Notice of RetractionModeling and forecasting of the vibration signal based on ARMA model

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

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 model´s 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.