一种基于时间序列的环控生保系统遥测数据预测方法

A telemetry data prediction method of environmental control and life support system based on time series analysis

为实现环控生保系统在轨故障预测与健康管理,研究系统遥测数据的时间序列信息。通过预测关键遥测数据的变化趋势,实现在故障出现之前对其识别、预判。结合环控生保系统遥测数据的特点,通过AIC与BIC相结合的方法确定预测模型。运用该模型对实际工程中遥测数据进行预测验证,结果表明采用该方法对氧分压数据进行前向6点预测,预测精度可达98.2%,可为后续系统在轨故障预测与健康管理提供基础。

In order to realize on orbit fault prediction and health management of environmental control and life support system(ECLSS),time series information of telemetry data is studied.By predicting the change trend of key telemetry data,the fault can be identified and predicted before it occurs.Combined with the characteristics of telemetry data of ECLSS,the prediction model is determined by combining AIC and BIC.The model is used to predict and verify the telemetry data in practical engineering.The experimental results show that the prediction accuracy of this method can reach 98.2%when the oxygen partial pressure data is predicted forward by using this method,which can provide the basis for the subsequent system on orbit fault prediction and health management.