On-Line Estimation of Coal's HGI by Neural Networks
| Autor: | Isao Moriyama, Takakazu Ishimatsu, Katsuyuki Kawaguchi, Kazuo Sagara, Eri Kawaguchi |
|---|---|
| Rok vydání: | 1999 |
| Předmět: |
Engineering
Quantitative Biology::Neurons and Cognition Pulverized coal-fired boiler Artificial neural network Waste management business.industry Mechanical Engineering Boiler (power generation) Network structure Industrial and Manufacturing Engineering Mechanics of Materials Pulverizer Coal business Process engineering Physics::Atmospheric and Oceanic Physics |
| Zdroj: | TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C. 65:4730-4736 |
| ISSN: | 1884-8354 0387-5024 |
| DOI: | 10.1299/kikaic.65.4730 |
| Popis: | In a pulverized coal fired boiler, various kinds of coals are used as a fuel. It is important to estimate properties of fired coal at the on-line, in order to realize good operated performance just like oil or gas fired boiler. Hardgrove grindability index is one of the important properties. Neural network method is proposed to estimate the index. Experimental results show that our estimation model is effective on the pulverizer, and is superior to multiple regression analysis. Study on the appropriate network structures is also described. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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