Book chapter
Mining Temporal Data: A Coal-Fired Boiler Case Study
Knowledge-Based Intelligent Information and Engineering Systems, pp.953-958
Lecture Notes in Computer Science, Springer Berlin Heidelberg
2005
DOI: 10.1007/11553939_134
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.
Details
- Title: Subtitle
- Mining Temporal Data: A Coal-Fired Boiler Case Study
- Creators
- Andrew Kusiak - Intelligent Systems Laboratory, Industrial Engineering, The University of Iowa, Iowa City, USAAlex Burns - Intelligent Systems Laboratory, Industrial Engineering, The University of Iowa, Iowa City, USA
- Resource Type
- Book chapter
- Publication Details
- Knowledge-Based Intelligent Information and Engineering Systems, pp.953-958
- Publisher
- Springer Berlin Heidelberg; Berlin, Heidelberg
- Series
- Lecture Notes in Computer Science
- DOI
- 10.1007/11553939_134
- eISSN
- 1611-3349
- ISSN
- 0302-9743
- Language
- English
- Date published
- 2005
- Academic Unit
- Nursing; Industrial and Systems Engineering
- Record Identifier
- 9984064586802771
Metrics
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