The Open Mechanical Engineering Journal
2014, 8 : 861-864Published online 2014 December 31. DOI: 10.2174/1874155X01408010861
Publisher ID: TOMEJ-8-861
Fault Classification of Rolling Bearing Based on Time-Frequency Generalized Dimension of Vibration Signal and ANFIS
School of Electric Multiple
Units Engineering, Dalian Jiaotong University, No.794, Huanghe road,
Shahekou District, Dalian, Liaoning province, 116028, China.
ABSTRACT
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.