Abstract
In order to optimize the sintering process, a real-time operation guide system with artificial intelligence was developed, mainly including the data acquisition online subsystem, the sinter chemical composition controller, the sintering process state controller, and the abnormal conditions diagnosis subsystem. Knowledge base of the sintering process controlling was constructed, and inference engine of the system was established. Sinter chemical compositions were controlled by the strategies of self-adaptive prediction, internal optimization and center on basicity. And the state of sintering was stabilized centering on permeability. In order to meet the needs of process change and make the system clear, the system has learning ability and explanation function. The software of the system was developed in Visual C++ programming language. The application of the system shows that the hitting accuracy of sinter compositions and burning through point prediction are more than 85%; the first-grade rate of sinter chemical composition, stability rate of burning through point and stability rate of sintering process are increased by 3%, 9% and 4%, respectively.
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Foundation item: Project (50374080) supported by the National Natural Science Foundation of China; project (030609) supported by the Innovation Project of Postgraduate Education of Central South University
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Fan, Xh., Chen, Xl., Jiang, T. et al. Real-time operation guide system for sintering process with artificial intelligence. J Cent. South Univ. Technol. 12, 531–535 (2005). https://doi.org/10.1007/s11771-005-0117-7
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DOI: https://doi.org/10.1007/s11771-005-0117-7