Fault recognition method of rolling bearings based on volterra series and HMM

摘要：

A new bearing fault recognition method based on volterra series and HMM is proposed.In the proposed method,first the feature vectors are extracted from amplitude demodulated signals obtained from normal,ball,inner and outer faulty bearings.The feature vectors are based on the volterra series of the vibration signals,which is obtained by the subspace method.Then these feature vectors are input to each faults HMM to be recognized.The result of experiment shows that the proposed method is very effective.The proposed method is tested with the experiment data sampled from drive end ball bearing of an induction motor driven mechanical system.

关键词： Volterra series Hidden Markov Model(HMM) Subspace Fault recognition

作者: Jiang Jing Li Zhinong

作者单位: School of Mechanical Engineering,ZhengZhou University,ZhengZhou 450001,China

会议类型: 国际会议

会议名称: The 8th International Conference on Damage Assessment of Structures(DAMAS 2009)(第八届结构损伤评价国际学术会议)

会议地点: 北京

会议语种:英文

页码: 561-567

在线出版日期: 2009-08-03（万方平台首次上网日期，不代表论文的发表时间）