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Back propagation neural network based control for the heating system of a polysilicon reduction furnace.
- Source :
-
The Review of scientific instruments [Rev Sci Instrum] 2013 Dec; Vol. 84 (12), pp. 125108. - Publication Year :
- 2013
-
Abstract
- In this paper, the Back Propagation (BP) neural network based control strategy is proposed for the heating system of a polysilicon reduction furnace. It is applied to obtain the control signal I(d), which is used to adjust the heating power through operations of the silicon core temperature, furnace temperature, silicon core voltage, and resistance of the current control cycle. With the control signal I(d) the polycrystalline silicon can be heated from room temperature to the required temperature smoothly and steadily. The proposed BP network applied in this paper can obtain the accurate control signal I(d) and achieve the precise control purpose. This paper presents the principle of the BP network and demonstrates the effectiveness of the BP network in the heating system of a polysilicon reduction furnace by combining the simulation analysis with experimental results.
Details
- Language :
- English
- ISSN :
- 1089-7623
- Volume :
- 84
- Issue :
- 12
- Database :
- MEDLINE
- Journal :
- The Review of scientific instruments
- Publication Type :
- Academic Journal
- Accession number :
- 24387469
- Full Text :
- https://doi.org/10.1063/1.4847157