20.500.12556/RUL-165105 Določanje lege strukturne spremembe z uporabo podatkovnih pristopov Data-based location identification of structural change Za zaznavanje napak na izdelkih se v industriji pogosto uporablja strojni vid. V primerih, ko to ni mogoče, moramo razviti alternativne metode. V sklopu naloge je bil zasnovan model z avtoenkodersko konvolucijsko nevronsko mrežo, ki na podlagi spektrogramov dinamskega odziva rekonstruira sliko izdelka s prikazano lego napake. Ugotovljeno je bilo, da izdelan model v večini primerov natančno določi lego napake na izdelku in rekonstruira ustrezno sliko. In industry, machine vision is often used for defect detection in products. In cases where this is not feasible, alternative methods must be developed. Within this thesis, a model with an autoencoder convolutional neural network was designed to reconstruct an image of the product, displaying the location of the defect, based on spectrograms of the dynamic response. It was found that in most cases the model accurately determines the defect location on the product and reconstructs the corresponding image. konvolucijska nevronska mreža pytorch strukturna dinamika rekonstrukcija slike avtoenkoder convolutional neural network pytorch structural dynamics image reconstruction autoencoder true false false Slovenski jezik Angleški jezik Magistrsko delo/naloga 2024-11-23 07:30:04 2024-11-23 07:30:20 2024-12-13 10:32:07 0000-00-00 00:00:00 2024 0 0 XXII, 69 str. 2024 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 270154 38392.pdf 38392.pdf 1 7CB94A289CB1D013C772944E74F40A0D 39dadb3853f45482835e9754bce8b6ddac30f63193d4e1d53b5efe927cf6bbce 04d7d950-a964-11ef-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=196080 Fakulteta za strojništvo 0 0 0