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An FS-TAR based method for vibration-response-based fault diagnosis in stochastic time-varying structures: Experimental application to a pick-and-place mechanism

机译:基于FS-TAR的随机时变结构中基于振动响应的故障诊断方法:取放机构的实验应用

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摘要

The problem of vibration-response-based fault diagnosis, that is fault detection and identification, in stochastic time-varying structures is considered via a statistical time series method. The method is based on stochastic Functional Series Time-dependent AutoRegres-sive (FS-TAR) modelling of the structural dynamics, as well as on an appropriate statistical decision making scheme for fault diagnosis. It is an output-only method, capable of operating with a minimal number of random vibration response signals, even of limited time duration and frequency bandwidth, under normal operating conditions, and in a potentially automated way. The method is applied to the problem of fault diagnosis in a pick-and-place mechanism based on a single vibration response signal. Its performance characteristics are thus confirmed using various fault scenarios and a number of experimental test cases.
机译:通过统计时间序列方法,研究了随机时变结构中基于振动响应的故障诊断问题,即故障的检测与识别。该方法基于结构动力学的随机功能序列随时间变化的自动回归(FS-TAR)建模,以及用于故障诊断的适当统计决策方案。它是一种仅输出的方法,能够在正常操作条件下以潜在的自动化方式,以最少数量的随机振动响应信号进行操作,即使在有限的持续时间和频率带宽下也是如此。该方法应用于基于单个振动响应信号的拾放机构中的故障诊断问题。因此,使用各种故障场景和大量实验测试案例可以确认其性能特征。

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