Polymer optical fiber Bragg gratings for multiparameter analysis in UAV wings: an AI-integrated approach
This paper presents the development of a polymer optical fiber Bragg grating (POFBG)-based sensor system for measurement of vibration, force amplitude and position for fixed-wing unmanned aerial vehicle (UAV). The POFBG is positioned along the wing structure, where forces amplitude and locations resulted in spectral changes in the POFBG. Then, predefined spectral features are used as input of a Generative Adversarial Network (GAN) for data augmentation, which increased the dataset to 1000 different force amplitude and locations. The accuracy of 1.9 Hz was obtained for vibration analysis. In the force amplitude and location analysis, the feed forward neural network (FFNN) resulted in relative errors of 3.30% and 3.51% for force amplitude and position, such errors are related to root mean squared errors (RMSE) and standard deviations of 0.33 N±0.05 N and 35.18 mm±2.3 mm for force amplitude and location, respectively. If the number of input features is reduced to only 3 predefined spectral features the RMSE without GAN increases to 1.23 N ± 0.15 N and 75.34 mm ± 9.20 mm for force amplitude and position, respectively. The FFNN with data augmentation resulted in relative errors of 7.8% for force amplitude and 2.4% for force location (RMSE of 0.78 N±0.10 N and 24.90 mm±2.1 mm, respectively), using 3 input features. The data augmentation resulted in accuracy increase with almost twofold reduction in the RMSE for the force amplitude and more than 3 times reduction of the RMSE for position estimation. Therefore, the POFBG sensor is a feasible option for shape reconstruction in UAV structures.