Desarrollo de una red neuronal convolucional para la detección de fallos en maquinaria rotativa en tiempo real

Abstract

ABSTRACT The importance of this research lies in the that it is a topic that is booming and with which solutions can be foreseen to the productive community. This research is intended to be a significant contribution to companies possessing machinery with three-phase alternating current motors, because it will provide operators with safety on fault-free machinery operation. This project is intended to be of practical use in the areas of Engineering in Systems and Industrial Engineering because through the use of computer tools information can be obtained on the status of three-phase ac motors in real time, whereby operators can anticipate failures that can occur in three-phase alternating current motors and anticipate their solutions , which will reduce losses caused by unforeseen machine shutdown. The proposed solution is based on the line of research that deals with Artificial Intelligence, which is based on developing intelligent systems, in this case through the use of a convolutional neural network, failures in three-phase motors will be detected in their early stages to apply immediate corrections. With this project, the main beneficiaries will be the companies that use rotating machinery in their production, because production would never be stopped if the failures were foreseen.