TY - GEN A1 - Zenger, Florian A1 - Herold, Gert A1 - Becker, Stefan A1 - Sarradj, Ennes T1 - Sound source localization on an axial fan at different operating points T2 - Experiments in Fluids Y1 - 2016 U6 - https://doi.org/10.1007/s00348-016-2223-8 SN - 0723-4864 SN - 1432-1114 VL - 57 SP - 136 ER - TY - GEN A1 - Sarradj, Ennes A1 - Herold, Gert T1 - A Python framework for microphone array data processing T2 - Applied Acoustics Y1 - 2016 U6 - https://doi.org/10.1016/j.apacoust.2016.09.015 SN - 0003-682X VL - 116 SP - 50 EP - 58 ER - TY - GEN A1 - Herold, Gert A1 - Geyer, Thomas A1 - Markus, Philipp A1 - Sarradj, Ennes T1 - Simultaneous Sound Power Measurement of Engine Components T2 - SAE International Journal of Passenger Cars - Mechanical Systems Y1 - 2016 U6 - https://doi.org/10.4271/2016-01-1774 SN - 1946-3995 SN - 1946-4002 VL - 9 IS - 3 SP - 974 EP - 979 ER - TY - GEN A1 - Hoeltgen, Laurent A1 - Breuß, Michael A1 - Herold, Gert A1 - Sarradj, Ennes T1 - Sparse ℓ1 regularisation of matrix valued models for acoustic source characterisation T2 - Optimization and Engineering N2 - We present a strategy for the recovery of a sparse solution of a common problem in acoustic engineering, which is the reconstruction of sound source levels and locations applying microphone array measurements. The considered task bears similarities to the basis pursuit formalism but also relies on additional model assumptions that are challenging from a mathematical point of view. Our approach reformulates the original task as a convex optimisation model. The sought solution shall be a matrix with a certain desired structure. We enforce this structure through additional constraints. By combining popular splitting algorithms and matrix differential theory in a novel framework we obtain a numerically efficient strategy. Besides a thorough theoretical consideration we also provide an experimental setup that certifies the usability of our strategy. Finally, we also address practical issues, such as the handling of inaccuracies in the measurement and corruption of the given data. We provide a post processing step that is capable of yielding an almost perfect solution in such circumstances. KW - Convex optimisation KW - Sparse recovery KW - Split Bregman KW - Microphone array KW - Matrix differentiation KW - Acoustic source characterisation Y1 - 2018 U6 - https://doi.org/10.1007/s11081-017-9357-2 SN - 1389-4420 SN - 1573-2924 VL - 19 IS - 1 SP - 39 EP - 70 ER - TY - GEN A1 - Merino-Martinez, Roberto A1 - Sijtsma, Pieter A1 - Snellen, Mirjam A1 - Ahlefeldt, Thomas A1 - Antoni, Jerome A1 - Bahr, Christopher A1 - Blacodon, Daniel A1 - Ernst, Daniel A1 - Finez, Arthur A1 - Funke, Stefan A1 - Geyer, Thomas A1 - Haxter, Stefan A1 - Herold, Gert A1 - Huang, Xun A1 - Humphreys, William A1 - Leclère, Quentin A1 - Malgoezar, Anwar A1 - Michel, Ulf A1 - Padois, Thomas A1 - Pereira, Antonio A1 - Picard, Christophe A1 - Sarradj, Ennes A1 - Siller, Henri A1 - Simons, Dick A1 - Spehr, Carsten T1 - A review of acoustic imaging methods using phased microphone arrays T2 - CEAS Aeronautical Journal N2 - 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. Y1 - 2019 U6 - https://doi.org/10.1007/s13272-019-00383-4 SN - 1869-5582 SN - 1869-5590 VL - 10 IS - 1 SP - 197 EP - 230 ER -