红外光谱发射率测量设备检定状态预测研究  

Research on predicting the calibration status of infrared spectral emissivity measurement equipment

作　　者：郭娟 张金铭 季新杰 GUO Juan;ZHANG Jin-ming;JI Xin-jie(Aviation Maintenance NCO School of Air Force Engineering University,Xinyang 464000,China)

机构地区：[1]空军工程大学航空机务士官学校,河南信阳464000

出　　处：《激光与红外》2024年第12期1900-1905,共6页Laser & Infrared

摘　　要：使用光谱发射率测量设备检测红外隐身涂层发射率,是监控飞机红外隐身涂层状态的一种重要手段。在测量设备检定周期内,受使用环境、使用频率、使用方法等因素影响,偶发设备状态变得恶劣,测量值偏离参考值,对及时发现红外隐身涂层缺陷带来一定风险,可能影响飞机整体红外隐身特性。针对检定周期内出现的测量值偏差问题,建立格拉姆角场(GAF)-并行卷积神经网络(PCNN)设备检定状态预测模型。将测量设备一维时序数据送入GAF-PC-NN模型中,经过深度学习,训练出红外发射率测量设备检定状态预测模型。试验表明,该检定状态预测模型平均识别准确率达到95%,且收敛速度快且稳定,可应用于设备检定状态预测,提示提前检定或者超检定周期使用,在确保设备状态良好的同时,减少设备检定活动,提高保障效率。Using spectral emissivity measurement equipment to detect the emissivity of infrared stealth coatings is an important means of monitoring the status of aircraft infrared stealth coatings.During the calibration cycle of the measuring equipment,due to factors such as usage environment,usage frequency,usage method and so on,the condition of the equipment occasionally becomes worse,and the measured values deviate from the reference value which poses a certain risk for timely detection of infrared stealth coating defects and may affect the overall infrared stealth characteristics of the aircraft.To address the issue of measurement deviation during the calibration cycle,a Gramian Angular Field(GAF)and Parallel Convolutional Neural Network(PCNN)calibration status prediction model is established.By collecting one-dimensional time-series data from the device and feeding it into the GAF-PCNN mode,a prediction model for the calibration status of infrared emissivity measurement equipment is trained through deep learning.The experiment shows that the average recognition accuracy of the calibration state prediction model reaches 95%,and the convergence speed is fast and stable,which can be applied to equipment calibration state prediction,prompting early calibration or use beyond the calibration cycle.While ensuring good equipment condition,it reduces equipment calibration activities and improves guarantee efficiency.

关 键 词：格拉姆角场 并行卷积神经网络 红外发射率 预测 检定状态 

分 类 号：TN976[电子电信—信号与信息处理] TH74[电子电信—信息与通信工程]