By Topic

Algorithm for fault prediction of power plant machines using peak codes

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Ui-Pil Chong ; Dept. of Comput. Eng. & Inf. Technol., Ulsan Univ., Ulsan ; Chang-Su Roh ; Kieu Huu Thu ; Jong-Myon Kim

Fault detection systems for machines used in a power plant have been actively studied in universities and research institutes around the world. Previous research has led to the development of detection systems that use vibration, temperature, and pressure as its measurement gauges. We introduce a novel approach where sound is used for fault prediction by creating the sound peak code method. The sound peak code can be attached to a machine like a bar code, and it can immediately find the normal or abnormal operation of a power plant machine. This method requires the development of an algorithm that satisfies three requirements.

Published in:

Strategic Technologies, 2008. IFOST 2008. Third International Forum on

Date of Conference:

23-29 June 2008