Bearing fault diagnosis based on TEO and SVM

摘要：

　　A fault method for bearing based on Teager energy operator (TEO) and support vector machine (SVM) is proposed in this paper.First, the total energy of the vibration signal of the bearing is estimated by the TEO technique, which has good time resolution for the instantaneous signal.Then, the Teager spectrums are obtained by applying fast Fourier transform (FFT) to the Teager energy signal.The feature frequencies of different fault modes, as well as the ratio of resonance frequency band energy to total energy in the Teager spectrum are extracted to form the feature vectors.Finally, these vectors are introduced into SVM to realize fault classification for the bearing.Experiments are conducted to verify the feasibility of the proposed method, the results show that the proposed method performs effectively to identify the failure mode of the bearing under variable conditions.

关键词： fault diagnosis bearing TEO SVM FFT

作者: Oingzhu Liu Yujie Cheng

作者单位: School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China Science and Technology on Reliability and Environmental Engineering Laboratory, Beijing 100191, Chin

会议类型: 国际会议

会议名称: the International Conference Vibroengineering-2014

会议地点: 贵阳

会议语种:英文

页码: 206-210

在线出版日期: 2014-11-07（万方平台首次上网日期，不代表论文的发表时间）