摘要
齿轮一旦发生断齿故障,就会产生周期性冲击,从而使啮合振动信号产生调制现象。有效提取调制信息,对于齿轮断齿故障的诊断至关重要。针对断齿故障特征信号被噪声淹没、滤波参数通常需要人为设定、断齿故障检出率低的问题,提出了一种改进的边带乘积谱算法(ISPS),以及基于IHPS/ISPS的自适应滤波与Hilbert变换解调相结合的齿轮断齿故障诊断方法。试验证明,该方法能有效分离被噪声淹没的故障特征信号,对于齿轮断齿故障的诊断,具有较大的应用价值。
Once the gear has broken tooth, there will be periodic shocks, which make the vibration signal of gear meshing modulated. So it is important for diagnosis of gear tooth broken to extract the modulation information effectively. Aiming at the problems that the fault signature is drowned by noise, the filtering parameters usually need to be set artificially, and the detection rate of tooth broken is low, this paper proposes Improved Sideband Product Spectrum(ISPS),and a diagnosis method for gear tooth broken by combining adaptive filtering on IHPS/ISPS and Hilbert transform demodulation. Experiments show that this method can effectively extract the fault characteristic signal buried by noise and has great application value for the diagnosis of tooth broken.
作者
陶九志
黄润华
马卫平
TAO JiuZhi;HUANG RunHua;MA WeiPing(Zhengzhou Research Institute of Mechanical Engineering,Co.,Ltd.,Zhengzhou 450052,China)
出处
《机械强度》
CAS
CSCD
北大核心
2021年第6期1303-1308,共6页
Journal of Mechanical Strength
