Grey box model for predicting the LF end-point temperature of molten steel
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摘要: LF精煉工序在煉鋼過程起著調節溫度的關鍵作用,準確預報LF精煉終點鋼水溫度對實際生產有重要意義.傳統的LF精煉預報模型包括機理模型與黑箱模型.機理預報模型能夠體現各工藝因素對終點鋼水溫度的影響,但由于LF精煉傳熱機理研究尚不完善,依靠機理模型預報終點鋼水溫度,難以達到預期效果;黑箱預報模型能夠準確預報終點鋼水溫度,但不能反映精煉過程各工藝因素對鋼水溫度的影響,尤其當生產工藝條件發生改變時,黑箱模型在應用上會受到限制.本文以方大特鋼LF精煉爐為研究對象,建立一種機理預報模型與黑箱預報模型(BP神經網絡預報模型)相結合的LF精煉終點鋼水溫度灰箱預報模型.該模型既能反映各工藝因素對終點鋼水溫度的影響,又能準確預測終點鋼水溫度,其終點鋼水溫度預測誤差在±5℃以內的命中率可以達到95%以上.Abstract: LF refining process plays an important role in the temperature adjustment of molten steel, and precisely predicting the LF end-point temperature of molten steel is of great importance to actual production. Generally speaking, the prediction models of LF end-point temperature include the mechanism model and the black box model. The mechanism model can reflect the influence of each factor on the end-point temperature of molten steel, but it is dimcult to obtain the expected prediction accuracy due to the limited comprehension of heat transfer in LF refining process. The black box model can usually achieve high prediction accuracy, whereas it does not reveal the effect of each factor. Moreover, the black box model has limited applications when process conditions are changed. Taking LF refining process in Fangda special steel plants as an object of study, this paper establishes a grey box model for predicting the LF end-point temperature of molten steel based on the mechanism model and the black box model. The grey box prediction model can not only indicate the impact of each factor, but also provide the precise prediction of LF end-point temperature. Verification results show that the hit rate of the grey box model is greater than 95% while the predictive error is within ±5℃.
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Key words:
- steelmaking furnaces /
- ladle metallurgy /
- temperature /
- prediction /
- neural networks /
- grey box model
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