Firstly

the boundary values of exhaust gas temperature(teg) was extracted from the original exhaust gas temperature data series.Further analysis on the boundary values data series indicated that there existed a chaos feature in it.Then

chaotic forecasting arithmetic based on multivariable phase space reconstruction was established to forecast the data series.Finally

by comparing the series with the red line

the condition of aero-engine was defined.The proposed arithmetic was verified through some type of aircraft aero-engine teg data series obtained from actual flight.The result shows that the proposed arithmetic can reduce the time complexity and has a better forecast accuracy in the prediction of outliers.It can be used as a supporting model in the decision making of this aero-engine fault forecast.