Using a test rig, two different fiber bragg grating sensors were exposed to temperature changes, compressive loads and bendings. The light spectrum reflected by them was analyzed with respect to these three effects, utilizing ma-chine learning algorithms. The results show that the models of the sensors are suitable for detecting and differenti-ating the effects of bending and temperature changes with sufficient accuracy