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A positive energy residual (PER) based planetary gear fault detection method under variable speed conditions

机译:变速条件下基于正能量残差(PER)的行星齿轮故障检测方法

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摘要

Most existing studies on vibration-based fault detection for planetary gears were developed and tested under constant speed conditions. Recently, some methods were developed to consider the variability of the rotating speed; however, these methods have limitations. Specifically, these methods are applicable only for small fluctuations of speed, or the methods require additional angular information as an input. This paper thus proposes a new method, the positive energy residual (PER) method, for fault detection of planetary gears. PER does not require the assumption of only small fluctuations of speed, nor does it need angular information. The proposed PER algorithm is based on two techniques, the wavelet transform (WT) and the Gaussian process (GP), which are used to remove the variability of the signals while extracting the faulty signals. Further, a fault feature is presented that is able to effectively quantify the characteristics of faulty signals. The performance of the proposed method is demonstrated using two case studies: vibration signals from a simulation model and vibration signals from a real test-bed. A comparison study with other methods, WT and energy residual (ER), is also presented to clarify the performance of the proposed PER algorithm. From the results, we conclude that the proposed PER method is capable of detecting faults of a planetary gear under variable speed conditions, while showing better performance than the two other methods. (C) 2018 Elsevier Ltd. All rights reserved.
机译:现有的有关基于齿轮的基于振动的故障检测的大多数研究都是在恒速条件下进行的,并进行了测试。最近,开发了一些方法来考虑转速的变化。但是,这些方法有局限性。特别地,这些方法仅适用于速度的小波动,或者这些方法需要附加的角度信息作为输入。因此,本文提出了一种新的方法,即正能量残差(PER)方法,用于行星齿轮的故障检测。 PER不需要仅假设速度的微小波动,也不需要角度信息。提出的PER算法基于小波变换(WT)和高斯过程(GP)两种技术,用于在提取故障信号时去除信号的可变性。此外,提出了一种故障特征,其能够有效地量化故障信号的特征。通过两个案例研究证明了所提出方法的性能:来自仿真模型的振动信号和来自真实测试台的振动信号。还提出了与其他方法(WT和能量残差(ER))的比较研究,以阐明所提出的PER算法的性能。从结果可以得出结论,提出的PER方法能够在变速条件下检测行星齿轮的故障,同时表现出比其他两种方法更好的性能。 (C)2018 Elsevier Ltd.保留所有权利。

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