Combinatorial Neural Networks Based Model for Identification of Marine Steam Turbine Clustered Parameters

Steam turbine model

In order to characterize the transient dynamics of steam turbines subsections, in this paper, nonlinear mathematical models are first developed based on the energy balance, thermodynamic principles and semi-empirical equations. Then, the related parameters of developed models are either determined by empirical relations or they are adjusted by applying genetic algorithms (GA) based on experimen...

Steam Turbine Steam System

Fault Detection and Isolation Based on Neural Networks Case Study: Steam Turbine

The real-time fault diagnosis system is very important for steam turbine generator set due serious fault results in a reduced amount of electricity supply in power plant. A novel real-time fault diagnosis system is proposed by using Levenberg-Marquardt algorithm related to tuning parameters of Artificial Neural Network (ANN). The model of novel fault diagnosis system by using ANN are built and ...

Steam Turbine Configuration

Most electric power is produced by steam turbines. This is because the steam cycle is well suited to the conversion of heat to work and steam turbines can be built in a wide range of capacities up to about 1500 MW. Steam turbines are basically very simple having fixed blades to accelerate the steam and moving blades to absorb the resulting kinetic energy. The moving blades are mounted on a rota...

Efficient Parameters Selection for CNTFET Modelling Using Artificial Neural Networks

In this article different types of artificial neural networks (ANN) were used for CNTFET (carbon nanotube transistors) simulation. CNTFET is one of the most likely alternatives to silicon transistors due to its excellent electronic properties. In determining the accurate output drain current of CNTFET, time lapsed and accuracy of different simulation methods were compared. The training data for...