广泛用于各行各业的转子系统的稳定性问题一直倍受关注·　而在当今失稳多是由于一些非线性现象的出现所引起,这就对转子系统的设计提出了更高的要求:考虑非线性因素,避开会出现非线性现象的不稳定参数点或区域·　若仅知未知系统的系列时间序列(有可能被噪声污染),如何识别系统运动性态的变化?为了探讨此问题,在本文中通过对一单盘Jeffcott转子的研究,得出了利用随参数变化的时间序列分维数趋势图,可以很好地识别轴承_转子动力系统发生分岔时的临界参数· The stability of the rotor system that is widely used in all walks of life has drawn much attention. However, the current instability is caused mostly by the appearance of some nonlinear phenomena, which puts higher demands on the design of the rotor system. Consideration Non-linear factors to avoid unstable parameter points or regions that may appear non-linear phenomenon · How to identify the change of system motion state if only the series time series of unknown system (which may be contaminated by noise)? To explore this problem, In this paper, through the study of a single-disk Jeffcott rotor, it is concluded that using the time-series fractal dimension trend chart with parameters changes, the critical parameters in bearing-rotor dynamic system when bifurcation can be well identified