中介轴承寿命预测方法与寿命试验研究

发布时间：2018-10-17 17:47

【摘要】：中介轴承作为航空发动机的关键零部件,工作在高温、高速、重载、强振动的恶劣环境下,其性能的可靠性直接制约着飞行安全与飞机性能。因此深入研究中介轴承的运行规律,对其进行实时的状态监测,实现对中介轴承的故障诊断和寿命预测,对于视情维修,降低维修成本,提高航空发动机健康管理水平有着重要的现实意义。本文以中介轴承为主要研究对象,研究基于Cox比例故障模型的寿命预测理论,并设计中介轴承试验台,进行寿命试验,开发了相应的中介轴承状态监测和寿命预测系统,论文主要研究内容如下：首先,本文论述了选题背景以及寿命预测理论和轴承试验台的国内外研究现状；介绍了中介轴承的概况；剖析了中介轴承的常见失效形式；研究了轴承的振动机理及时域、频域、时频域内的振动信号特征提取分析方法。其次,介绍了可靠性与寿命等相关指标；研究了基于威布尔分布的比例故障率模型的寿命预测方法,选择了最佳的寿命基准函数；研究了基于极大似然估计模型的参数估计方法,基于相关性分析的协变量选取方法以及基于AR模型的协变量趋势预测方法；根据FEMTO-ST研究所提供轴承全寿命周期的试验数据,选取了三个协变量,建立了基于威布尔分布的比例故障率模型,并做出了可靠性函数图,得到了可靠性寿命,验证了模型的有效性和可靠性。然后,以中介轴承为主要研究对象,模拟航空发动机的实际支撑结构和工作环境,设计了中介轴承双转子试验台；进行了中介轴承加速度寿命试验,分析并选择了合适的加速应力,对停机阈值的选择做了深入研究；设计了中介轴承加速寿命试验的监测方案,对传感器的选择和布置做了详细描述；进行了寿命过程中的典型试验,做了中介轴承不同损伤程度的寿命试验分析。最后,开发了中介轴承状态监测与寿命预测系统。介绍了系统的软件和硬件开发环境；根据监测方案要求,状态监测部分实现了温度监测、转速监测、位移监测和振动监测,寿命预测系统部分实现了振动信号特征提取,模型的协变量选取与趋势分析,模型的参数估计和可靠性寿命估计,系统还实现用户登陆、报警设置、数据保存,拥有良好的人机关系。
[Abstract]:As the key parts of aero-engine, intermediate bearings work in the harsh environment of high temperature, high speed, heavy load and strong vibration. The reliability of their performance directly restricts flight safety and aircraft performance. Therefore, the running law of intermediary bearing is deeply studied, the real-time condition monitoring is carried out, the fault diagnosis and life prediction of intermediary bearing are realized, and the maintenance cost is reduced according to the situation. It is of great practical significance to improve the level of aero-engine health management. In this paper, the life prediction theory based on Cox proportional fault model is studied, and the life test bench is designed to carry out the life test, and the corresponding intermediate bearing condition monitoring and life prediction system is developed. The main contents of this paper are as follows: first, this paper discusses the background of the topic, the life prediction theory and the domestic and foreign research status of the bearing test bed, introduces the general situation of the intermediate bearing, analyzes the common failure forms of the intermediate bearing. The vibration mechanism of bearing and the extraction and analysis methods of vibration signals in time domain, frequency domain and time frequency domain are studied. Secondly, the reliability and service life are introduced, the life prediction method of proportional failure rate model based on Weibull distribution is studied, and the best life reference function is selected. Parameter estimation method based on maximum likelihood estimation model, covariable selection method based on correlation analysis and covariable trend prediction method based on AR model are studied. The proportional failure rate model based on Weibull distribution is established and the reliability function diagram is given. The reliability life is obtained and the validity and reliability of the model are verified. Then, taking the intermediate bearing as the main research object, simulates the actual supporting structure and working environment of the aeroengine, designs the double rotor test bench of the intermediate bearing, carries out the acceleration life test of the intermediate bearing, The suitable acceleration stress is analyzed and selected, the selection of stop threshold is studied deeply, the monitoring scheme of intermediate bearing accelerated life test is designed, and the selection and arrangement of sensor are described in detail. The typical life test was carried out, and the life test of intermediate bearing with different damage degree was made. Finally, an intermediate bearing condition monitoring and life prediction system is developed. This paper introduces the software and hardware development environment of the system, according to the requirements of the monitoring scheme, the state monitoring part realizes temperature monitoring, rotational speed monitoring, displacement monitoring and vibration monitoring, and the life prediction system realizes the feature extraction of vibration signal. Covariable selection and trend analysis of the model, parameter estimation and reliability life estimation of the model. The system also realizes user login, alarm setting, data saving and good man-machine relationship.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：V263.6

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