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针对变转速下齿轮箱复合故障的故障特征提取,提出了基于形态分量分析与阶次跟踪的齿轮箱复合故障诊断方法.该方法根据齿轮箱复合故障振动信号中齿轮和滚动轴承故障成分的形态差异性,先用形态分量分析将其分解为包含齿轮局部故障信息的谐振分量、包含滚动轴承局部故障信息的冲击分量和随机噪声分量,再根据实测转速信号分别对谐振分量和冲击分量进行包络阶次分析,根据各包络阶次谱诊断齿轮箱复合故障.算法仿真和应用实例表明:该方法能有效分离变转速下齿轮和滚动轴承的故障特征,且其故障特征提取效果要优于传统的包络阶次谱方法.
Aiming at the fault feature extraction of compound gear box under variable speed, a compound gearbox fault diagnosis method based on morphological component analysis and order tracking is proposed. According to the difference of gearbox and rolling bearing fault components in gearbox compound fault signal Firstly, the morphological component analysis is used to decompose it into the harmonic components containing the local fault information of the gear, including the impact component and the random noise component of the local fault information of the rolling bearing. Then the envelope and order components of the resonance component and the impact component are respectively analyzed according to the measured rotational speed signal , And diagnoses the gearbox compound fault according to the envelope order spectra.The simulation and application examples show that this method can effectively separate the fault features of gear and rolling bearing under variable speed and the fault feature extraction effect is better than the traditional envelope order Sub-spectrum method.