Fault Classify of Rolling Bearing Based on Time-frequency Generalized Dimension of Vibration Signal and ANFIS

摘要：

　　Research shows that multi-fractal can not only exhibit the singular probability distribution form of the fractal signal completely,but also increase the fine level of signal geometrical characteristics and local scaling behavior.Based on multi fractal dimension calculation of time frequency matrix of vibration signal of rolling bearing in this paper,energy distribution characteristics of time-frequency domain of vibration signal could be extracted,then adaptive fuzzy neural network(ANFIS)was used in signal classification.Experiments showed that this method can realize fault classify of rolling bearing effectively,it is feasible in engineering application.

关键词： multi-fractal vibration time frequency matrix classify

作者: Li Fang

作者单位: School of Electric Multiple Units Engineering,Dalian Jiaotong University Dalian116028,China

会议类型: 国际会议

会议名称: 2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference(ITOEC2017)(2017 IEEE 第3届信息技术与机电一体化工程国际学术会议)

会议地点: 重庆

会议语种:英文

页码: 681-684

在线出版日期: 2017-10-03（万方平台首次上网日期，不代表论文的发表时间）