LAUSR

Abstract We are now at a point where airframes, aeroengines and their integration require radical changes to meet increasingly aggressive environmental targets. Generally, fan noise emitted from rotor-stator assemblies would be one of the dominant noise sources for modern and next-generation aircraft engines, which shall direct most research interest into fans in the coming decade and, therefore, the associated measurement constitutes the main focus of the current review. Amongst various approaches, an experimental study of fan noise is usually efficient and of high-fidelity, but the associated cost is expensive. Moreover, the design of a test would be time-consuming due to the adequate choice of testing methods with the adaption to the testing case and rig. In addition, in most cases the experimental setup requires some sort of optimization to achieve high measurement accuracy. This article provides a contemporary review of the most well-known and state-of-the-art testing methods with the focus on fan noise problems. More specifically, the acoustic mode detection and noise source reconstruction methods are most relevant to the understanding of noise generation mechanism and propagating characteristics, which are useful for further noise reduction studies, and therefore are extensively reviewed in this article. As timely guidance to potential interested readers, this paper also provides an overview of recent developments based on the compressive sensing and machine learning techniques that have enabled disruptive innovations by fundamentally changing the testing practices of conventional measurement methods, thus constituting the continued research direction for next-generation aeroengines.