Fault feature extraction of planetary gear using an optimized matching pursuit decomposition

Weigang Wen, Wei-dong Cheng
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Abstract

This paper presents a novel method for fault feature extraction of planetary gear using optimized matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of planetary gearbox. This method combined optimization algorithm, planetary gearbox vibration model, and matching pursuit to implement planet gear fault characteristic extraction. Genetic algorithm and matching pursuit were integrated to decompose the vibration sensor signals into parameterized planetary gearbox model bases. Then the parameters of model bases were composited to extract fault feature of planetary gear. Different planet gear faults were tested for verifying the presented methods in different scenarios. All results of experiment analysis demonstrated its effectiveness and reliability.
基于优化匹配追踪分解的行星齿轮故障特征提取
提出了一种基于优化匹配追踪算法的行星齿轮故障特征提取方法,并将其应用于行星齿轮箱振动传感器信号特征提取和故障诊断中。该方法将优化算法、行星齿轮箱振动模型和匹配追踪相结合,实现行星齿轮故障特征提取。将遗传算法与匹配追踪相结合,将振动传感器信号分解为参数化行星齿轮箱模型库。然后对模型库参数进行组合,提取行星齿轮的故障特征。针对不同的行星齿轮故障,在不同的场景下对所提出的方法进行了验证。实验分析结果证明了该方法的有效性和可靠性。
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