航空发动机快变信号的稀疏结构化增强原理研究

The aero-engine is the heart of the airplane. The safety and reliable operation are the first priority of the aero-engine, which always attracts the global concern. However, the aero-engine services in an extreme environment, such as high speed, high temperature, heavy load, and strong disturbance, which may result in serious accidents. As a result, service safety of aero-engine becomes one of the major bottlenecks for advancing the aero-engine technology. Because of the factors such as the frequently varying condition, the sharp speed-up or speed-down, and high-speed varying-stiffness, the instantaneous frequency of the vibration of the aero-engine is always highly oscillated and changed with time. The vibration signals with fast time-varying instantaneous frequency are strong nonstationary. This project will analyze aero-engine vibration signals with fast time-varying instantaneous frequency, and research the sparsity-assisted structured enhancement principle for aero-engine vibration analysis with fast-varying instantaneous frequency. Firstly, the influence of the vibration noise will be investigated, and the statistic model of the vibration noise will be studied to improve the robustness of the vibration signal analysis. Secondly, the sparsity priors and the time-frequency priors will be introduced to enhance the performance of the vibration signal analysis, and thus to improve the effectiveness of the sparsity-assisted machinery fault diagnosis. Thirdly, the vibration noising and customized shrinkage/thresholding operator-driven adaptive optimization method will be studied, and then the accurate fault diagnosis can be realized. Lastly, taking a center aero-engine dual-rotor system as the research object, the experimental and engineering study will be implemented. Based on these researches, the sparsity-assisted structured enhancement method will be proposed for aero-engine vibration analysis with fast-varying instantaneous frequency. The research results of this project will provide a theoretical basis and technical support for aero-engine fault diagnosis, and thus will provide a significant role in guaranteeing the safety and reliable operation of mechanical equipment.

航空发动机是飞机的“心脏”，常常工作于高速、高温、重载、强扰动等极端服役环境，导致灾难性事故时有发生，航空发动机故障诊断是制约我国航空发动机运行安全的“卡脖子”瓶颈。本项目针对航空发动机快变信号分析与故障诊断难点，根据快变信号的物理特征与数学特征，研究快变信号分析的稀疏结构化增强原理与方法，以提高航空发动机运行安全保障能力。具体包括：研究航空发动机振动噪声影响与噪声建模方法，提升快变信号分析鲁棒性；研究航空发动机快变信号稀疏时频结构先验增强原理，提高快变信号分析能力；研究振动降噪与定制化阈值收缩算子驱动的自适应优化方法，实现航空发动机快变信号分析与故障诊断；以某型航空发动机双转子系统为对象，开展实验与工程验证研究。在上述研究基础上，提出航空发动机快变信号的稀疏结构化增强原理与方法，探索航空发动机故障诊断研究的基础理论与工程应用方法，为提高我国航空发动机运行安全提供理论与技术支撑。

航空发动机是飞机的“心脏”，常常工作于高速、高温、重载、强扰动等极端服役环境，导致灾难性事故时有发生，健康监测与故障诊断对保障航空发动机运行安全至关重要。本项目以航空发动机频繁变工况、大幅升降速、高转速变刚度运行等引起的瞬时频率快速变化、且具有强时变非平稳特性的快变信号为分析对象，研究航空发动机快变信号分析稀疏结构化增强原理。.（1）提出了航空发动机振动噪声广义高斯混合模型建模方法，在噪声建模框架下将实际的多源噪声分布与理论上的拉普拉斯分布、混合高斯分布进行有效的拟合匹配，提升快变信号分析算法的鲁棒性；（2）提出了快变信号时频结构先验增强方法，构建了数据保真项、稀疏正则项以及快变结构正则项三者融合的航空发动机快变信号稀疏优化模型，提升快变信号特征提取精度；（3）提出了定制化阈值收缩算子驱动的自适应优化方法，实现航空发动机快变信号分析与故障诊断；（4）搭建了航空发动机双转子系统等试验平台，开展了实验研究与工程应用。.基于本项目相关研究成果，以第一作者或通讯作者发表SCI论文8篇，会议论文2篇；申请并授权发明专利6项。航空发动机快变信号研究成果获得2020年教育部自然科学一等奖1项“航空发动机快变信号匹配时频及智能诊断理论与应用”，项目负责人排名第三。作为骨干成员参与国家自然科学基金重大研究计划集成项目“航空发动机主轴承及传动系统故障智能诊断研究”，本项目研究成果将集成于某型航空发动机健康管理系统中。 基于本项目的资助与相关研究，项目负责人于2021年晋升教授，获批国家自然科学基金优秀青年基金，国家两机重大专项课题，以及中国航发集团企业横向课题2项，作为骨干成员参与、国家自然科学基金重点项目“航空发动机燃油控制系统服役安全保障方法研究”（2019-2023）和国家重点研发计划项目各1项。项目负责人自2021年1起，担任领域著名期刊IEEE Transactions on Instrumentation and Measurement副编辑。

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