DocumentCode :
3762050
Title :
Fuel oil leak detection in power plant with recurrent neural network and execute in programmable logic controller
Author :
Mahmoud Mohammadi;Abbas Nikbakht;Aliakbar Bavalishoar
Author_Institution :
Khorram Shahr Power Plant, Khorram Shahr, Iran
fYear :
2015
Firstpage :
927
Lastpage :
932
Abstract :
In this paper, the use of Recurrent Neural Network has designed in MATLAB software with manual formulation for nonlinear system identification in order to detect fuel oil leakage and then the Neural Network structure has converted to a software block for Siemens SIMATIC programmable logic controller that can be used quite practically inside the project. By comparing the actual data that is taken from the real environment with output of the identified system by the neural network, the leak is going to detect in a few seconds.
Keywords :
"Decision support systems","Fuels","Programming","Neural networks","System identification","Leak detection","Power generation"
Publisher :
ieee
Conference_Titel :
Knowledge-Based Engineering and Innovation (KBEI), 2015 2nd International Conference on
Type :
conf
DOI :
10.1109/KBEI.2015.7436168
Filename :
7436168
Link To Document :
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