Rolling Force Prediction in Heavy Plate Rolling Based on Uniform Differential Neural Network
Accurate prediction of the rolling force is critical to assuring the quality of the final product in steel manufacturing. Exit thickness of plate for each pass is calculated from roll gap, mill spring, and predicted roll force. Ideal pass scheduling is dependent on a precise prediction of the roll f...
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | Journal of Control Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2016/6473137 |
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| _version_ | 1832550338564980736 |
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| author | Fei Zhang Yuntao Zhao Jian Shao |
| author_facet | Fei Zhang Yuntao Zhao Jian Shao |
| author_sort | Fei Zhang |
| collection | DOAJ |
| description | Accurate prediction of the rolling force is critical to assuring the quality of the final product in steel manufacturing. Exit thickness of plate for each pass is calculated from roll gap, mill spring, and predicted roll force. Ideal pass scheduling is dependent on a precise prediction of the roll force in each pass. This paper will introduce a concept that allows obtaining the material model parameters directly from the rolling process on an industrial scale by the uniform differential neural network. On the basis of the characteristics that the uniform distribution can fully characterize the solution space and enhance the diversity of the population, uniformity research on differential evolution operator is made to get improved crossover with uniform distribution. When its original function is transferred with a transfer function, the uniform differential evolution algorithms can quickly solve complex optimization problems. Neural network structure and weights threshold are optimized by uniform differential evolution algorithm, and a uniform differential neural network is formed to improve rolling force prediction accuracy in process control system. |
| format | Article |
| id | doaj-art-23403b796d2a42b0a91aadfa09ec726b |
| institution | Kabale University |
| issn | 1687-5249 1687-5257 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Control Science and Engineering |
| spelling | doaj-art-23403b796d2a42b0a91aadfa09ec726b2025-02-03T06:06:58ZengWileyJournal of Control Science and Engineering1687-52491687-52572016-01-01201610.1155/2016/64731376473137Rolling Force Prediction in Heavy Plate Rolling Based on Uniform Differential Neural NetworkFei Zhang0Yuntao Zhao1Jian Shao2National Engineering Research Center for Advanced Rolling Technology, University of Science and Technology Beijing, Beijing 100083, ChinaWISDRI (Wuhan) Automation Co. Ltd., Wuhan 430223, ChinaNational Engineering Research Center for Advanced Rolling Technology, University of Science and Technology Beijing, Beijing 100083, ChinaAccurate prediction of the rolling force is critical to assuring the quality of the final product in steel manufacturing. Exit thickness of plate for each pass is calculated from roll gap, mill spring, and predicted roll force. Ideal pass scheduling is dependent on a precise prediction of the roll force in each pass. This paper will introduce a concept that allows obtaining the material model parameters directly from the rolling process on an industrial scale by the uniform differential neural network. On the basis of the characteristics that the uniform distribution can fully characterize the solution space and enhance the diversity of the population, uniformity research on differential evolution operator is made to get improved crossover with uniform distribution. When its original function is transferred with a transfer function, the uniform differential evolution algorithms can quickly solve complex optimization problems. Neural network structure and weights threshold are optimized by uniform differential evolution algorithm, and a uniform differential neural network is formed to improve rolling force prediction accuracy in process control system.http://dx.doi.org/10.1155/2016/6473137 |
| spellingShingle | Fei Zhang Yuntao Zhao Jian Shao Rolling Force Prediction in Heavy Plate Rolling Based on Uniform Differential Neural Network Journal of Control Science and Engineering |
| title | Rolling Force Prediction in Heavy Plate Rolling Based on Uniform Differential Neural Network |
| title_full | Rolling Force Prediction in Heavy Plate Rolling Based on Uniform Differential Neural Network |
| title_fullStr | Rolling Force Prediction in Heavy Plate Rolling Based on Uniform Differential Neural Network |
| title_full_unstemmed | Rolling Force Prediction in Heavy Plate Rolling Based on Uniform Differential Neural Network |
| title_short | Rolling Force Prediction in Heavy Plate Rolling Based on Uniform Differential Neural Network |
| title_sort | rolling force prediction in heavy plate rolling based on uniform differential neural network |
| url | http://dx.doi.org/10.1155/2016/6473137 |
| work_keys_str_mv | AT feizhang rollingforcepredictioninheavyplaterollingbasedonuniformdifferentialneuralnetwork AT yuntaozhao rollingforcepredictioninheavyplaterollingbasedonuniformdifferentialneuralnetwork AT jianshao rollingforcepredictioninheavyplaterollingbasedonuniformdifferentialneuralnetwork |