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Detection of Impulsive Fault Signal by Cumulant Maximisation

机译:通过累积最大化检测脉冲故障信号

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Classical deconvolution methods for source identification following linear filtering can only be used if the transfer function of the system is known. For many practical situations, however, this information is not accessible and/or is time varying. The problem addressed here is that of reconstruction of the original input from only the measured signal. This is known as 'blind deconvolution'. By using Higher Order Statistics (HOS), the restoration of the input signal is established through the maximisation of higher order moments (cumulants) with respect to the characteristics of the signals concerned. This restoration is achieved by constructing an inverse filter considering the choice of the initial inverse filter type. As a practical application, an experimental verification is carried out for the restoration of our impacting signal arising in the response of a cantilever beam with an end stop when randomly excited.
机译:如果已知系统的传递函数,则只能使用源识别的源识别的古典解卷积方法。然而,对于许多实际情况,该信息无法访问和/或时间变化。这里解决的问题是从测量信号中重建原始输入的问题。这被称为“盲目解构”。通过使用更高阶统计(HOS),通过关于所涉及的信号的特性,通过高阶矩(累积分子)的最大化建立输入信号的恢复。考虑到初始逆滤波器类型的选择来构建逆滤波器来实现该恢复。作为实际应用,进行实验验证,用于恢复我们在随机兴奋的悬臂梁响应时产生的撞击信号引起的撞击信号。

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