Gear faults in a transmission system generally cause impulse components in vibration signals, which is a crucial symbol for gearbox fault diagnosis. However, their related signals are often interfered or even submerged by the noisy meshing components (NMC) of gearboxes in degradation, which introduces challenges for incipient fault detection and condition monitoring. Commonly employed deconvolution-based methods attempt to design a filter to extract impulse components. However, these methods fail to address the interference issue of the NMC on deconvolution process. To overcome this limitation, this paper proposes an optimal weight impulse extraction (OWIE) methodology to suppress the NMC and highlight impulse component in vibration signal. Different from deconvolution-based methods, the proposed method locates impulses adaptively driven by waveform itself. A non-impulse part is suppressed through point-to-point removal, while impulse components are highlighted by subtracting a weighted signal from a raw signal. An iterative procedure is utilized to solve the optimal weight sequence by maximizing the kurtosis of an impulse signal. The effectiveness of the proposed OWIE is validated through a simulation case study and a run-to-failure experiment of gearboxes. Results demonstrate that the OWIE is sensitive to incipient faults and is suitable for the health condition monitoring of gearboxes.

中文翻译：

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最佳重量脉冲提取：用于初始齿轮箱状态监测的新脉冲提取方法

传动系统中的齿轮故障通常会在振动信号中产生脉冲分量，这是齿轮箱故障诊断的重要标志。然而，它们的相关信号经常受到退化齿轮箱的噪声啮合部件（NMC）的干扰甚至淹没，这给早期故障检测和状态监测带来了挑战。常用的基于反卷积的方法尝试设计滤波器来提取脉冲分量。然而，这些方法未能解决NMC对反卷积过程的干扰问题。为了克服这一限制，本文提出了一种最佳权重脉冲提取（OWIE）方法来抑制 NMC 并突出振动信号中的脉冲分量。与基于反卷积的方法不同，所提出的方法自适应地定位由波形本身驱动的脉冲。通过点对点去除来抑制非脉冲部分，同时通过从原始信号中减去加权信号来突出显示脉冲分量。利用迭代过程通过最大化脉冲信号的峰度来求解最佳权重序列。所提出的 OWIE 的有效性通过仿真案例研究和齿轮箱运行至故障实验得到验证。结果表明，OWIE 对早期故障敏感，适合齿轮箱的健康状态监测。