首页> 外文会议>ASME International Mechanical Engineering Congress and Exposition >AN EIGENSYSTEM REALIZATION ALGORITHM FOR MODAL PARAMETER IDENTIFICATION OF A VERTICAL-SHAFT HIGH-SPEED CENTRIFUGAL MACHINE
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AN EIGENSYSTEM REALIZATION ALGORITHM FOR MODAL PARAMETER IDENTIFICATION OF A VERTICAL-SHAFT HIGH-SPEED CENTRIFUGAL MACHINE

机译:垂直轴高速离心机模态参数识别的Eigensystem实现算法

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In this paper, we utilize the observer/Kalman filter identification (OKID) and the eigensystem realization algorithm (ERA) techniques to identify the modal parameters of a centrifugal machine. To this end, we me an experimental setup to generate a pseudo-impulse input and collect output measurements which are corrupted by noise. We use the pseudo-impulse input and the OKID to find the Markov parameters of the system. Then we form the Hankel matrix of the system and determine the singular values of the system. A minimum-order, state-space model of the system is realized through the Markov parameters and then the natural frequency, damping ratio, mode shapes, and modal amplitudes at the sensor location are estimated by the ERA. We find three models for three separate cases and validate all the three identified models with the measured data and the Waterfall plot. The identified models are useful for designing passive or active vibration suppression control and fault detection systems. The results confirm that OKID/ERA is a reliable time-domain method for identifying the modal parameters of vertical centrifuge machines.
机译:在本文中,我们利用观察者/卡尔曼滤波器识别(OKID)和Eigensysy实现算法(ERA)技术来识别离心机的模态参数。为此,我们是一个实验设置,以产生伪脉冲输入并收集因噪声损坏的输出测量。我们使用伪脉冲输入和OKID来找到系统的Markov参数。然后我们形成系统的Hankel矩阵并确定系统的奇异值。通过Markov参数实现系统的最小阶状态 - 空间模型,然后通过Markov参数实现了传感器位置的自然频率,阻尼比,模式形状和模态幅度。我们发现三种型号为三个单独的情况,并使用测量的数据和瀑布图验证所有三个识别的模型。所识别的模型对于设计被动或有源振动抑制控制和故障检测系统是有用的。结果证实OkId / ERA是用于识别垂直离心机的模态参数的可靠时域方法。

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