Model-based Monitoring of Rotor Systems

对于许多典型的转子应用，例如涡轮机、压缩机和泵，安全性和可靠性起着重要作用，因为故障可能导致整个发电厂或飞机关闭。然而，许多缺陷在变得关键之前就可以被识别出来，因为当它们很小的时候，它们已经影响了转子的行为。因此，状态监测可以用来寻找这些迹象，并对出现的损害进行警告。目前应用的监测系统大多只使用测量数据进行诊断。因此，很难具体说明误差的位置和数量以及转子的未来行为。这些信息可以在添加受损转子的仿真模型时获得。这就是基于模型的监控。在本研究项目中，开发了一个基于模型的自主监控系统。在执行安装阶段后，系统会自动监控系统的振动。如果它们与正常操作不同，将记录测量数据，并将其与存储在损坏库中的典型错误模式进行比较。基于这种错误分类的结果，为了优化故障参数，进行了适当的仿真。优化的仿真可以进行详细的损伤诊断。目前，损伤库包括不平衡、静态弯曲、角度不对中和转子跌落引起的碰摩。在接下来的检查中，应扩大损伤库。重点在于进一步的错位现象。它们尤其出现在带有多个轴承的转子中，就像发电厂中常见的那样。应研究在识别过程中如何将基座内的不对中分配给特定轴承，以及如何量化其量。第二次扩展库应包括刚性联轴器中的不对中。在这种情况下，未对准的部件随转子旋转，因此该误差与基座中的未对准具有不同的特征。实际上，它非常类似于转子的静态弯曲。离合器存在平面角不匹配和径向偏移两种不对准现象，为了检测这些故障，必须对现有的试验台进行更新。还应该可以包括不同数量的错误。对于基于信号的故障分类，必须找到这些错误的典型模式。仿真中的误差模型应尽可能简单，以便快速识别误差，但必须正确描述误差特性。为了进一步验证，应测试几种设置，例如对试验台的小修改或几个错误的叠加。

For many typical applications of rotors, e.g. turbines, compressors and pumps, safety and reliability play an important role as failures could result in a shutdown of entire power plants or airplanes. Yet, many defects can be recognized before they get critical as they already influence the behavior of the rotor when they are small. So, condition monitoring could be used to search for these signs and to warn against the arising damage.Most of the currently applied monitoring systems only use measured data for diagnosis. Therefore, it is difficult to specify the location and amount of error and the future behavior of the rotor. This information can be gained when adding a simulation model of the damaged rotor. This is called the model-based monitoring.In this research project, an autonomous system for model-based monitoring is developed. After performing an installation phase, the system automatically monitors the vibrations of the system. If they differ from normal operation, the measurement data will be recorded and compared with typical patterns of errors which are stored in a damage library. Based on the results of this error classification, a suitable simulation is started in order to optimize the fault parameters. The optimized simulation allows a detailed damage diagnosis.Contemporary, the damage library includes unbalance, static bow, angular misalignment and rubbing due to rotor drops. In the following examinations, the damage library should be expanded. The focus lies on further misalignment phenomena. They especially occur in rotors with multiple bearings like they are common in power plants. It should be investigated how misalignment within the pedestal can be allocated to specific bearings during identification and how its amount can be quantified.The second expansion of the library should include misalignment in rigid couplings. In this case, the misaligned components rotate with the rotor, so this error has different characteristics than misalignment in the pedestal. In fact, it is quite similar to static bow of the rotor. There exist two kinds of misalignment in clutches, which are an angular mismatch between the plane faces and an offset in radial direction.In order to examine these failures, the existing test rig has to be updated. It should also be possible to include different amounts of the errors. For the signal-based fault classification, typical patterns for these errors must be found. The error models in simulation should be as simple as possible for fast error identification, yet they must describe the error characteristics correctly. For further verification, several setups should be tested, e.g. small modifications of the test rig or the superposition of several errors.