Nicolas Marichal, GracilianoDel Castillo Zas, María LourdesLópez López, JesúsPadrón, IsidroArtes Gomez, Mariano2023-11-082023-11-082016-04-01Marichal, G., Del Castillo, M. L., López, J. R., Padrón, I., & Artés, M. (2016). An artificial intelligence approach for gears diagnostics in AUVs. Sensors, 16(4), 529.1424-3210https://hdl.handle.net/10016/38795In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised.14eng© 2016 by the authors; licensee MDPI, Basel, Switzerland.Atribución 3.0 EspañaVibrationAuvsVibrationAlgorithmSystemAnfisCondition monitoringGenetic neuro-fuzzy systemsFuzzy logicFault-tolerant controlNeural-networksUnderwater vehiclesFuzzy inferenceresearch articleIngeniería Mecánicahttps://doi.org/10.3390/s16040529open access14, 52914Sensors16AR/0000018684