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Research Papers: Gas Turbines: Aircraft Engine

Continuous-Scan Phased Array Measurement Methods for Turbofan Engine Acoustic Testing

[+] Author and Article Information
Parthiv N. Shah, Andrew White

ATA Engineering, Inc.,
San Diego, CA 92128

Dan Hensley

ATA Engineering, Inc.,
Lakewood, CO 80401

Dimitri Papamoschou

The Henry Samueli School of Engineering,
Department of Mechanical and
Aerospace Engineering,
University of California,
Irvine, Irvine, CA 92697

Håvard Vold

Vold, LLC,
Charleston, SC 29412

Contributed by the Aircraft Engine Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received June 22, 2018; final manuscript received December 19, 2018; published online February 11, 2019. Editor: Jerzy T. Sawicki.

J. Eng. Gas Turbines Power 141(8), 081201 (Feb 11, 2019) (13 pages) Paper No: GTP-18-1310; doi: 10.1115/1.4042395 History: Received June 22, 2018; Revised December 19, 2018

Imaging of aeroacoustic noise sources is routinely accomplished with geometrically fixed phased arrays of microphones. Several decades of research have gone into improvement and optimization of sensor layouts, selection of basis models, and deconvolution algorithms to produce sharper and more localized images of sound-producing regions in space. This paper explores an extension to conventional phased array measurements that uses slowly, continuously moving microphone arrays with and without coupling to rigid fixed arrays to improve image quality and better describe noise mechanisms on turbofan engine sources such as jet exhausts and turbomachinery components. Three approaches are compared in the paper: fixed receiver beamforming (FRBF), continuous-scan beamforming (CSBF), and multireference CSBF (MRCSBF). The third takes advantage of transfer function matrices formed between fixed and moving sensors to achieve effective virtual arrays with spatial density one to two orders of magnitude higher, with practical sensor budgets and scan speeds. The MRCSBF technique produces array sidelobe rejection that approaches the theoretical array pattern of a continuous two-dimensional (2D) aperture. The implications of this finding are that better source localization may be achieved with conventional delay and sum (DAS) beamforming (BF) with practical sensor budgets, and that an improved starting image of the sound source can be provided to deconvolution algorithms. These findings are demonstrated on analytical and experimental examples from a low-cost rotating phased array using point sound sources, as well as linear scanning array experiments of an impinging jets point source and a near-sonic jet nozzle exhaust.

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References

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Figures

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Fig. 1

Plane wave formulation for array pattern

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Fig. 2

Array pattern magnitude (left) under various processing assumptions for 16-microphone (four spiral arm) array (right)

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Fig. 3

Array pattern magnitude (left) under various processing assumptions for 64-microphone spiral array (right)

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Fig. 4

Synthetic experiment showing distributed sources on Z = 0 plane and example array (circle (FR) and square (CS) symbols)

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Fig. 5

Four-source model at 6976 Hz (Δf = 64 Hz). CS microphones given by circular symbols complete one revolution: (a) FRBF 16, (b) CSBF 16, (c) MRCSBF 8 fixed/8 scan, and (d) MRCSBF 16 fixed/8 scan.

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Fig. 6

Proof-of-concept rotating array

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Fig. 7

Rotating array experiment results, 6976 Hz. Array microphones were located ∼50 cm away in Z: (a) FRBF, (b) MRCSBF 16/8 array stationary, (c) CSBF—rotating array, and (d) MRCSBF 16/8—rotating array.

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Fig. 8

UCI Aeroacoustics Laboratory; fixed and scanning (double sided arrow) microphones are illustrated

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Fig. 9

Microphone layout in UCI experiments

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Fig. 10

Pressure autospectra for odd-numbered microphones in the 12-microphone array simulation of a point source. Microphone 01 is the CS channel; others are FR.

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Fig. 11

Beamforming images from numerical simulation of a 12-microphone array with random noise point source in UCI facility. MRCSBF (left) and CSBF (right) results with maximum level set to 0 dB and dynamic range set to 20 dB.

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Fig. 12

Photograph of IJS experiment setup with zoomed-in view of IJS nozzle

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Fig. 13

Pressure-time histories of odd-numbered channels from IJS experiment, with time in seconds on abscissae and pressure in pascals on ordinates. Mic 01 is the CS microphone.

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Fig. 14

Pressure autospectra of odd-numbered microphones in UCI IJS experiment. Microphone 1 is CS.

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Fig. 15

Ranked singular values (diagonal of Σ) of 11 × 11 GRR,avg=UΣUH matrix in IJS experiment

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Fig. 16

Beamforming images from 12 microphone array experiment with IJS in UCI facility; MRCSBF (left) and CSBF (right) results with maximum level set to 0 dB and dynamic range set to 20 dB

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Fig. 17

Photograph of near-sonic jet nozzle test

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Fig. 18

Pressure-time histories of odd-numbered channels in near-sonic jet experiment, with time in seconds on abscissae and pressure in pascals on ordinates. Mic 01 is the CS microphone.

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Fig. 19

Pressure autospectra of odd-numbered microphones in near-sonic jet experiment. Microphone 01 is CS. Vertical line shows Strouhal number of unity.

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Fig. 20

Ranked singular values (diagonal of Σ) of 11 × 11 GRR,avg=UΣUH matrix in near-sonic jet experiment. Vertical line shows Strouhal number of unity.

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Fig. 21

Beamforming images from 12 microphone array experiment with near-sonic jet nozzle in UCI facility: MRCSBF (left) and CSBF (right) results, with maximum level set to 0 dB and dynamic range set to 20 dB

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