Coiling temperature model self-learning method suitable for fast-paced rolling
The invention relates to a coiling temperature model self-learning method suitable for fast-paced rolling, and belongs to the technical field of hot rolling methods in the metallurgical industry. According to the technical scheme, a water-cooling self-learning target point of a coiling temperature m...
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Main Authors | , , , , , , , , |
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Format | Patent |
Language | Chinese English |
Published |
29.07.2022
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Subjects | |
Online Access | Get full text |
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Summary: | The invention relates to a coiling temperature model self-learning method suitable for fast-paced rolling, and belongs to the technical field of hot rolling methods in the metallurgical industry. According to the technical scheme, a water-cooling self-learning target point of a coiling temperature model is configured, after the self-learning target point passes through a pyrometer, actual temperature data are obtained and are immediately compared with predicted temperature, a water-cooling self-learning coefficient is calculated, upper and lower limits and data are subjected to smoothing processing, and then the data are updated to a model database for coiling temperature model calculation. The method has the beneficial effects that the problem that in an original design, the model self-learning coefficient is updated only after the hot-rolled strip steel completely passes through a pyrometer before coiling, and during fast-paced production, the updated model self-learning coefficient cannot be used for setti |
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Bibliography: | Application Number: CN202210224797 |