Fault diagnosis of planetary gearbox based on adaptive parameter variational mode decomposition

孙灿飞; 王友仁; 沈勇; 陈伟

doi:10.13224/j.cnki.jasp.2018.11.022

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Fault diagnosis of planetary gearbox based on adaptive parameter variational mode decomposition

更新时间：2026-07-07

- Fault diagnosis of planetary gearbox based on adaptive parameter variational mode decomposition
- Vol. 33, Issue 11, Pages: 2756-2765(2018)
- 作者机构：
  
  1. 南京航空航天大学自动化学院,南京,211106
  2. 中国航空工业集团有限公司故障诊断与健康管理技术航空科技重点实验室试验与验证中心,上海,201601
- 作者简介：
- 基金信息：
- DOI：10.13224/j.cnki.jasp.2018.11.022
  CLC：
- Published：2018
- 稿件说明：
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孙灿飞, 王友仁, 沈勇, 陈伟. 基于参数自适应变分模态分解的行星齿轮箱故障诊断[J]. 航空动力学报, 2018, 33(11): 2756-2765.

doi: 10.13224/j.cnki.jasp.2018.11.022
孙灿飞, 王友仁, 沈勇, 陈伟. 基于参数自适应变分模态分解的行星齿轮箱故障诊断[J]. 航空动力学报, 2018, 33(11): 2756-2765. DOI： 10.13224/j.cnki.jasp.2018.11.022.

doi: 10.13224/j.cnki.jasp.2018.11.022 DOI：

摘要

针对变分模态分解需要人为设定模态数量以及在强噪声情况下容易造成分解错误的问题，提出了依据功率谱密度极值点自适应确定模态数量与中心频率的参数自适应变分模态分解方法，通过信号仿真分析验证了方法的有效性。基于参数自适应变分模态分解提出了一种行星齿轮箱故障诊断方法，应用于行星齿轮箱第2级太阳轮裂纹的故障诊断，行星齿轮箱传动实验台的试验结果表明：该方法能实现振动信号准确分解，有效提取和辨别出故障特征频率，实现了在强背景噪声和微弱故障信号情况下对第2级太阳轮裂纹故障的准确诊断。

Abstract

In order to solve the problems of variational mode decomposition

including presetting parameter of mode number and failure liability in signal decomposition under the condition of strong noise

an improved method for determining the number of modal decomposition modes and the center of frequency band based on the extreme point of power spectral density was proposed. The effectiveness of the method was verified by signal simulation analysis. Based on the adaptive parameter variational mode decomposition

a fault diagnosis procedure was applied to diagnose the second level sun gear crack of planetary gearbox test platform. Test results proved that the method can accurately decompose the vibration signal

effectively extract and identify the fault characteristic frequency

and achieve accurate diagnosis of the second-stage sun gear crack fault under the condition of strong background noise and weak fault signal.

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