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Customized Multiwavelets for Planetary Gearbox Fault Detection Based on Vibration Sensor Signals

机译:基于振动传感器信号的定制多小波行星齿轮箱故障检测

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Planetary gearboxes exhibit complicated dynamic responses which are more difficult to detect in vibration signals than fixed-axis gear trains because of the special gear transmission structures. Diverse advanced methods have been developed for this challenging task to reduce or avoid unscheduled breakdown and catastrophic accidents. It is feasible to make fault features distinct by using multiwavelet denoising which depends on the feature separation and the threshold denoising. However, standard and fixed multiwavelets are not suitable for accurate fault feature detections because they are usually independent of the measured signals. To overcome this drawback, a method to construct customized multiwavelets based on the redundant symmetric lifting scheme is proposed in this paper. A novel indicator which combines kurtosis and entropy is applied to select the optimal multiwavelets, because kurtosis is sensitive to sharp impulses and entropy is effective for periodic impulses. The improved neighboring coefficients method is introduced into multiwavelet denoising. The vibration signals of a planetary gearbox from a satellite communication antenna on a measurement ship are captured under various motor speeds. The results show the proposed method could accurately detect the incipient pitting faults on two neighboring teeth in the planetary gearbox.
机译:行星齿轮箱具有复杂的动态响应,由于特殊的齿轮传动结构,与固定轴齿轮系相比,在振动信号中更难检测到。为了减少或避免计划外的故障和灾难性事故,已经开发出多种先进的方法来应对这一具有挑战性的任务。通过使用取决于特征分离和阈值去噪的多小波去噪使故障特征不同是可行的。但是,标准多波和固定多波不适合用于精确的故障特征检测,因为它们通常与测量信号无关。为克服这一缺点,提出了一种基于冗余对称提升方案的定制多小波构造方法。一种新颖的结合峰度和熵的指标用于选择最佳多小波,因为峰度对尖锐脉冲敏感,而熵对周期性脉冲有效。改进的邻域系数方法被引入多小波去噪中。来自测量船上卫星通信天线的行星齿轮箱的振动信号在各种电动机转速下均被捕获。结果表明,该方法可以准确地检测出行星齿轮箱两个相邻齿上的初期点蚀故障。

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