基于FBG反射谱特征的修补结构裂纹扩展监测

为了提高飞行器壁板裂纹修补结构的安全性，对基于光纤布拉格光栅(FBG)反射谱特征的航空铝合金修补结构疲劳裂纹扩展长度及角度监测方法进行了研究。修补结构在疲劳载荷的作用下，裂纹发生扩展，其尖端附近会产生不均匀应变场，在其作用下FBG传感器反射谱发生变形，通过检测反射谱变形达到监测裂纹扩展的目的。建立了实验样件的模型，使用有限元方法计算得到不同角度下裂纹扩展到不同长度时的应变分布，使用传输矩阵数值计算方法得到相应的FBG反射谱。提取反射谱的主峰偏移、反射谱面积、次峰峰值和三峰峰值等变形特征，建立并训练人工神经网络(ANN)，通过ANN建立反射谱变形特征同裂纹扩展情况的关系，实现了对修补结构裂纹扩展的精确监测，监测裂纹长度误差在0.5 mm之内，角度误差在5°之内。解决了修补结构的裂纹扩展精确监测问题，对提高飞行器安全以及节约维护成本有着重要意义。

Monitoring of Crack Propagation in Repaired Structures Based on Characteristics of FBG Sensors Reflecting Spectra

In order to improve the security of aircraft repaired structures, a method of crack propagation monitoring in repaired structures is put forward basing on characteristics of Fiber Bragg Grating(FBG) reflecting spectra in this article. With the cyclic loading effecting on repaired structure, cracks propagate, whilenon-uniform strain field appears nearby the tip of crack which leads to the FBG sensors’ reflecting spectra deformations. The crack propagating can be monitored by extracting the characteristics of FBG sensors’ reflecting spectral deformations. A finite element model (FEM) of the specimen is established. Meanwhile, the distributions of strains which are under the action of cracks of different angles and lengths are obtained. The characteristics, such as main peak wavelength shift, area of reflecting spectra, second and third peak valueand so on, are extracted from the FBGs’ reflecting spectral which are calculated by transfer matrix algorithm. An artificial neural network is built to act as the model between the characteristics of the reflecting spectral and the propagation of crack. As a result, the crack propagation of repaired structures is monitored accurately and the error of crack length is less than 0.5 mm, the error of crack angle is less than 5 degree. The accurately monitoring problem of crack propagation of repaired structures is solved by taking use of this method. It has important significance in aircrafts safety improvement and maintenance cost reducing.