时间序列自回归滑动平均模型(Autoregressive Integrated Moving Average Model,ARIMA)能较准确处理和预测依循环顺序获得的航空发动机性能数据.采用分箱改进的拉伊达准则处理起飞EGTM数据,可为ARIMA模型提供了更加真实的数据,获得航空发动机起飞EGTM预测值,依据航空公司发动机设定的可靠度进行下发预测.应用验证表明:基于ARIMA的起飞EGTM时间序列能够满足航空发动机的质量管理的要求.“,”Autoregressive Integrated Moving Average time series Model (ARIMA) can accurately predict the civil aviation engine performance data collected in a cyclical order.The paper adopts the binned Pauta Criterion to process take-off EGTM data which can provide more realistic data for the ARIMA model,obtains the prediction of aero-engine take-off EGTM,and predicts civil aviation engine removal date accurately based on the reliability set by the airline engine.It is shown by an application example verification that prediction of civil aviation engine removal date based on ARIMA model meets the requirements of civil aviation engine quality management.