DSP-base adaptive angular-velocity VKF order tracking for online real-time monitoring system

Ting-Chi Yeh, M. Pan, Cheng-Yi Ho
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引用次数: 0

Abstract

Mechanical systems under periodic loading due to rotary operation usually respond in measurements with a superposition of sinusoids whose frequencies were integer or fractional integer multiples of the reference shaft speed. When the rotary machines are running, acousto-mechanical signals acquired from the machines enable to reveal their operation status and machine conditions. The study proposed a DSP-based adaptive angular-velocity Vold-Kalman filtering order tracking (AV2KF_OT) algorithm with online real-time nature for signal interpretation and machine condition monitoring. Theoretical derivation and numerical implementation of the computation scheme was briefly introduced. An online real-time condition monitoring system based on the AV2KF_OT algorithm, which was implemented through both a digital signal processor (DSP) and a man-machine interface coded by using LabVIEW®, was developed. An experimental task, the startup detection on the fluid-induced whirl performed through a journal-bearing rotor rig, was used to justify the proposed technique.
基于dsp的自适应角速度VKF阶次跟踪在线实时监测系统
由于旋转操作而受到周期性载荷的机械系统,通常在测量中以频率为参考轴转速的整数或分数整数倍的正弦波的叠加响应。当旋转机械运行时,从机器上采集声机械信号,可以显示机器的运行状态和机器状况。提出了一种基于dsp的具有在线实时性的自适应角速度Vold-Kalman滤波阶数跟踪(AV2KF_OT)算法,用于信号解释和机器状态监测。简要介绍了计算方案的理论推导和数值实现。开发了基于AV2KF_OT算法的在线实时状态监测系统,该系统通过数字信号处理器(DSP)和LabVIEW®编码的人机界面实现。通过轴向轴承转子装置进行的流体诱导旋涡启动检测实验验证了该方法的正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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