Original title: Využití umělé inteligence k monitorování stavu obráběcího stroje
Translated title: Using artificial intelligence to monitor the state of the machine
Authors: Popara, Nikola ; Bražina, Jakub (referee) ; Kovář, Jiří (advisor)
Document type: Master’s theses
Year: 2021
Language: cze
Publisher: Vysoké učení technické v Brně. Fakulta strojního inženýrství
Abstract: [cze] [eng]
Práca je zameraná na monitorovanie najviac namáhaných častí obrábacieho stroja. Použitá metóda umelej inteligencie je rekurentná neurónová sieť a jej modifikácie. Nakoľko dáta zo senzorov mali sekvenčný charakter, bolo vhodné zvoliť práve rekurentnú neuóonovú sieť. Práca sa zaoberá riešením troch úloh. Prvá úloha bola zameraná na stanovenie predpokladaného opotrebenia frézy, na základe nepriamej metódy využívajúcej neurónovú sieť. Ďalšia úloha sa zameriava na detekciu poruchy ložíska na základe dát získaných z akcelerometra. Treťou úlohou bolo predikovať dobu do poškodenia monitorovaného ložiska. This thesis is focus on monitoring state of machine parts that are under the most stress. Type of artificial intelligence used in this work is recurrent neural network and its modifications. Chosen type of neural network was used because of the sequential character of used data. This thesis is solving three problems. In first problem algorithm is trying to determine state of mill tool wear using recurrent neural network. Used method for monitoring state is indirect. Second Problem was focused on detecting fault of a bearing and classifying it to specific category. In third problem RNN is used to predict RUL of monitored bearing.
Keywords: condition monitoring of a bearing; degradation state of a bearing; GRU; LSTM; prediction of RUL; recurrent neural network; GRU; LSTM; monitorovanie ložiska; predikcia RUL; rekurentná neurónová sieť; stav opotrebenia frézy

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/199575

Permalink: http://www.nusl.cz/ntk/nusl-609386


The record appears in these collections:
Universities and colleges > Public universities > Brno University of Technology
Academic theses (ETDs) > Master’s theses