Gearbox Composite Fault Diagnosis based on MRSVD Energy Characteristic and KFCM

Haiying Liang; Xin Xu; Hongxia Pan; Zhimin Fu

doi:10.16578/j.issn.1004.2539.2019.09.022

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Gearbox Composite Fault Diagnosis based on MRSVD Energy Characteristic and KFCM

Test·Analysis | 更新时间：2022-09-24

- Gearbox Composite Fault Diagnosis based on MRSVD Energy Characteristic and KFCM
- Journal of Mechanical Transmission Vol. 43, Issue 9, Pages: 128-132(2019)
- 作者机构：
  
  1.中北大学机械工程学院，山西太原 030051
- 作者简介：
- 基金信息：
- DOI：10.16578/j.issn.1004.2539.2019.09.022
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梁海英,许昕,潘宏侠等.基于MRSVD能量特征和KFCM的齿轮箱复合故障诊断[J].机械传动,2019,43(09):128-132.

Liang Haiying,Xu Xin,Pan Hongxia,et al.Gearbox Composite Fault Diagnosis based on MRSVD Energy Characteristic and KFCM[J].Journal of Mechanical Transmission,2019,43(09):128-132.
梁海英,许昕,潘宏侠等.基于MRSVD能量特征和KFCM的齿轮箱复合故障诊断[J].机械传动,2019,43(09):128-132. DOI： 10.16578/j.issn.1004.2539.2019.09.022.

Liang Haiying,Xu Xin,Pan Hongxia,et al.Gearbox Composite Fault Diagnosis based on MRSVD Energy Characteristic and KFCM[J].Journal of Mechanical Transmission,2019,43(09):128-132. DOI： 10.16578/j.issn.1004.2539.2019.09.022.

摘要

针对齿轮箱复合故障信号成分复杂和故障特征难以识别的问题，提出基于多分辨奇异值分解（MRSVD）能量特征和模糊核聚类（KFCM）的齿轮箱复合故障诊断方法。首先，采集齿轮箱不同工况下的振动信号，通过进行MRSVD分解得到1个相似信号和5个细节信号；然后，提取6个分量信号的能量特征并进行归一化处理，得其能量相对值；最后，使用KFCM进行故障诊断。实验结果表明，MRSVD能量特征提取方法可有效提取齿轮箱复合故障特征，且KFCM可准确诊断齿轮箱复合故障。

Abstract

A composite gearbox fault diagnosis method based on multi-resolution singular value decomposition (MRSVD) energy characteristic and fuzzy kernel clustering (KFCM) is proposed for the complex fault signal components of the gearbox and the difficulty in identifying fault characteristic. Firstly, the vibration signal of the gearbox under different working conditions is acquired to obtain a similar signal and five detail signals by performing MRSVD decomposition. Then, the energy characteristic of the six component signals are extracted and normalized to obtain the relative value of the energy. Finally, KFCM is used for fault diagnosis. The experimental results show that the MRSVD energy characteristic extraction method can effectively extract the composite fault characteristic of the gearbox, and KFCM can accurately diagnose the gearbox composite fault.

关键词

齿轮箱多分辨奇异值分解能量特征模糊核聚类故障诊断

Keywords

GearboxMRSVDEnergy characteristicKFCMFault diagnosis

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