复合材料胶接挖补中的情境意识预测  

Situational awareness prediction model in bonding repair of composite materials

作　　者：贺强[1] 程林 HE Qiang;CHENG Lin(Aviation Engineering College,Civil Aviation Flight University of China,Guanghan 618307,China)

机构地区：[1]中国民用航空飞行学院航空工程学院,广汉618307

出　　处：《复合材料科学与工程》2022年第12期93-100,共8页Composites Science and Engineering

基　　金：四川省科技计划资助应用基础研究项目(2021YJ0537)。

摘　　要：情境意识丧失和退化是导致复合材料结构适航维修差错的重要诱因,情境意识水平监测对于减少维修差错、保障飞行安全具有重要意义。为监测复合材料胶接挖补中的情境意识水平,提出基于眼动的情境意识度量与预测方法。首先,针对复合材料结构胶接挖补工艺过程,结合情境意识理论模型分析了复合材料维修中的情境意识。在此基础上,设计复合材料胶接挖补情境意识测量实验,利用Tobii眼动仪记录被试的眼动数据,SART量表测量被试的情境意识水平,基于情境意识水平与眼动指标的相关性提取了度量情境意识的眼动特征模式。基于该模式,利用RVM构建了情境意识预测模型。研究结果表明模型的预测精度和拟合效果能支持维修情境意识水平的在线监测和评价。The situational awareness loss and degradation is an important error causation in airworthiness maintenance of composite material components. The monitoring of situational awareness level has great significance to reduce maintenance errors and ensure flight safety. To monitor the situational awareness, the measurement and prediction method of situational awareness based on eye movement was proposed. Firstly, the situational awareness of composite materials bonding repair was analyzed according to the maintenance process and the theoretical model of situational awareness. Then, the situational awareness measurement experiment was designed. In this experiment, the eye movement data was recorded by Tobii and the SART was used to measure the situational awareness subjectively. Dependent on the correlation analysis between eye movement and situational awareness, the feature mode of eye movement was constructed to measure the situational awareness. Finally, the situational awareness prediction model was established by relevance vector machine with this pattern. The experimental results show that the prediction accuracy and fitting effect of the model can support the online monitoring and evaluation of the maintenance situational awareness.

关 键 词：复合材料 适航维修 眼动 情境意识 RVM 

分 类 号：TB332[一般工业技术—材料科学与工程]