Title

Mining temporal data: A coal-fired boiler case study

Document Type

Conference Paper

Peer Reviewed

1

Publication Date

1-1-2005

Journal/Book/Conference Title

9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005, September 14, 2005 - September 16

Conference Location

Melbourne, Australia

Volume

3683 LNAI

Abstract

This paper presents an approach to control pluggage of a coal-fired boiler. The proposed approach involves statistics, data partitioning, parameter reduction, and data mining. The proposed approach was tested on a 750 MW commercial coal-fired boiler affected with a fouling problem that leads to boiler pluggage that causes unscheduled shutdowns. The rare-event detection approach presented in the paper identified several critical time-based data segments that are indicative of the ash pluggage. Springer-Verlag Berlin Heidelberg 2005.

Keywords

Sustainability, This paper presents an approach to control pluggage of a coal-fired boiler. The proposed approach involves statistics, data partitioning, parameter reduction, and data mining. The proposed approach was tested on a 750 MW commercial coal-fired boiler affected with a fouling problem that leads to boiler pluggage that causes unscheduled shutdowns. The rare-event detection approach presented in the paper identified several critical time-based data segments that are indicative of the ash pluggage. Springer-Verlag Berlin Heidelberg 2005.

Published Article/Book Citation

9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005, September 14, 2005 - September 16, Melbourne, Australia, 2005.



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URL

http://ir.uiowa.edu/cee_pubs/405