Wang Tianyang, Chu Fulei, Han Qinkai
Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China.
Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China.
ISA Trans. 2017 Mar;67:173-182. doi: 10.1016/j.isatra.2016.11.008. Epub 2016 Nov 25.
Identifying the differences between the spectra or envelope spectra of a faulty signal and a healthy baseline signal is an efficient planetary gearbox local fault detection strategy. However, causes other than local faults can also generate the characteristic frequency of a ring gear fault; this may further affect the detection of a local fault. To address this issue, a new filtering algorithm based on the meshing resonance phenomenon is proposed. In detail, the raw signal is first decomposed into different frequency bands and levels. Then, a new meshing index and an MRgram are constructed to determine which bands belong to the meshing resonance frequency band. Furthermore, an optimal filter band is selected from this MRgram. Finally, the ring gear fault can be detected according to the envelope spectrum of the band-pass filtering result.
识别故障信号与健康基线信号的频谱或包络谱之间的差异是一种有效的行星齿轮箱局部故障检测策略。然而,除局部故障外的其他原因也可能产生齿圈故障的特征频率;这可能会进一步影响局部故障的检测。为了解决这个问题,提出了一种基于啮合共振现象的新滤波算法。具体来说,首先将原始信号分解为不同的频带和层次。然后,构建一个新的啮合指标和一个MRgram来确定哪些频带属于啮合共振频带。此外,从这个MRgram中选择一个最优滤波带。最后,根据带通滤波结果的包络谱检测齿圈故障。