主管单位:中华人民共和国工业和信息化部
主办单位:西北工业大学  中国航空学会
地       址:西北工业大学友谊校区航空楼
POD算法在飞机RAT舱温度预测中的应用研究
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中国商飞上海飞机设计研究院

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V216.5+1

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Application of POD Method for Temperature Prediction in Aircraft RAT Bay
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1.COMAC Shanghai Aircraft Design&2.Research Institute

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    摘要:

    冲压空气涡轮(RAT)系统是飞机的应急发电系统,在飞机失去主交流电源后为飞机供电,RAT平时回收在非气密区的RAT舱内,在应急工况下释放到气流中。RAT舱温度很大程度上决定了RAT的释放时间,进而影响飞机在应急工况下的安全性,RAT舱的温度预测对于应急供电下的安全性具有显著的意义。本文通过本征正交分解(POD)将RAT舱温度与高度、大气静温、飞行速度、RAT舱周围舱温度作为模型整体进行统一分析,并通过RAT舱温度简化模型及简化模型与完整模型的映射关系,预测特定工况下的RAT舱温度。本文选取试验数据作为样本数据,利用POD方法进行RAT舱温度预测,根据预测结果显示,1阶模态占据所有模态的比重超过99%。归一化处理后,预测结果的绝对平均误差最小可达到0.063,方差最小达到0.07;同时,结果显示样本数量越多,预测效果越好。

    Abstract:

    Ram air turbine (RAT) system is the emergency power generation system of the aircraft. It supplies power to the aircraft after the aircraft loses the main AC power. RAT is stowed in the RAT bay in the non air tight area normally and deployed into the air flow under emergency conditions. The temperature of the RAT bay determines the deploy time of the RAT, thus affecting the safety of the aircraft under emergency conditions. The temperature prediction of the RAT bay is of significant for the safety under emergency condition. In this paper, the RAT bay temperature, altitude, atmospheric static temperature, flight speed, and cabin temperatures around the RAT bay are analyzed as a whole through the Proper Orthogonal Decomposition (POD), and the RAT bay temperature is predicted under specific working conditions through RAT bay temperature model and the mapping relationship between the simplified model and the complete model. This paper selects the test data as the sample data, and uses POD method to predict the temperature of the RAT bay. According to the prediction results, the energy distribution of the first order mode exceeds 99% of energy of all modes. After data normalization, the absolute average error of the prediction results could reach 0.063 as the minimum, and the variance could reach 0.07 as the minimum; furthermore, the resuls show that the better the prediction effect could be achieved with more samples.

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  • 收稿日期:2022-11-09
  • 最后修改日期:2023-03-12
  • 录用日期:2023-03-14
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