An algorithm to remove noise from locomotive bearing vibration signal based on self-adaptive EEMD filter

作者：Wang Chun-sheng^*; Sha Chun-yang; Su Mei; Hu Yu-kun

来源：Journal of Central South University, 2017, 24(2): 478-488.

DOI：10.1007/s11771-017-3450-8

• locomotive bearing
• vibration signal enhancement
• self-adaptive EEMD
• parameter-varying noise signal
• feature extraction

An improved ensemble empirical mode decomposition (EEMD) algorithm is described in this work, in which the sifting and ensemble number are self-adaptive. In particular, the new algorithm can effectively avoid the mode mixing problem. The algorithm has been validated with a simulation signal and locomotive bearing vibration signal. The results show that the proposed self-adaptive EEMD algorithm has a better filtering performance compared with the conventional EEMD. The filter results further show that the feature of the signal can be distinguished clearly with the proposed algorithm, which implies that the fault characteristics of the locomotive bearing can be detected successfully.

• 出版日期2017-2
• 单位中南大学