TY  - CONF
AU  - Ilić, Dragoljub
AU  - Milošević, Dragan
AU  - Momčilović, Dejan
PY  - 2022
UR  - http://rims.institutims.rs/handle/123456789/480
AB  - During regular operation, hydro turbine elements have complex operating conditions. In order to prevent major failures, among other common preventive measures, it is necessary to make a useful model of hydro turbine. Development of this model was focused on real elements and data set of real operating history. To solve this, an integral diagnostic approach is used. Based on the real diagnostics data of the condition and data history of the hydro turbine shaft and the designed life expectancy, a multi-layer perceptron (MLP) based artificial neural network (ANN) is built. The idea with this model was to enable to life assessment of the turbine shaft in any particular moment during regular operation.
This paper describes a model for estimating the condition of the shafts of turbines of the current generator in Hydropower plant Derdap 2. The significance of this approach is that real experimental data support development of ML ANN (number of neurons and layers) topology, which is optimal for this model, training and testing. Results obtained from this model are used for decision-making about the planning time schedule of maintenance actions, as well as reducing overhaul time and direct losses.
PB  - University of Belgrade - Faculty of Mechanical Engineering, Belgrade, Serbia
C3  - 1st International Conference on Mathematical Modelling in Mechanics and Engineering Mathematical Institute SANU
T1  - Neural network model for the condition assessment of hydro turbines
SP  - 154
UR  - https://hdl.handle.net/21.15107/rcub_rims_480
ER  - 

@conference{
author = "Ilić, Dragoljub and Milošević, Dragan and Momčilović, Dejan",
year = "2022",
abstract = "During regular operation, hydro turbine elements have complex operating conditions. In order to prevent major failures, among other common preventive measures, it is necessary to make a useful model of hydro turbine. Development of this model was focused on real elements and data set of real operating history. To solve this, an integral diagnostic approach is used. Based on the real diagnostics data of the condition and data history of the hydro turbine shaft and the designed life expectancy, a multi-layer perceptron (MLP) based artificial neural network (ANN) is built. The idea with this model was to enable to life assessment of the turbine shaft in any particular moment during regular operation.
This paper describes a model for estimating the condition of the shafts of turbines of the current generator in Hydropower plant Derdap 2. The significance of this approach is that real experimental data support development of ML ANN (number of neurons and layers) topology, which is optimal for this model, training and testing. Results obtained from this model are used for decision-making about the planning time schedule of maintenance actions, as well as reducing overhaul time and direct losses.",
publisher = "University of Belgrade - Faculty of Mechanical Engineering, Belgrade, Serbia",
journal = "1st International Conference on Mathematical Modelling in Mechanics and Engineering Mathematical Institute SANU",
title = "Neural network model for the condition assessment of hydro turbines",
pages = "154",
url = "https://hdl.handle.net/21.15107/rcub_rims_480"
}

Ilić, D., Milošević, D.,& Momčilović, D.. (2022). Neural network model for the condition assessment of hydro turbines. in 1st International Conference on Mathematical Modelling in Mechanics and Engineering Mathematical Institute SANU
University of Belgrade - Faculty of Mechanical Engineering, Belgrade, Serbia., 154.
https://hdl.handle.net/21.15107/rcub_rims_480

Ilić D, Milošević D, Momčilović D. Neural network model for the condition assessment of hydro turbines. in 1st International Conference on Mathematical Modelling in Mechanics and Engineering Mathematical Institute SANU. 2022;:154.
https://hdl.handle.net/21.15107/rcub_rims_480 .

Ilić, Dragoljub, Milošević, Dragan, Momčilović, Dejan, "Neural network model for the condition assessment of hydro turbines" in 1st International Conference on Mathematical Modelling in Mechanics and Engineering Mathematical Institute SANU (2022):154,
https://hdl.handle.net/21.15107/rcub_rims_480 .