Fault Diagnosis of Hoist Gearbox Based on Time-Domain Analysis of EMD and Fuzzy Clustering

摘要：

In this paper, the method of combining the timedomain analysis of empirical mode decomposition (EMD) and fuzzy clustering is explored for the hoist gearbox fault diagnosis. Firstly, it adopts the EMD technique to decompose the signal of vibration. With it, any complicated dataset can be decomposed into a finite and often small number of intrinsic mode functions (IMFs). Then a number of IMFs containing main fault information were selected, from which time domain feature parameters--variance and kurtosis coefficient were extracted. At last, fuzzy clustering is used to diagnose and identify the kind of fault. The numerical simulation and the analysis of the response signal data from the hoist gearbox show that the method is effective at discriminating the three condition of the gear, i.e. the normal, surface fatigue pitting and cracked tooth.

关键词： Time-domain analysis of EMD Variance and kurtosis Fuzzy clustering Gearbox Fault diagnosis

作者: Zigui LI Bijuan YAN

作者单位: Taiyuan university of science and technology, Taiyuan, Shanxi, China

会议类型: 国际会议

会议名称: 2011 International Conference on Mechatronics and Materials Processing(2011年机电一体化与材料加工国际会议 ICMMP)

会议地点: 广州

会议语种:英文

页码: 1717-1720

在线出版日期: 2011-11-18（万方平台首次上网日期，不代表论文的发表时间）