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利用时间序列算法,对飞机空调系统故障进行预测研究。该算法基于数据处理后集成到SAS系统中的飞机空调系统故障序列,利用SAS/ETS模块相应命令检验该序列为平稳非白噪声序列,在此基础上对有限多个模型进行相对最优化选择后构建自回归移动平均(ARMA)预测模型。最后,将该模型应用于某型飞机空调系统故障实证研究及短期预测中,分析结果表明,该方法在飞机空调系统故障短期预测中的效果良好。
The use of time series algorithm for aircraft air conditioning system failure prediction. Based on the fault sequence of aircraft air conditioning system integrated into SAS system after data processing, this algorithm verifies the sequence as a stationary non-white noise sequence by using the corresponding commands of SAS / ETS module. Based on this, after relatively optimal selection of a limited number of models Construct autoregressive moving average (ARMA) forecasting model. Finally, the model is applied to the empirical research and short-term prediction of the fault of a certain type of aircraft air conditioning system. The analysis results show that the proposed method is effective in the short-term prediction of aircraft air conditioning system failures.