Modeling and Forecasting of the Vibration Signal Based on ARMA Model
A novel time series analysis is presented to analyze and forecast nonlinear random vibration signals. Mathematical models are established to describe vibration signals. First, the non-stationary vibration signals acquired in the field are transformed to stationary time series. Second, the time series models are constructed from the selected reference signals, and nonlinear least square method is used to estimate the models parameters. Then, the vibration signals are forecasted using the models. The application results show that the models can simulate time series of vibration signals quite well with good accuracy and meet the need of forecasting.
ARMA model forecast parameter estimation
Cao Xin-Yan Li Meng
College of Electronic Information Engineering University of Changchun Changchun, Jilin Province, Chi College of Mechanical Engineering University of Changchun Changchun, Jilin Province, China
国际会议
长春
英文
9-12
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）