AOD furnace splash soft-sensor in the smelting process based on improved BP neural network

Haitao Ma; Shanshan Wang; Libin Wu; Ying Yu

doi:10.1117/12.2294038

15 November 2017 AOD furnace splash soft-sensor in the smelting process based on improved BP neural network

Haitao Ma, Shanshan Wang, Libin Wu, Ying Yu

Proceedings Volume 10605, LIDAR Imaging Detection and Target Recognition 2017; 106052S (2017) https://doi.org/10.1117/12.2294038
Event: LIDAR Imaging Detection and Target Recognition 2017, 2017, Changchun, China

Abstract

In view of argon oxygen refining low carbon ferrochrome production process, in the splash of smelting process as the research object, based on splash mechanism analysis in the smelting process , using multi-sensor information fusion and BP neural network modeling techniques is proposed in this paper, using the vibration signal, the audio signal and the flame image signal in the furnace as the characteristic signal of splash, the vibration signal, the audio signal and the flame image signal in the furnace integration and modeling, and reconstruct splash signal, realize the splash soft measurement in the smelting process, the simulation results show that the method can accurately forecast splash type in the smelting process, provide a new method of measurement for forecast splash in the smelting process, provide more accurate information to control splash.

Citation Download Citation

Haitao Ma, Shanshan Wang, Libin Wu, and Ying Yu "AOD furnace splash soft-sensor in the smelting process based on improved BP neural network", Proc. SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017, 106052S (15 November 2017); https://doi.org/10.1117/12.2294038

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