Pregled bibliografske jedinice broj: 601494
The use of self organizing neural network for vibration unbalance assessment
The use of self organizing neural network for vibration unbalance assessment // 21th European Congress on Maintenance and Asset Management (EUROMAINTENANCE 2012) : proceedings
Beograd, 2012. (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), stručni)
CROSBI ID: 601494 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
The use of self organizing neural network for vibration unbalance assessment
Autori
Lisjak, Dragutin ; Čala, Ivo ; Alić, Kostešić, Vesna
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), stručni
Izvornik
21th European Congress on Maintenance and Asset Management (EUROMAINTENANCE 2012) : proceedings
/ - Beograd, 2012
Skup
European Congress on Maintenance and Asset Management (21 ; 2012)
Mjesto i datum
Beograd, Srbija, 14.05.2012. - 16.05.2012
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
vibration; unbalance; neural networks; self-organizing maps
Sažetak
In the paper the possibility of using the self-organizing (Self Organizing Maps - SOM) neural network as a model for the assessment of vibration causes and respectively the assessment of vibration unbalance is presented. For a successful assessment of vibration unbalance the clustering of measurement data from a frequency spectrum (Hz, mm/s) is included in the model. The presented model of self-organizing neural network may be used as a template for the assessment, i.e. identification of other types of vibration loadings and also its integration in a CMMS system (Computerized Maintenance Management System) as an expert system for a decision making support is proposed.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo
POVEZANOST RADA
Projekti:
120-1201780-1779 - Modeliranje svojstava materijala i parametara procesa (Filetin, Tomislav, MZOS ) ( CroRIS)
Ustanove:
Fakultet strojarstva i brodogradnje, Zagreb
