A compressive-sensing-based method for radial mode analysis of aeroengine fan noise. (6th January 2020)

• Record Type: Journal Article
• Authors: Bu, Huanxian; Huang, Xun; Zhang, Xin
• Is Part Of: Journal of sound and vibration. Volume 464(2020)
• Publication Date: 2020-01-06
• Subjects: Fan noise -- Radial mode detection -- Compressive sensing -- Inverse method; Sound -- Periodicals; Vibration -- Periodicals; Son -- Périodiques; Vibration -- Périodiques; Sound; Vibration; Periodicals; Electronic journals; 620.205
• DOI: 10.1016/j.jsv.2019.114930
• Languages: English
• ISSNs: 0022-460X

Abstract

Abstract: A couple of new mode detection methods are proposed in this paper to enable effective and efficient radial mode analysis of in-duct tonal sound fields by utilizing compressive sensing. The first method uses a compressive-sensing-based azimuthal mode detection and an inverse-method-based radial mode decomposition. The second method employs the compressive sensing directly from an in-duct sound propagation model. Prediction error analysis of the two techniques is numerically performed by the Monte Carlo method along with synthesized sound fields. The analysis shows that a reasonably good accuracy can be achieved with a significantly reduced number of sensors by using the proposed compressive-sensing-based methods. Moreover, the proposed methods enable a sensor layout that would minimize the interference to the main flow inside the duct. In addition, the second approach is more advantageous in terms of the performance and flexibility in arrangement of the sensors. Finally, the proposed method is experimentally demonstrated in a duct test rig in anechoic wind tunnel tests. The results confirm the potential capability for aeroengine aeroacoustics tests in a practical testing facility.