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, while non-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 value and 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.