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.
Conference proceeding
Mining temporal data: A coal-fired boiler case study
9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005, September 14, 2005 - September 16, pp.953-958
3683 LNAI (Melbourne, Australia)
2005
Abstract
Details
- Title: Subtitle
- Mining temporal data: A coal-fired boiler case study
- Creators
- Andrew Kusiak - University of IowaAlex Burns
- Resource Type
- Conference proceeding
- Publication Details
- 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005, September 14, 2005 - September 16, pp.953-958
- Conference
- 3683 LNAI (Melbourne, Australia)
- ISSN
- 1931-0145
- Language
- English
- Date published
- 2005
- Academic Unit
- Nursing; Industrial and Systems Engineering
- Record Identifier
- 9983557509002771
Metrics
21 Record Views