The fan-stator stage of turbofan engines is one of the main regions of broadband noise generation. The trend of increasing bypass ratios will make fan-stator broadband noise even more significant, as jet noise will decrease and nacelles will become shorter, thus leaving less space for liners. Within the fan-stator stage there are several aerodynamic phenomena that can cause broadband noise. However, techniques for experimental identification and quantification (and thus classification) of these broadband noise sources are still immature. Beamforming using in-duct microphones is feasible, but a major challenge is the strong rotational component of the flow that needs to be accounted for in the steering vectors. This paper proposes a solution for that challenge, based on a fast ray tracing approach. With synthesized microphone array data, calculated with an approximate method for the Green’s function in a ducted swirling flow, it is demonstrated that detection of acoustic sources is possible.@en

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.

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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.

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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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