Reserch On Feature Extraction Of Bearing Weak Fault Based On Duffing System

Rolling bearing is one of the important parts in rotating machinery.Its running state immediately determines the working precision and working efficiency of the whole equipment.It is very important to study the early damage state of rolling bearing and to deal with different faults in time.In this paper,the responce characteristics of Duffing system under the excitation of damping force,nonlinear restoring force and periodic force are studied.According that,the effect of external periodic excitation on Duffing system is pointed out.The effects of four parameters:amplitude and frequency of external excitation,external noise and damping ratio of Duffing system on Duffing system are discussed,and the range of damping ratio is given.It is pointed out that the traditional Duffing system is only sensitive to the periodic signal with small frequency and is not suitable for engineering signal,thus coefficient p is introduced,and an improved Duffing system which makes the response spectrum of the Duffing system wider and increases its applicable range is developed.In the field of weak signal detection using Duffing system,the detection method based on phase plane change is analyzed,and the influence of frequency difference,phase difference and system state on system detection results is pointed out.By studying the variance of Duffing system response x and y with parametersρ,it is found that the ruler of maximizing the variance of Duffing system response x with the variation of parameters p can be used to detect weak periodic excitation signals.The influence of the phase difference,signal data volume and sampling frequency on the detection results of Duffing system is discussed,then the acquisition rule of signal data volume and sampling frequency is given.Taking the weak cosine signal as the weak fault signal,it is found that the signal number can improve the identification ability of duffing systemby adjusting the sampling frequency properly.By using the improved signal detection method based on Duffing system,the identification of impact signal,multi frequency component signal and bearing fault simulation signal is realized,which shows that this method can be used to identify the fault of bearing damage.In this paper,the theory of empirical wavelet transform(EWT)is researched.The simulation signal of bearing fault is decomposed by empirical wavelet transform,and the mode containing fault characteristic frequency is extracted,which improve the signal-to-noise ratio of the signal to be detected.Then the obtained characteristic mode is used to excite duffing system to realize the recognition of bearing fault simulation signal.In this paper,the above fault diagnosis method is used in the initial fault identification of a rolling bearing,which effectively detects the initial faults of the inner and outer rings of the bearing under different working conditions,thus validating the correctness of the method proposed in this paper.The detection method based on Duffing system is studied in this paper,which provides a new idea for initial fault identification of rolling bearing.