Fig.1

Main contents of aerostructure impact monitoring

Table 1

Summary of advantages and disadvantages of sensors for impact monitoring

传感器类型		优点	缺点
压电传感器		频率响应范围宽，动态响应速度快，测量信号的信噪比高	材料性质随温度变化，测量中易受到振动的干扰
光纤光栅传感器		重量轻，耐腐蚀，可嵌入，能够实现多参数测量，抗电磁干扰	制造成本较高，容易脆断，需要精确的校准和补偿
应变传感器		制造成本低，重量轻，动态响应速度快，简单易用	稳定性受到温度的影响，测量信号的信噪比较差
声发射传感器		频率响应范围宽，动态响应速度快，灵敏度高	体积较大，制造成本高，对环境噪声敏感
加速度传感器		频率响应范围宽，低功耗，动态响应速度快	体积较大，制造成本较高，测量中易受到振动的干扰
柔性传感器		体积小、重量轻，适应复杂结构表面	软硬接口处对机械变形敏感，抗疲劳性能较差

Fig.2

Distributed and dense sensor array layout diagram

Fig.3

Typical impact localization methods based on time difference

Fig.4

Time reversal focusing impact localization method［65］

Fig.5

Virtual time reversal focusing method for impact localization based on phase synthesis［69］

Fig.6

Experimental verification of reference database method on real composite wing box structure［78］

Fig.7

Impact monitoring method based on transfer learning［111］

Fig.8

Beamforming method for impact localization

Fig.9

Sensor clusters methods for impact localization

Fig.10

Linear sensor array impact signal model

Fig.11

Experimental verification of near field 2D-MUSIC impact localization method［139-140］

Fig.12

MUSIC impact localization method based on plum blossom array［144］

Fig.13

Spatial wavenumber filter impact localization method［145］

Fig.14

Impact monitoring on Airbus A350-900［149］

Table 2

Comparison of impact location methods

Fig.15

Impact force identification method based on FOGS Lp［163］

Fig.16

Element-wise Bayesian regularization for impact load identification［165］

Fig.17

Impact localization and load reconstruction based on machine vision and deep learning［170］

Fig.18

Feature learning-based method for impact load reconstruction and localization［171］

Table 3

Comparison of impact load reconstruction methods

Fig.19

Impact energy level assessment of composite structures using MUSIC-ANN approach［173］