RT info:eu-repo/semantics/article
T1 Classification of belts status based on an automatic generator of fuzzy rules base system
A1 Hernández López, Ángela
A1 Marichal Plasencia, Graciliano Nicolás
A1 Ávila Prats, Deivis
A1 García-Prada, Juan Carlos
A2 Ingeniería CivilNáutica y Marítima
A2 INGEMAR
K1 Classification
K1 Vibration
K1 Genetic neuro-fuzzy
K1 Belts
AB The automation of maintenance is agrowingfieldandconsequently, predictive maintenance is achieving more importance. The main objective is to predict a breakage before it happens. In order to reach this, it is necessary to have an intelligent classification technique that analyzes the state of the key breakage elements and evaluates whether a replacement is necessary or not. This work presents a study to classify belts according to their state of use. For training, vibration data have been collected on a test bench using new belts, belts with half use and belts near the breaking point. The processing of these vibrations allows for extracting the characteristic parameters that can be related to its state of use, and then, after the initial analysis, these values are used as inputs for training the intelligent system. In particular, the Genetic Neuro-Fuzzy (GNF) technique has been chosen and, with the proposed algorithm, more detailed Fuzzy rules are obtained. Once the algorithm has been trained, it is possible to establish a relationship between the vibration shown by the belt and its state of use. The achieved results show that a good classifier has been built.
YR 2024
FD 2024
LK http://riull.ull.es/xmlui/handle/915/39564
UL http://riull.ull.es/xmlui/handle/915/39564
LA en
DS Repositorio institucional de la Universidad de La Laguna
RD 24-nov-2024