Fault classify of rolling bearing based on time-frequency generalized dimension of vibration signal and ANFIS
Fang Li · 2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference (ITOEC) · 2017
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.