This paper proposes the enhancement of a previously developed method for beamforming in engine ducts, which enables phased array beamforming in the interstage section of a turbofan engine. The enhanced method features the use of tailored Green’s functions, to deal with the annular geometry and the non-uniform (swirling) flow in this part of the engine duct. A complicating factor is the occurrence of resonant acoustic modes, when there is no acoustic lining. The paper describes the computation of the tailored Green’s functions and how resonant modes can be subtracted. The use of the method is firstly demonstrated by application to simulated sources, and is subsequently applied to test data. At the moment there is no other information on the sources that could be used to validate the method. The only indication that the method is working well is that it should find the correct number of rotating fan blades in the beamforming plots. This is indeed the case, but only in a small fraction of the results.

Most acoustic imaging methods assume the presence of point sound sources and, hence, may fail to correctly estimate the sound emissions of distributed sound sources, such as trailing-edge noise. In this contribution, three integration techniques are suggested to overcome this issue based on models considering a single point source, a line source, and several line sources, respectively. Two simulated benchmark cases featuring distributed sound sources are employed to compare the performance of these integration techniques with respect to other well-known acoustic imaging methods. The considered integration methods provide the best performance in retrieving the source levels and require short computation times. In addition, the negative effects of the presence of unwanted noise sources, such as corner sources in wind-tunnel measurements, can be eliminated. A sensitivity analysis shows that the integration technique based on a line source is robust with respect to the choice of the integration area (shape, position, and mesh fineness). This technique is applied to a trailing-edge-noise experiment in an open-jet wind tunnel featuring a NACA 0018 airfoil. The location and far-field noise emissions of the trailing-edge line source were calculated.

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 well-known 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.

The recently introduced high-resolution (HR)-CLEAN-SC algorithm for acoustic imaging provides ‘super-resolution’, i.e. the ability to discern sound sources located closer than the Rayleigh resolution limit. This is achieved by allowing the source markers to be relocated from the actual source locations within a certain constraint to avoid the combined influence of the other sound sources. The freedom to relocate the source markers to increase the performance of the algorithm depends on the maximum sidelobe level of the acoustic array used. This paper presents an ‘enhanced’ version of the HR-CLEAN-SC algorithm which benefits from low maximum sidelobe level array design. The source marker constraint μ is adapted to the maximum sidelobe level at each frequency. Application to up to four synthetic sound sources shows that the sources can be resolved at half the frequency associated with the Rayleigh resolution limit, when an acoustic array optimized for low maximum sidelobe level is used in combination with Enhanced HR-CLEAN-SC. This improves source discrimination compared to when the HR-CLEAN-SC algorithm is used with a benchmark acoustic array design. The results are confirmed by experimental validation in which up to four loudspeakers and the same array configurations as in the synthesized data case are used.

Unequally spaced transducer rings make it possible to extend the range of detectable azimuthal modes. The disadvantage 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 a fan rig. An increase in dynamic range of typically 10–15 dB was found.

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.

Significant spectral broadening of tone noise by jet shear-layer turbulence can occur if the tone frequency and the path length through the shear layer are sufficiently large. A typical example of spectral broadening or ‘tone haystacking’ are turbine aero-engine tones which exhibit little or no haystacking when measured inside the engine but are sometimes so strongly haystacked in the far-field that the original tone cannot be observed in the measured spectrum. This haystacking of turbine tones requires an engineering method that can predict both the far-field haystacking and the associated reduction in incident tone level. A previous published method, the so-called ‘beta’ correlation has displayed encouraging agreement with a number of experimental datasets but significant disagreement with others. In this paper another set of experimental data, which includes phased array data, is analysed. The objective is to improve our understanding of the tone haystacking mechanisms with the aid of beamforming and to compare with a prediction from weak scattering theory, in the form of a simple Doppler shift relationship between frequency and angle scattering, assuming a frozen turbulence model. The experimental data acquired by QinetiQ and CLEAN-SC beamformer results described herein begin to provide validation of that prediction, which may lead to resolution of the discrepancies previously observed between the beta correlation and the data acquired under a GARTEUR project.

In this article, a high-resolution extension of CLEAN-SC is proposed: high-resolution-CLEAN-SC. Where CLEAN-SC uses peak sources in ‘dirty maps’ to define so-called source components, high-resolution-CLEAN-SC takes advantage of the fact that source components can likewise be derived from points at some distance from the peak, as long as these ‘source markers’ are on the main lobe of the point spread function. This is very useful when sources are closely spaced together, such that their point spread functions interfere. Then, alternative markers can be sought in which the relative influence by point spread functions of other source locations is minimised. For those markers, the source components agree better with the actual sources, which allows for better estimation of their locations and strengths. This article outlines the theory needed to understand this approach and discusses applications to 2D and 3D microphone array simulations with closely spaced sources. An experimental validation was performed with two closely spaced loudspeakers in an anechoic chamber.