Research on satellite structural health monitoring based on ultrashort femtosecond grating array and artificial neural network

•A new type of oxide-doped fiber was designed and fabricated, and high-performance ultrashort grating arrays were engraved on the fiber by femtosecond laser direct writing technology.•The layout strategy of the novel grating sensor array on the satellite surface is studied. The mechanical model of the satellite is established.•The damage strain response of the satellite under the attack of different angles and speeds were measured by sensors.•The precise location of the damage on the surface of the spacecraft satellite is realized by combining the grating array sensor data with the multi-layer convolutional neural network. The accuracy rate can reach 90.31%. The safety of spacecraft and satellite in orbit is very important, and structural health monitoring is needed. At present, the existing technology is limited by load and difficult to realize. In this paper, we propose a feasible method to detect and locate the damage of satellite by combining ultrashort femtosecond grating array inscribed on oxide-doped fiber with multilayer artificial neural network. An oxide-doped fiber with high robustness is designed, and ultrashort grating arrays are fabricated on the fiber by femtosecond laser point-by-point writing technology. The effects of impactor velocity and angle on impact response was investigated by numerical simulations and physical experiments. Subsequently, repeated impact experiments were conducted on the satellite to obtain the training dataset and testing dataset for two-dimensional convolutional neural network. The network with symmetric convention kernels has an 88.12% localization accuracy and a better performance in boundary region, and the network architecture with asymmetric convention kernels has a 90.31% accuracy and a better performance in middle region.