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Dynamic Signal Interpretation of Rotary Machines Using Adaptive Order Tracking

机译:使用自适应阶次跟踪的旋转机械动态信号解释

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This paper proposes and implements an adaptive Vold-Kalman filtering order tracking (VKF_OT) approach to overcome the deficiencies of the original VKFOT scheme for condition monitoring and diagnosis of rotary machinery. This article comprises theoretical derivation, numerical implementation and experimental validation. Comparisons of the adaptive scheme to the original are accomplished through processing a synthetic signal composed of close order components. Parameters such as the weighting factor and the correlation matrix of process noise, which influences tracking performance, are investigated in the study. The adaptive OT scheme based on the Kalman filter can be computed on-line and implemented as a real-time processing application. This paper also illustrates experimental validation through the separation of two close orders arising from a transmission test bench.
机译:本文提出并实现了一种自适应Vold-Kalman滤波阶数跟踪(VKF_OT)方法,以克服原始VKFOT方案用于旋转机械状态监测和诊断的缺陷。本文包括理论推导,数值实现和实验验证。自适应方案与原始方案的比较是通过处理由近阶分量组成的合成信号来完成的。研究了影响跟踪性能的参数,例如加权因子和过程噪声的相关矩阵。可以在线计算基于卡尔曼滤波器的自适应OT方案,并将其实现为实时处理应用程序。本文还说明了通过将传输测试台架上的两个关闭订单分开来进行的实验验证。

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