Continuous annealing deviation prediction method and device based on neural network
The invention discloses a neural network-based continuous annealing deviation prediction method and apparatus. The method comprises the steps of obtaining historical production data; the reference deviation probability of the strip steel is calculated based on the historical production data, and a d...
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Format | Patent |
Language | Chinese English |
Published |
10.06.2022
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Abstract | The invention discloses a neural network-based continuous annealing deviation prediction method and apparatus. The method comprises the steps of obtaining historical production data; the reference deviation probability of the strip steel is calculated based on the historical production data, and a deviation warning value is determined based on the reference deviation probability according to the deviation correction cylinder position mean value and the strip steel position mean value; establishing a neural network prediction model, and training the neural network prediction model based on historical production data; the trained neural network prediction model is used for predicting the position of each deviation correction cylinder and the position of the strip steel of the to-be-produced strip steel, and when the predicted position of each deviation correction cylinder or the position of the strip steel exceeds a deviation warning value, it is judged that the current to-be-produced strip steel deviates; and |
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AbstractList | The invention discloses a neural network-based continuous annealing deviation prediction method and apparatus. The method comprises the steps of obtaining historical production data; the reference deviation probability of the strip steel is calculated based on the historical production data, and a deviation warning value is determined based on the reference deviation probability according to the deviation correction cylinder position mean value and the strip steel position mean value; establishing a neural network prediction model, and training the neural network prediction model based on historical production data; the trained neural network prediction model is used for predicting the position of each deviation correction cylinder and the position of the strip steel of the to-be-produced strip steel, and when the predicted position of each deviation correction cylinder or the position of the strip steel exceeds a deviation warning value, it is judged that the current to-be-produced strip steel deviates; and |
Author | HE ANRUI LI LIGANG SUN WENQUAN YUAN YUTIAN YUAN TIEHENG |
Author_xml | – fullname: LI LIGANG – fullname: HE ANRUI – fullname: YUAN YUTIAN – fullname: YUAN TIEHENG – fullname: SUN WENQUAN |
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DocumentTitleAlternate | 一种基于神经网络的连退跑偏预测方法及装置 |
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Snippet | The invention discloses a neural network-based continuous annealing deviation prediction method and apparatus. The method comprises the steps of obtaining... |
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SubjectTerms | CALCULATING CHEMISTRY COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING GENERAL DEVICES FOR HEAT TREATMENT OF FERROUS OR NON-FERROUSMETALS OR ALLOYS MAKING METAL MALLEABLE BY DECARBURISATION, TEMPERING OR OTHERTREATMENTS METALLURGY METALLURGY OF IRON MODIFYING THE PHYSICAL STRUCTURE OF FERROUS METALS PHYSICS |
Title | Continuous annealing deviation prediction method and device based on neural network |
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