Naslov
Vibration prediction of pellet mills power transmission by artificial neural network

Autori
Milovancevic, Milos ; Nikolic, Vlastimir ; Pavlovic, Nenad T. ; Veg, Aleksandar ; Troha, Sanjin

Izvornik
Assembly Automation (0144-5154) 37 (2017), 4; 01-08

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Sensors, Simulation

Sažetak
Purpose – Vibration monitoring is an important task for any system to ensure safe operations. Improvement of control strategies is crucial for the vibration monitoring. Design/methodology/approach – As predictive control is one of the options for the vibration monitoring in this paper, the predictive model for vibration monitoring was created. Findings – Although the achieved prediction results were acceptable, there is need for more work to apply and test these results in real environment. Originality/value – Artificial neural network (ANN) was implemented as the predictive model while extreme learning machine (ELM) and back propagation (BP) learning schemes were used as training algorithms for the ANN. BP learning algorithm minimizes the error function by using the gradient descent method. ELM training algorithm is based on selecting of the input weights randomly of the ANN network and the output weight of the network are determined analytically.

Izvorni jezik
Engleski

Znanstvena područja
Strojarstvo, Temeljne tehničke znanosti

POVEZANOST RADA