基于时间多重同步挤压W变换的高精度轴承故障诊断
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作者单位:

1.中国石化胜利油田分公司 技术检测中心;2.成都理工大学数理学院

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中图分类号:

TH133.3;TH165.3

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油气藏地质及开发工程国家重点实验室开放基金(PLC2021100)


High-precision fault diagnosis of bearings based on time multi-synchrosqueezing W transform
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Technical Inspection Center,Sinopec Shengli Oilfield Company

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    摘要:

    状态监测(condition monitoring, CM)信号中的脉冲特征通常意味着旋转机器中存在缺陷。为了准确捕获CM信号中的脉冲分量,提出了一种高精度的时间多重同步挤压W变换(TMSSWT)用于提高CM信号的时频聚焦性能。该算法首先利用W变换(WT)获取信号的时频表征结果,然后在时频域上构建估计信号真实群延迟(group delay, GD)的时频后处理表征算子——“挤压算子”,从而对原始W变换得到的时频谱能量进行“挤压”操作;其次,利用不动点的迭代算法将时频能量重新排列至信号真实的GD脊线上;最后利用信号重构的脉冲特征提取算法,计算时频包络,对TMSSWT获得的时频谱提取最强振幅对应频率的脉冲特性,通过对比脉冲特性的时间间隔识别轴承故障。模拟信号结果很好地证实了该方法可以有效地提高时频能量聚焦性,以期在实际故障诊断应用中可以准确地捕获脉冲特征,更好的识别与诊断轴承机械故障。

    Abstract:

    It is usually indicated a defect in the rotating machine by the impulse features in the condition monitoring (CM)signals. To accurately capture the impulse components in the CM signal, this paper proposes a high-precision time-reassigned multi-synchrosqueezing W transform (TMSSWT), which improves the time-frequency concentration performance of the CM signal. The algorithm first uses the W transform (WT) to obtain the time-frequency representation result of the signal, and then constructs a time-frequency post-processing operator - “synchrosqueezing” operator to estimate the group delay(GD)of the signal in the time-frequency domain, thus performing a "squeeze" operation on the time-spectrum energy obtained from the original WT. Secondly, a fixed-point iterative algorithm is used to reallocate the time-frequency energy to the real GD ridge of the signal. Finally, we employ the impulse feature extraction algorithm of signal reconstruction to calculate the time-frequency envelope and then extract the impulse characteristics of the frequency corresponding to the strongest amplitude from the time-frequency spectrum obtained by TMSSWT. By comparing the time interval of impulse characteristics, the bearing fault can be identified. It is well proved that the proposed method can effectively improve the time-frequency energy concentration through the results of simulated signal, in order to accurately capture the impulse characteristics in the actual fault diagnosis application, and better identify and diagnose the mechanical fault bearing.

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和虎,赵金刚,彭露,等. 基于时间多重同步挤压W变换的高精度轴承故障诊断[J]. 科学技术与工程, , ():

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  • 收稿日期:2021-12-14
  • 最后修改日期:2022-04-19
  • 录用日期:2022-04-30
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