Artificial intelligence applied to electromechanical monitoring, a performance analysis
Visualitza/Obre
Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/183995
Correu electrònic de l'autorOSTERC.STASGMAIL.COM
Realitzat a/ambUniverza v Mariboru
Tipus de documentTreball Final de Grau
Data2020-01-05
Condicions d'accésAccés obert
Tots els drets reservats. Aquesta obra està protegida pels drets de propietat intel·lectual i
industrial corresponents. Sense perjudici de les exempcions legals existents, queda prohibida la seva
reproducció, distribució, comunicació pública o transformació sense l'autorització del titular dels drets
Abstract
Artificial intelligence is a wide concept and it’s being used in more and more machine applications, teaching them to perform tasks which would require human intelligence. The implemented algorithm requires samples of ''experience'' from which it can learn and predict the outcome; from there it mainly feeds itself. AI is basically divided into two subsets; deep learning and machine learning. They are mostly distinguished with the way the data is presented to the network. To summarize this project; First the data was monitored on an electromechanical system, monitored data from vibrations was saved and brought in Matlab program, there the data was transformed for future use with autoencoders, which learned the conditions, after training we have to try different parameters for getting the closest reconstruction possible. In the project we applied several techniques like using a multilayered auto-encoder and then finding the best hyper parameters for best results (they were measured by plotting signals and mean square error).
TitulacióMOBILITAT INCOMING
Localització
Fitxers | Descripció | Mida | Format | Visualitza |
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artificial intelligence.pdf | 1,768Mb | Visualitza/Obre |