| 학회 |
한국화학공학회 |
| 학술대회 |
2018년 봄 (04/25 ~ 04/27, 창원컨벤션센터) |
| 권호 |
24권 1호, p.141 |
| 발표분야 |
공정시스템 |
| 제목 |
Comparative study of estimation methods of NOx emission with selection of input parameters for a coal-fired boiler |
| 초록 |
This study focuses on estimation of NOx emission and selection of input parameters for a coal-fired boiler in 500 MW power generation plant. The initial operating input parameters are determined based on operation heuristics and accumulated operation knowledge, and the essential input parameters are selected by sensitivity analysis where the performance of the estimation model is assessed as one or some input parameters are successively eliminated from the computation while all other input parameters are retained. From the sequential input selection process, less than 10 input parameters were survived out of 36 initial input parameters. Auto-regressive moving average (ARMA) model, artificial neural networks (ANN), partial least-squares (PLS) model, and least-squares support vector machine (LSSVM) algorithm were proposed to express the relationship between the operating input parameters and the content of NOx emission. Finally, the principal components analysis (PCA) apply to enhances the estimation performance of each model.
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| 저자 |
김범석1, 김태영1, 박태창1, 박상용2, 임미숙2, 임준재2, 여영구1
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| 소속 |
1한양대, 2한국서부발전 |
| 키워드 |
공정모델링 |
| E-Mail |
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| 원문파일 |
초록 보기 |
