航空发动机叶轮机械气动噪声场阵列成像技术的关键理论和实验研究

Aircraft turbofan engine noise is mainly from turbomachinery of high spped rotations that generate spinning modal flow-induced sound, which would not only induce acousitc resonance within the duct that affects operating life, but radiate to the far-field that impedes airworthiness certifications. Acoustic imaging with microphone arrays will deepen the associated physical insights that could be helpful for controlling spinning modal sound by evaluating and improving the various low-noise designs of a turbomachinery. In this work, we will develop a new acoustic imaging testing technology based on microphone arrays. In particular, we will extend the classical beamforming method, based on the characteristics of duct acoustic propagations, to generate acoustic images of the noise sources from high speed blades in real-time. In addition, we will focus on extending our obesever method for spining modal sound field governed by partial differential equations, by investigating the observability theory of wave equations, to generate images of any cross-section within the spinning modal sound field. Finally, we will extend our existing experimental facility and conduct experiments to validate and demonstrate the new technology. In summary, we will resovle practical problems with theoretical development, study the observability of partial differential systems and acoustic array signal processing method, and conduct numerical and experimental investigations. The main focus of this research is the development and the demonstration of our new testing method. We expect that this research will accomplish important achievements in both theoretical and experimental technologies, which would finally benefit aircraft engine noise tests.

涡扇航空发动机的叶轮机械高速旋转时所产生的模态噪声会诱发声腔共振从而影响叶片使用寿命，还会辐射到远场影响适航认证，基于传声器阵列的气动噪声测试能直观揭示相关物理机制、评估和改进叶轮机械设计，是当前航空发动机测试技术研究中的前沿和热点问题之一。本项目将针对旋转部件气动噪声的气动特征，发展关键实验技术、设计测试系统和实验台。首先扩展传统波束形成方法来实时获取高速旋转叶片的噪声源成像并重构声场，探索线化波动和Euler等一类偏微分系统的可观性理论，并结合压缩感知理论来发展我们前期提出的阵列观测器方法来获取在探测空间任意截面传播的模态声场。我们还将设计测试阵列仪器、完善引导性风扇台，验证和演示所开发的新试验技术。总的来说，我们会聚焦航空发动机前沿问题，重点研究相关力学系统的可观性理论和测试新方法，开展数值模拟和实验验证，为航空发动机噪声测试问题建立理论和实验技术方面的支撑。

涡扇航空发动机的叶轮机械高速旋转时所产生的模态噪声会诱发声腔共振从而影响叶片使用寿命，还会辐射到远场影响适航认证，基于传声器阵列的气动噪声测试能直观揭示相关物理机制、评估和改进叶轮机械设计，是当前航空发动机测试技术研究中的前沿和热点问题之一。本项目针对旋转部件气动噪声的气动特征，发展关键实验技术、设计测试系统和实验台，并探索了机器学习在航空发动机噪声中的研究新范式。取得的重要成果及其科学意义和应用价值有：（1）针对航空发动机风扇噪声源成像实验难题，分别提出高频声波探测低频流动结构的实验思路及压缩感知技术，为解析风扇噪声的湍流声源关键科学问题提供实验新技术。（2）设计测试阵列仪器，完善引导性风扇台，建成带流动、以及声衬段的航空发动机风扇噪声实验台，验证和演示所开发的新试验技术。（3）在气动声学研究中探索机器学习研究新范式，将航空发动机噪声理论模型作为代理模型来高效地产生海量训练数据，将声学内在动量守恒约束嵌入U-net神经网络，发展脉动压力场到脉动速度场的深度学习技术，提出航空发动机外涵道流管内噪声源反演和健康诊断新方法。.总的来说，我们聚焦航空发动机噪声前沿问题，重点研究相关气动噪声测试新方法，并开展数值模拟和实验验证，为航空发动机噪声测试问题建立理论和实验技术方面的支撑。本项目支持下培养的博士生有1人获得北京大学和北京市优秀毕业生荣誉，成果发表在Progress of Aerospace Science等业内权威期刊，同时引导和支撑了我国航空业在研的2座风扇噪声台的建设调试工作。