Skip to Main content Skip to Navigation

Caractérisation de sources acoustiques par imagerie en écoulement d'eau confiné

Abstract : The noise requirements for naval and research vessels lead to the development of new characterization methods. The propeller, which is the most important source in the far field, is usually studied in a water tunnel. However, due to the reverberation in the tunnel and the high level of flow noise, the characterization may be difficult. The aim of the thesis is to improve the measurement capabilities of the DGA Hydrodynamic tunnel (GTH) in terms of noise radiated by models in flow configurations.The propagation model is described through the image source method. Unfortunately, the reflection coefficients of the tunnel walls are generally unknown and it is proposed to estimate these parameters using an inverse method and the knowledge of some reference transfer functions. The boundary layer noise (BLN) may be stronger than the acoustic signal, therefore a Robust Principal Component Analysis is introduced in order to separate, blindly or semi-blindly, the acoustic signal from the noise. This algorithm is taking advantage of the low rank and sparse structure of the acoustic and the BLN cross-spectrum matrices. Then an acoustic imaging technique based on the equivalent source method is applied in order to localize and quantify correlated or decorrelated sources. Finally, the potentiality of the proposed techniques is evaluated experimentally in the GTH in the presence of an acoustic source and a controlled flow.
Complete list of metadata

Cited literature [132 references]  Display  Hide  Download
Contributor : ABES STAR :  Contact
Submitted on : Tuesday, May 15, 2018 - 1:59:06 PM
Last modification on : Tuesday, March 31, 2020 - 3:22:45 PM
Long-term archiving on: : Monday, September 24, 2018 - 12:49:05 PM


Version validated by the jury (STAR)


  • HAL Id : tel-01792389, version 1


Sylvain Amailland. Caractérisation de sources acoustiques par imagerie en écoulement d'eau confiné. Acoustique [physics.class-ph]. Université du Maine, 2017. Français. ⟨NNT : 2017LEMA1037⟩. ⟨tel-01792389⟩



Record views


Files downloads