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MODEL BASED SHAFT CRACK IDENTIFICATION IN ROTATING MACHINERY

机译:旋转机械中基于模型的轴裂纹识别

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Modern rotating machinery is prone to fatigue cracks due to the severe working and continuously varying loading conditions. To avoid failure of the rotating systems due to these aacks, the system needs to be continuously monitored. The reliability of the machinery can be enhanced with the fault identification at the early stages of their occurrence. Model based methods are used for crack identification in rotating systems successfully. Model based methods are of different types. One of the methods, the equivalent loads minimization method is studied here. It has a limitation that the error in identified crack depth increases with decrease in number of measured vibrations. In the present work, the theoretical fault model loads used in least squares minimization algorithm are transformed using modal expansion to reduce error in the identified fault parameters. The crack is identified accurately even in the case of less number of measured vibrations. The method is applied for crack identification in a centrifugal pump rotor using transverse vibrations. The results presented are obtained purely from FEM simulations.
机译:由于严重的工作和不断变化的装载条件,现代旋转机械易于疲劳裂缝。为避免由于这些acks而导致的旋转系统失败,因此需要连续监测系统。可以在其发生早期阶段的故障识别中增强机器的可靠性。基于模型的方法用于成功旋转系统的裂缝识别。基于模型的方法是不同类型的。其中一个方法,在此研究等效的负载最小化方法。它有一个限制,识别裂纹深度的误差随着测量振动的数量的降低而增加。在本作工作中,使用模态扩展来转换用于最小二乘最小化算法的理论故障模型负载,以减少识别的故障参数中的错误。即使在较少数量的测量振动的情况下,也可以精确地识别裂缝。使用横向振动将该方法应用于离心泵转子中的裂纹识别。呈现的结果纯粹从有限元模拟获得。

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