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Analytical vibration signal model and signature analysis in resonance region for planetary gearbox fault diagnosis

机译:行星齿轮箱故障诊断共振区域的分析振动信号模型及其签名分析

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Complex components and multi-modulations characterize planetary gearbox vibration signals. As the vibration signals become time-varying under nonstationary conditions, it is difficult to extract fault features around meshing frequency harmonics, since they are all dependent on speed, and change under time-varying speed conditions. To address this issue, we turn to the resonance region and exploit the time-invariability of resonance frequency and the sideband symmetry around resonance frequency for planetary gearbox fault diagnosis under both constant and time-varying speed conditions. Gear fault generates impulses and thereby excites resonance of the planetary gearbox and even the measurement system. As such, gear fault information can be explored in the resonance region. To thoroughly understand gear fault vibration features in resonance region, the vibration signal is modeled as an amplitude modulation and frequency modulation (AM-FM) process, considering the multi-modulations due to gear fault, time-varying vibration transmission path, and time-varying angle between mesh line of action and measurement axis of vibration sensor. Furthermore, explicit time-varying Fourier spectra under nonstationary conditions are derived. Sideband symmetry features around resonance frequency can be utilized to detect gear fault. This is a major progress and contribution in contrast to reported researches that focus on meshing frequency or its harmonics only. Resonance frequency identification is the key to gear fault feature extraction in resonance region. An on-line resonance frequency identification method under time-varying speeds is proposed by exploiting the nature of resonance independence of running conditions. To effectively pinpoint the time-varying sidebands in the time-frequency domain, the iterative generalized demodulation (IGD) method is used to achieve high time-frequency resolution and to avoid both outer and inner interferences at the same time. The theoretical derivations and proposed method are validated through numerical simulation and lab experiments. Gear fault features are extracted in the resonance region of the planetary gearbox and the accelerometer under time-varying speed conditions.
机译:行星齿轮箱振动信号具有复杂的部件和多种调制特性。由于振动信号在非平稳条件下是时变的,因此很难提取啮合频率谐波周围的故障特征,因为它们都依赖于速度,并且在时变速度条件下是变化的。为了解决这个问题,我们转向共振区域,利用共振频率的时间不变性和共振频率周围的边带对称性,在恒速和时变转速条件下进行行星齿轮箱故障诊断。齿轮故障会产生脉冲,从而激发行星齿轮箱甚至测量系统的共振。因此,可以在共振区域探索齿轮故障信息。为了深入了解齿轮故障共振区的振动特征,将振动信号建模为振幅调制和频率调制(AM-FM)过程,考虑了齿轮故障引起的多次调制、时变振动传播路径以及振动传感器的作用线与测量轴之间的时变角度。此外,还导出了非平稳条件下的显式时变傅里叶谱。利用共振频率附近的边带对称特征可以检测齿轮故障。与仅关注啮合频率或其谐波的报道研究相比,这是一个重大进展和贡献。共振频率识别是共振区齿轮故障特征提取的关键。利用运行条件与共振无关的特性,提出了一种时变转速下的在线共振频率识别方法。为了在时频域中有效地定位时变边带,采用迭代广义解调(IGD)方法来实现高的时频分辨率,同时避免外部和内部干扰。通过数值模拟和实验室实验验证了理论推导和提出的方法。在时变转速条件下,在行星齿轮箱和加速度计的共振区域提取齿轮故障特征。

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