基于非线性系统频谱分析的轴承早期微小故障检测

随着机械设备的不断发展，滚动轴承作为重要的机械零部件在各种工业设备中广泛应用。然而，由于工作条件的恶劣和长时间的使用，滚动轴承会逐渐出现各种缺陷和故障，影响设备的正常运行，甚至导致机器损坏和生产线停滞。因此，对滚动轴承的状态进行检测和诊断至关重要。对轴承进行定期维修是传统的做法，但这种方法不仅耗费时间和人力，而且可能会错过轴承早期微小故障的发生。本文旨在研究一种基于非线性系统频谱分析的轴承早期微小故障检测方法。
首先，建立了二自由度的轴承动力学模型。针对工业界重要部件的轴承缺乏故障信号样本的问题，研究了轴承的接触刚度、波纹度和Hertz 接触力对其运动的影响。随后分别对正常运行和有局部缺陷的轴承进行了仿真实验，与西储大学的试验台架获得的实际振动信号做了对比，特征频率是相似的，验证了所建立的轴承动力学模型是准确的，为轴承故障检测提供可靠的依据。
接着，根据轴承运动过程是具有正弦输入的非线性系统的特性，提出了一种基于多频正弦输入的轴承故障检测方法。第一步研究了非线性系统的特性，阐述了其输入和输出具有概周期函数的特性。第二步，利用输入频率和输出频率间的混合整数关系，得到输出信号在关键频率上的能量总和，从而减弱噪声对信号的影响，强化信号的能量。然后，使用基于周期图的渐近局部故障检测方法，将故障检测问题转化为假设检验问题，并通过给定的置信度和特定频率矩阵的自由度获得阈值。通过仿真结果的验证，证明该方法能够在强噪声环境下有效快速地检测早期小故障。
最后，提出了一种方法来解决输入频率未知的轴承故障检测问题，该方法可有效提取轴承互调正弦信号，从而实现故障检测。当考虑到轴承打滑时，其各部件间的角速度关系无法直接确定，这意味着输入频率也是未知的。首先，采用周期图法初步估计输出频率向量，然后构建互调结构，并利用输入输出频率间的关系矩阵估计出互调参数矩阵，最终可以精确估计出输入频率。完成输入输出频率的估计后，可以采用基于多频正弦输入的轴承故障检测方法进行故障检测。仿真结果证明，该方法准确地估计了输入输出频率，同时也验证了轴承故障检测的有效性。

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