission Effects Through the ACAT1 Fan Stage using Compressed Sensing-based Mode Analysis

Behn

Tapken

2019

25th AIAA/CEAS Aeroacoustics Conference

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In an extensive measurement campaign at the UFFA test rig of AneCom AeroTest in Wildau, Germany, the sound field generated from the ACAT1 fan stage was measured by several dynamic pressure sensor arrays of different geometrical arrangements at the inlet, interstage and bypass section. The sparse ring arrays with irregular and optimised geometries are utilised in combination with the Compressed Sensing-based mode analysis in order to investigate the tonal and broadband sound generation and transmission with high resolution. From the azimuthal mode spectra, the relation between the cut-on mode range at the sources and the dominant modes at the measurement sections is observed and used to determine the contribution of different sound generation mechanisms. With the help of interstage mode analyses strong rotor-coherent contributions due to rotor wake irregularities are identified and the rotor-shielding effect is assessed. The dependencies of the broadband mode spectra with respect to the operation points and working lines are shown and the contribution of stator and rotor bound sources is investigated. Results indicate that mode scattering at the stator vane row has a significant influence on the downstream radiated sound field. Evidence is further found for the occurrence of the acoustic tunnel effect, where cutoff modes excited at the stator leading edge become cut-on during the propagation through the inter-vane channels. This effect triggers mode scattering towards rotor counter-rotating modes and increases the sound radiation from fan stages.

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“…When the analysis is restricted to tonal (shaft-periodic) sound, advantage can be taken from the fact that the sound field is usually dominated by a limited set of modes. This "sparsity" of modes has recently 11,12 been exploited by applying Compressed (or Compressive) Sensing, which is a signal processing technique aiming at representing measured data with fewer samples than prescribed by the Nyquist-Shannon sampling criterion. The Compressed Sensing technique features the minimisation of the L1-norm of the vector of mode amplitudes.…”

Section: Nomenclaturementioning

confidence: 99%

“…By application of an extended version of the Orthogonal Matching Pursuit algorithm a maximum number of dominant modes is determined accurately with a given array and after a deconvolution step the remaining mode spectrum is estimated using e.g. the DFT 11 . For broadband noise, of which the acoustic energy is more equally distributed over the mode orders, this may not be the most appropriate approach.…”

Section: Nomenclaturementioning

confidence: 99%

Deconvolution of Azimuthal Mode Detection Measurements

Sijtsma¹,

Brouwer

2017

23rd AIAA/CEAS Aeroacoustics Conference

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Unequally spaced transducer rings make it possible to extend the range of detectable azimuthal modes. The other side of the coin is that the response of the mode detection algorithm to a single mode is distributed over all detectable modes, similarly to the Point Spread Function of Conventional Beamforming with microphone arrays. With multiple modes the response patterns interfere, leading to a relatively high "noise floor" of spurious modes in the detected mode spectrum, in other words, to a low dynamic range. In this paper a deconvolution strategy is proposed for increasing this dynamic range. It starts with separating the measured sound into shaft tones and broadband noise. For broadband noise modes, a standard Non-Negative Least Squares solver appeared to be a perfect deconvolution tool. For shaft tones a Matching Pursuit approach is proposed, taking advantage of the sparsity of dominant modes. The deconvolution methods were applied to mode detection measurements in an AneCom fan rig. An increase in dynamic range of typically 10 to 15 dB was found.

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Efficient Azimuthal Mode Analysis using Compressed Sensing

Cited by 27 publications

References 10 publications

A review of acoustic imaging methods using phased microphone arrays

A review of acoustic imaging methods using phased microphone arrays

Investigation of Sound Generation and Transmission Effects Through the ACAT1 Fan Stage using Compressed Sensing-based Mode Analysis

Deconvolution of Azimuthal Mode Detection Measurements

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