Fault Diagnosis of Planetary Gear System Based on Nonlinear Time-varying Dynamic Model Analysis

Yinghui Liu, Huibo Zhang, Dong Zhen, Hao Zhang, Zhanqun Shi, Fengshou Gu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Planetary gear trains are widely equipped in wind turbines and often run under bad conditions. Gear as a key part of the transmission system in wind turbines, its failure often occurs. However, the incipient gear faults can hardly be detected and may cause tremendous loss. To better detect the incipient gear faults, a nonlinear time-varying dynamic model is established. Based on this dynamic model, the modulation laws of vibration signal are analyzed by comparing the meshing force spectrums in both health and fault conditions. The amplitude modulation and frequency modulation of the gear meshing force spectrum are analyzed and the effect of overlap ratio on the vibration of the sun is also studied. By introducing the manufacturing errors at all sun-planet and ring-planet gear meshes, the amplitude modulation and frequency modulation of the gear meshing force spectrum are analyzed. In order to better simulate the actual vibration signal, the effect of the force transmission path that varies as the carrier rotates is considered in this model.

Conference

Conference25th IEEE International Conference on Automation and Computing
Abbreviated titleICAC 2019
CountryUnited Kingdom
CityLancaster
Period5/09/197/09/19
Internet address

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