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To obtain higher resolution acoustic source plots from microphone array measurements, deconvolution techniques are becoming increasingly popular. Deconvolution algorithms aim at identifying Point Spread Functions (PSF) in source plots, and may therefore fall short when actual beam patterns of measured noise sources are not similar to synthetically obtained PSF's. To overcome this, a new version of the classical deconvolution method CLEAN is proposed here: CLEAN-SC. By this new method, which is based on spatial source coherence, side lobes can be removed of actually measured beam patterns. Essentially, CLEAN-SC iteratively removes the part of the source plot which is spatially coherent with the peak source. A feature of CLEAN-SC is its ability to extract absolute sound power levels from the source plots. The merits of CLEAN-SC were demonstrated using array measurements of airframe noise on a scale model of the Airbus A340 in the 8×6 m 2 closed test section of DNW-LLF.

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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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A method is described for the location of moving sources by a microphone array. This method can be applied to out-of-flow measurements in an open jet wind tunnel. For that purpose, an expression is derived for the pressure Held of a moving monopole in a uniform flow. It is argued that the open jet shear layer does not form a serious obstacle. A technique is described for reconstruction of power spectra with high signal/noise ratio. The method was implemented for rotating sources, resulting in the computer program ROSI ("Rotating Source Identifier")* Applications of ROSI are given for rotating whistles, blades of a helicopter in hover and wind turbine blades. The test with the rotating whistles demonstrated convincingly the capability to reconstruct the emitted sound. On the helicopter blades, rotating broadband noise sources were made clearly visible. On the wind turbine blades, noise emitted from the leading and trailing edge could be distinguished well. Nomenclature e x = unit vector in jc-direction G = Green's function, Eq. (6) M = Mach number of uniform flow N = number of microphones p = acoustic pressure Q = inner product, Eq. (11) T = transfer function, Eq. (12) x = receiver position x n = microphone position 8 = Dirac delta function e n (t) = noise, Eq. (14) % n (t) = microphone signal o(t) = source signal 6(t) = reconstructed source signal o n (t) = partly reconstructed source signal, Eq. (20) T e = emission time £ (t)

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.

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