Abstract
Tube leakage in boilers has been a major contribution to trips which eventually leads to power plant shut downs. Training of network and developing artificial neural network (ANN) models are essential in fault detection in critically large systems. This research focusses on the ANN modelling through training and validation of real data acquired from a sub-critical boiler unit. The artificial neural network (ANN) was used to develop a compatible model and to evaluate the working properties and behaviour of boiler. The training and validation of real data has been applied using the feed-forward with back-propagation (BP). The right combination of number of neurons, number of hidden layers, training algorithms and training functions was run to achieve the best ANN model with lowest error. The ANN was trained and validated using real site data acquired from a coal fired power plant in Malaysia. The results showed that the Neural Network (NN) with one hidden layers performed better than two hidden layer using feed-forward back-propagation network. The outcome from this study give us the best ANN model which eventually allows for early detection of boiler tube leakages, and forecast of a trip before the real shutdown. This will eventually reduce shutdowns in power plants.
Highlights
A thermal power plant works using steam to drive the turbines. These power plants consist of various essential components working together including the boiler, condenser, burner, turbines and coal bunkers
The boiler consists of various sections including the economisers, steam drum, superheaters, fluidising grid and boiler tubes
This study has focused on constructing the best artificial neural network (ANN) combination model
Summary
A thermal power plant works using steam to drive the turbines These power plants consist of various essential components working together including the boiler, condenser, burner, turbines and coal bunkers. All these systems has to work together in order to ensure smooth operations in the plant. The boiler consists of various sections including the economisers, steam drum, superheaters, fluidising grid and boiler tubes. These tubes contain large amount of water travelling through inside at high velocity. Any debris or foreign object flowing in the tubes at high velocity will cause tube damage or failure. Undetected tube failures, may cause even more damages to other tubes
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