首页> 外文会议>Proceedings of the ASME international design engineering technical conferences and computers and information in engineering conference 2009 >APPLICATION OF A BALANCING FILTER FOR MODEL-BASED FAULT DIAGNOSIS ON A CENTRIFUGAL PUMP IN ACTIVE MAGNETIC BEARINGS
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APPLICATION OF A BALANCING FILTER FOR MODEL-BASED FAULT DIAGNOSIS ON A CENTRIFUGAL PUMP IN ACTIVE MAGNETIC BEARINGS

机译:平衡泵在离心磁力泵中基于模型的故障诊断中的应用

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This paper discusses the suitability of a special discrete filter, called balancing filter, to improve the performance of model-based fault detection and fault diagnosis on a centrifugal pump in active magnetic bearings. The focus in this subject lies on the extraction of better symptoms for the fault diagnosis. The application of the balancing filter sets up on a multi-model approach which uses a model of the system for the reference state and every fault that is to be detected. These models are stimulated with the same test signals as the ones applied to the process while it is running. To compare the simulation results of the models with the process response the output error is calculated. After this the remaining residuals are used as symptoms for the fault detection. The balancing filter is used to remove the large differences within the amplitude responses of the models caused by the lowpass characteristics of the mechanical part of the system. Hence the influence of the smaller differences caused by the examined faults is weighted equally at all interesting frequencies. This leads to new residuals which are separated more clearly. This approach is used to detect common faults appearing on centrifugal pumps as dry run, incorrect installation and worn out balance pistons.rnThe test rig used to examine the suitability of the proposed filter is a one-level centrifugal pump in magnetic bearings. The rotor of the pump is driven by an asynchronous motor at rotation speeds up to 3000 rpm. The first flexible mode of the rotor isrnlocated at 280 Hz. In the seal gap fluid-structure-interaction is appearing. The forces on the rotor are calculated based on the current applied to the bearings, while its displacement is measured by eddy current sensors integrated into the bearings. The first two natural frequencies of the system are located at about 200 Hz and 500 Hz. These frequencies are shifted when a fault is occuring. In the models for the fault states this behaviour is represented. Hence the model matching the current state of the pump leads to the lowest residual. The advantage of the balancing filter is that the detection of faults becomes more reliable. Below the examined faults, the model-based concept and the design of the balancing filter are described in detail. Results from experiments on the test rig are given to show the advantages of the balancing filter.
机译:本文讨论了一种特殊的离散过滤器(称为平衡过滤器)的适用性,以提高主动电磁轴承中的离心泵的基于模型的故障检测和故障诊断的性能。该主题的重点在于为故障诊断提取更好的症状。平衡滤波器的应用建立在多模型方法上,该方法将系统模型用于参考状态和要检测的每个故障。这些模型的刺激信号与过程运行时所施加的信号相同。为了将模型的仿真结果与过程响应进行比较,需要计算输出误差。此后,将剩余的残留物用作故障检测的症状。平衡滤波器用于消除由于系统机械部分的低通特性而导致的模型幅度响应中的较大差异。因此,在所有感兴趣的频率上,均会对由检查出的故障引起的较小差异的影响进行平均加权。这导致新残差被更清晰地分离。这种方法用于检测离心泵上出现的常见故障,如空转,不正确的安装和平衡活塞的磨损。用来检验所提出的过滤器是否适用的试验台是电磁轴承中的一级离心泵。泵的转子由异步电动机驱动,转速高达3000 rpm。转子的第一柔性模式位于280 Hz。在密封间隙中出现了流固耦合。转子上的力是根据施加到轴承上的电流来计算的,而其位移是通过集成在轴承中的涡流传感器来测量的。系统的前两个固有频率位于大约200 Hz和500 Hz。发生故障时,这些频率会发生偏移。在故障状态的模型中,这种行为得以体现。因此,与泵的当前状态匹配的模型导致最低的残差。平衡滤波器的优点是故障检测变得更加可靠。在检查的故障下方,详细描述了基于模型的概念和平衡滤波器的设计。给出了在试验台上进行的实验结果,显示了平衡滤波器的优点。

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