A Research Of The Fault Diagnosis For Rolling Bearing Based On The Time-varying Non-stationary Time Series Analysis

The research on failure diagnosis of rolling bearings, which are the most ordinary parts in mechanical equipments, is very significant. The running state of the bearings will influence the performance of the whole machine directly. Vibration signals of rolling bearings contain rich failure information, and the necessary monitoring equipment is relatively simple, meanwhile the signal analysis technology is more mature. The research is based on the analysis of vibration signals. The fault principle and the fault vibration property are analyzed. The methods of vibration signal analysis and fault diagnosis of the rolling bearing are also introduced. The application of time series analysis used in failure diagnosis of rolling bearings is mainly researched.The time-varying non-stationary time series analysis method is used to adapt to analyze non-stationary signal from outside surface. The principle of time series analysis is introduced simply. The parameter estimation, order determining, model building of ARMA model and ARIMA model are researched. The possibility of the application of using time-varying non-stationary time series to analysis the fault diagnosis for rolling bearing is researched.Experimental project are designed and variety vibration signals are collected on the experiment table. Time domain analysis, frequency domain analysis time-frequency analysis and time series analysis are used to analyze the signals.