Fault diagnosis of rolling bearings using weighted horizontal visibility graph and graph Fourier transform
Fault diagnosis of rolling bearings using weighted horizontal visibility graph and graph Fourier transform
复制标题
利用加权水平可视性图和图傅立叶变换进行滚动轴承故障诊断
DOI：
10.1016/j.measurement.2019.107036
复制
发表时间：
2020-01-01
期刊：
影响因子：
5.6
通讯作者：
Wang, Haojiang
中科院分区：
文献类型：
--
作者：
Gao, Yiyuan;Yu, Dejie;Wang, Haojiang
图形傅里叶变换(GFT)已被证明是一种有效的滚动轴承脉冲分量提取工具，但其性能与底层图形的结构密切相关。与加权路径图相比，加权水平可见度图(WHVG)更能反映振动信号的动力学特性。当故障轴承振动信号被变换到WHVG时，GFT可以将大部分故障脉冲分量聚类到最高阶范围，具有很强的抗干扰性。提出了一种基于WHVG和GFT的滚动轴承故障诊断新方法。该方法首先提取最高阶谱系数重构故障脉冲分量，然后利用Hilbert包络谱对轴承故障进行诊断。仿真和实验结果表明，所提出的滚动轴承故障诊断方法具有较强的抗噪能力和较好的诊断效果。(C)2019爱思唯尔有限公司。保留所有权利。
Graph Fourier transform (GFT) has been proven to be an effective tool for impulse component extraction of rolling bearings, but its performance is closely related to the structure of underlying graph. Compared with the weighted path graph, the weighted horizontal visibility graph (WHVG) can reflect the dynamics characteristics of vibration signals better. When the fault bearing vibration signal is transformed into the WHVG, GFT can cluster most of the fault impulse component to the highest order range and has strong anti-interference ability. Based on WHVG and GFT, a novel fault diagnosis method for rolling bearings is proposed. In the proposed method, the graph spectrum coefficients in the highest order range are extracted to reconstruct the fault impulse component, and then the Hilbert envelope spectrum is used to diagnose the bearing fault. Simulation and experimental results demonstrate that the proposed fault diagnosis method for rolling bearings is noise tolerant and effective. (C) 2019 Elsevier Ltd. All rights reserved.