MLP ANN Condition Assessment Model of the Turbogenerator Shaft A6 HPP Đerdap 2

Abstract

This paper describes a model for estimating the condition of the shafts of turbines of the current generator in Hydropower plant Đerdap 2. For this purpose, an integral diagnostic approach was used. Based on the diagnostics of the condition of the shaft and the estimated lifetime, a multi-layer perceptron (MLP) based artificial neural network (ANN) is built, which is able to estimate the remaining lifespan of the turbine shaft. The MLP ANN model has not been made in this way on turbogenerators of hydroelectric power plant Đerdap 2 until now. The significance of this approach is that experiment brings about topology of ML ANN (number of neurons and layers) which is optimal for this model, training and testing. Results obtained from the neural network can be further used for decision-making about the moment of diagnosis or maintenance actions, as well as reducing stagnation and production losses.

A Practical Model of the Application of Information Technology in Various Fields of Online Education during the COVID-19 Pandemic: Mechanical Engineering, Traffic, Informatics and Statistics, Accounting and Auditing

“…The ANN model proposed in this paper was developed by the first author and implemented in other fields [29,30], which was the inspiration to perform research on the possibility of the ANN being a helpful tool or selecting questions for tests on its own.…”

Fault diagnosis of machines operating in variable conditions using artificial neural network not requiring training data from a faulty machine

“…A naturally occurring artificial intelligence model for diagnostic applications is that of classifier models. This is problematic, however, because when using neural networks as classifiers, learning data recorded for the machine to be diagnosed and for predicted faults are required [16][17][18][19][20][21][22][23][24]. There is work related to the reduction of damage data in learning vectors [25].…”