Back propagation artificial neural network and its application in fault detection of condenser failure in thermo plant

11Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Steam condenser is one of the most important equipment in steam power plants. If the steam condenser trips it may lead to whole unit shutdown, which is economically burdensome. Early condenser trips monitoring is crucial to maintain normal and safe operational conditions. In the present work, artificial intelligent monitoring systems specialized in condenser outages has been proposed and coded within the MATLAB environment. The training and validation of the system has been performed using real operational measurements captured from the control system of selected steam power plant. An integrated plant data preparation scheme for condenser outages with related operational variables has been proposed. Condenser outages under consideration have been detected by developed system before the plant control system» © Published under licence by IOP Publishing Ltd.

Cite

CITATION STYLE

APA

Ismail, F. B., & Thiruchelvam, V. (2013). Back propagation artificial neural network and its application in fault detection of condenser failure in thermo plant. In IOP Conference Series: Earth and Environmental Science (Vol. 16). Institute of Physics Publishing. https://doi.org/10.1088/1755-1315/16/1/012019

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free