PREGLED UPORABE UMETNE INTELIGENCE V JEDRSKIH ELEKTRARNAH
Povzetek
Jedrske elektrarne so poznane kot kompleksni sistemi, njihovo vzdrževanje pa je ključno za zagotavljanje varnosti in zanesljivega obratovanja. Trenutno se v jedrskih elektrarnah uporablja princip časovno zasnovanega vzdrževanja, ki temelji na periodičnih pregledih za preprečevanje okvar. Pomembno je poudariti, da takšen pristop zahteva veliko porabo sredstev in ni vedno učinkovit. Alternativno lahko uvedemo vzdrževanje na podlagi stanja opreme z uporabo umetne inteligence ob predčasnem zaznavanju okvar, s čimer zmanjšamo stroške vzdrževanja in obratovanja. Potencial umetne inteligence v jedrski industriji je velik, od zagotavljanja zanesljive proizvodnje do vzdrževanja. Tehniki, kot sta nadzorovano in nenadzorovano učenje, sta izpostavljeni v članku, saj sta ključno orodje za zaznavanje napak, vzorcev in razvoja preventivnih modelov. Pri nadzorovanem učenju algoritem učimo z znanimi podatki, ki so klasificirani. Pri nenadzorovanem učenju algoritem učimo z veliko količino neklasificiranih podatkov, iz katerih model izlušči vzorce in zaznava odstopanje. Za integracijo umetne inteligence v jedrske elektrarne pa ostaja še veliko izzivov, med drugim tudi pomanjkanje standardnih pristopov. Ne glede na ponujene izzive pa orodja z uporabo umetne inteligence, globokega učenja in hibridnimi modeli obetajo pozitivne rezultate na področju zaznavanja napak in napovedovanja v jedrskih elektrarnah. Takšni napredki izboljšujejo varnost in omogočajo zanesljivo obratovanje. Čeprav umetna inteligenca še ni bila temeljno vpeljana v jedrsko industrijo, prikazuje pozitivne napredke za njeno prihodnost. Njena implementacija povečuje zaznavanje napak, zmanjšuje obratovalna tveganja ter zagotavlja stabilno in zanesljivo proizvodnjo električne energije.
Prenosi
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