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Instantaneous speed jitter detection via encoder signal and its application for the diagnosis of planetary gearbox

机译:编码器信号瞬时速度抖动检测及其在行星齿轮箱诊断中的应用

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摘要

In modern rotating machinery, rotary encoders have been widely used for the purpose of positioning and dynamic control. The study in this paper indicates that, the encoder signal, after proper processing, can be also effectively used for the health monitoring of rotating machines. In this work, a Kurtosis-guided local polynomial differentiator (KLPD) is proposed to estimate the instantaneous angular speed (IAS) of rotating machines based on the encoder signal. Compared with the central difference method, the KLPD is more robust to noise and it is able to precisely capture the weak speed jitters introduced by mechanical defects. The fault diagnosis of planetary gearbox has proven to be a challenging issue in both industry and academia. Based on the proposed KLPD, a systematic method for the fault diagnosis of planetary gearbox is proposed. In this method, residual time synchronous time averaging (RTSA) is first employed to remove the operation-related IAS components that come from normal gear meshing and non-stationary load variations, KLPD is then utilized to detect and enhance the speed jitter from the IAS residual in a data-driven manner. The effectiveness of proposed method has been validated by both simulated data and experimental data. The results demonstrate that the proposed KLPD-RTSA could not only detect fault signatures but also identify defective components, thus providing a promising tool for the health monitoring of planetary gearbox.
机译:在现代旋转机械中,旋转编码器已广泛用于定位和动态控制。本文的研究表明,编码器信号经过适当处理后,也可以有效地用于旋转机械的健康监测。在这项工作中,提出了一种由峰度指导的局部多项式微分器(KLPD)来基于编码器信号估计旋转机械的瞬时角速度(IAS)。与中心差分法相比,KLPD对噪声更鲁棒,并且能够精确捕获由机械缺陷引起的微弱速度抖动。在工业界和学术界,行星齿轮箱的故障诊断已被证明是一个具有挑战性的问题。基于提出的KLPD,提出了一种行星齿轮箱故障诊断的系统方法。在这种方法中,首先采用剩余时间同步时间平均(RTSA)来消除来自正常齿轮啮合和非平稳负载变化的与操作相关的IAS组件,然后使用KLPD检测并增强IAS的速度抖动以数据驱动的方式残留。仿真数据和实验数据均验证了该方法的有效性。结果表明,提出的KLPD-RTSA不仅可以检测故障特征,还可以识别有缺陷的组件,从而为行星齿轮箱的健康监测提供了有希望的工具。

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