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首页> 外文期刊>Measurement >Automatic quantitative diagnosis for rolling bearing compound faults via adapted dictionary free orthogonal matching pursuit
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Automatic quantitative diagnosis for rolling bearing compound faults via adapted dictionary free orthogonal matching pursuit

机译：自动定量诊断滚动轴承复合故障通过调整字典自由正交匹配追求

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摘要

Vibration signals of rolling bearings can reflect not only the concrete faulty component, but also the faulty status, e.g., the severity. Motivated by the fault status assessment, a sparse step-impact characteristic-oriented quantitative diagnosis method is developed for the automatic size estimations of compound faults. First, based on the excitation mechanism of bearing step-impact signals, a right-angle quadrilateral model is established for size estimation. Then the linear time-invariant (LTI) filter and autoregressive model (AR model) are used to pre-process the original fault signal. Technically supported by the adapted dictionary free orthogonal matching pursuit (ADOMP), through correlating the Asymmetric Gaussian Chirplet Model (AGCM) atoms and bearing signals, the location of step-impact points are parameterized and the selection strategy for the most suitable AGCM atoms are also investigated, guaranteeing the successful separation of severe and slight fault step-impact components. Finally, the estimations for compound fault sizes are automatically realized via combining the time shift factors of AGCM atoms and proposed right-angle quadrilateral model. The simulated result shows that the proposed right-angle quadrilateral model and quantitative diagnosis method can be reliably applied to the automatic estimations of compound fault sizes. The experimental results show that, the estimation deviations for compound sizes (2.5 mm and 1.0 mm) come only to 1.61% and 6.49% at 300r/min, respectively, superior to Symlet5 wavelet decomposition. Furthermore, the proposed method is applied to the quantitative analysis at different speeds and compound fault sizes, and the satisfactory diagnosis results are obtained. (C) 2020 Elsevier Ltd. All rights reserved.
机译：滚动轴承的振动信号不仅可以反映混凝土故障的部件，而且还可以反映出故障状态，例如严重程度。通过故障状态评估的动机，开发了一种稀疏的阶梯 - 撞击特性定量定量诊断方法，用于复合故障的自动尺寸估计。首先，基于轴承阶跃冲击信号的激励机制，建立了右角四边形模型以进行尺寸估计。然后，线性时间不变（LTI）滤波器和自回归模型（AR模型）用于预处理原始故障信号。通过技术支持的字典自由正交匹配追求（ADOMP），通过关联非对称高斯啁啾模型（AGCM）原子和轴承信号，阶跃冲击点的位置是参数化的，并且最合适的AGCM原子的选择策略也是如此调查，保证成功分离严重和轻微的故障阶跃抗冲组件。最后，通过组合AGCM原子的时间换档因子和提出的直角四边形模型来自动实现复合故障尺寸的估计。模拟结果表明，所提出的直角四边形模型和定量诊断方法可以可靠地应用于复合故障尺寸的自动估计。实验结果表明，化合物尺寸（2.5mm和1.0mm）的估计偏差分别仅为300r / min的1.61％和6.49％，优于Symlet5小波分解。此外，所提出的方法应用于不同速度和复合故障尺寸的定量分析，并且获得了令人满意的诊断结果。 （c）2020 elestvier有限公司保留所有权利。

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