TY  - JOUR
AB  - Purpose The purpose of this study is to establish a vibration prediction of pellet mills power transmission by artificial neural network. 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.
VL  - 37
IS  - 4
SN  - 0144-5154
DO  - 10.1108/AA-06-2016-060
UR  - https://doi.org/10.1108/AA-06-2016-060
AU  - Milovancevic Milos
AU  - Nikolic Vlastimir
AU  - Pavlovic Nenad T.
AU  - Veg Aleksandar
AU  - Troha Sanjin
PY  - 2017
Y1  - 2017/01/01
TI  - Vibration prediction of pellet mills power transmission by artificial neural network
T2  - Assembly Automation
PB  - Emerald Publishing Limited
SP  - 464
EP  - 470
Y2  - 2024/04/23
ER  -