Research and Application of Model and Control Strategies for Hot Rolled Strip Cooling Process Based on Ultra-Fast Cooling System

Chen, Dong; Li, Y.J.; Yuan, Guo

doi:10.2355/isijinternational.isijint-2019-104

Cited by 5 publications

(4 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This approach eliminates the impact of deviations between steel strip speed and actual speed on temperature control accuracy in the after-rolling cooling control system by continuously updating the speed of steel strip samples in the model and recalculating sample temperatures in real-time. Dong Chen et al [8] proposed a temperature distribution prediction method based on recursive neural networks to address the challenge of rapidly adjusting temperature and water distribution in the cooling section during variable-speed rolling.…”

Section: The Control Strategy For Steel Stripmentioning

confidence: 99%

Research progress of cooling control systems after hot rolling

Chen,

Yao,

Shi

et al. 2024

Fourth International Conference on Mechanical Engineering, Intelligent Manufacturing, and Automation Technology (MEMAT 2023)

View full text Add to dashboard Cite

After-rolling cooling is a crucial technology for regulating the structure and properties of hot-rolled products, providing vital support for the production and quality improvement of hot-rolled strip products. The after-rolling cooling control system is a core factor limiting the development of after-rolling cooling technology. Therefore, conducting research on the after-rolling cooling control system is of significant importance. This paper first analyzes the basic principles of afterrolling cooling and summarizes the current state of research and applications for after-rolling cooling systems. It provides a comprehensive analysis and summarizes the research status and development trends of the after-rolling cooling control system from two aspects: control strategies and heat transfer mathematical models. Temperature control, as a key component of the after-rolling cooling control system, is essential. Precise control of cooling water pressure, flow rate, and the impact of strip speed fluctuations during the cooling process is an effective control strategy to improve the highprecision temperature control of the after-rolling cooling system. A comprehensive analysis of the application of traditional heat transfer models in strip steel heat transfer processes is presented. A comparative analysis of traditional temperature control models and temperature control models with the addition of intelligent algorithms indicates that conventional afterrolling cooling control models can no longer meet the requirements of new after-rolling cooling systems under complex conditions. Therefore, it is necessary to develop more practical and intelligent adaptive control models that align with the characteristics of the new after-rolling cooling systems.

show abstract

Section: The Control Strategy For Steel Stripmentioning

confidence: 99%

Research progress of cooling control systems after hot rolling

Chen,

Yao,

Shi

et al. 2024

Fourth International Conference on Mechanical Engineering, Intelligent Manufacturing, and Automation Technology (MEMAT 2023)

View full text Add to dashboard Cite

show abstract

“…Compared to traditional laminar cooling systems, ultra-fast cooling can effectively break the air film on the surface of steel strip, achieving highly efficient, uniform, and precise cooling for plate and strip of hot rolling. Ultra-fast cooling has become a trend in the development of post-rolling cooling control technology for hot-rolled plate strip steel both domestically and internationally [2][3][4]. The post-rolling cooling control system for plate and strip of hot rolling has the disadvantages of hysteresis, nonlinearity, and complexity.…”

Section: Introductionmentioning

confidence: 99%

The current research status of heat transfer models for hot rolling strip

yao,

Chen,

Shi

et al. 2024

Fourth International Conference on Mechanical Engineering, Intelligent Manufacturing, and Automation Technology (MEMAT 2023)

View full text Add to dashboard Cite

Post-rolling cooling is a critical step in the hot rolling production process, and it has a significant impact on the microstructure and mechanical properties of the final product. This paper first introduces three main modules of research on advanced post-rolling cooling system models. Secondly, it analyzes how to establish high-precision predictive models for post-rolling cooling systems and improve temperature control accuracy. The paper summarizes some strategies and solutions proposed by scholars to address identified issues. By utilizing advanced control theory and deep learning, a postrolling control and cooling predictive model is developed to effectively mine production big data and provide accurate forecasts for the cooling system. In terms of improving temperature control accuracy, scholars have optimized existing self-learning models, resulting in a dual-model parallel system known as VSG+DNN. This system significantly enhances the stability and robustness of the post-rolling cooling system.

show abstract

“…When the cooling process is changed, the residual stress in the hot-rolled strip is bound to change as well. Previous researchers have optimized the cooling process of hot-rolled strip mainly from the microstructure of the product, ignoring the effect of the cooling process on the residual stress [10,11]. Multi-objective optimization of the cooling process of hot-rolled strip, taking into account the microstructure and residual stress, is extremely important for improving the overall quality of the product.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of Low-Alloy Hot-Rolled Strip Cooling Process Based on Gray Correlation Analysis

Xue,

Fei

2024

Metals

View full text Add to dashboard Cite

The residual stress in low-alloy hot-rolled strips seriously affects the use and processing of products. Reducing residual stress is important for improving the product quality of hot-rolled strips. In this paper, the changes in grain size and residual stress of hot-rolled strips under different cooling processes were investigated via thermal simulation experiments and electron backscatter diffraction. It was found that the optimum cooling process solution for single-objective optimization of grain size was a final rolling temperature of 875 °C, a laminar cooling speed of 50 °C/s, and a coiling temperature of 550 °C. When single-objective optimization of residual stress was carried out, the optimal cooling process scheme was 900 °C for final rolling temperature, 20 °C/s for laminar cooling speed, and 625 °C for coiling temperature. The significance of the effect of cooling processes on grain size and residual stress was analyzed based on the extreme deviation of the effect of each cooling process on grain size and residual stress in orthogonal experiments. The results show that the coiling temperature was the most influential factor on grain size and residual stress among the cooling process parameters. The difference was that grain size increased with increasing coiling temperature, and residual stress decreased with increasing coiling temperature. Using both grain size and residual stress as evaluation indicators, a multi-objective optimization of the cooling process for hot-rolled strips was carried out via the gray correlation analysis method. The optimized solution was 875 °C final rolling temperature, 30 °C/s laminar cooling speed, and 625 °C coiling temperature. At this time, the grain size was 4.8 μm, and the KAM (Kernel Average Misorientation) was 0.40°. The grain size under the actual production process scheme was 4.4 μm with a KAM of 0.78°. Compared to the actual production process solution, the multi-objective optimization solution showed little change in grain size, with only a 9% increase and a 49% reduction in KAM. The optimization scheme in this paper could significantly reduce the level of residual stresses while ensuring the fine grain size of hot-rolled strips, thus improving the overall quality of hot-rolled strips.

show abstract

Research and Application of Model and Control Strategies for Hot Rolled Strip Cooling Process Based on Ultra-Fast Cooling System

Cited by 5 publications

References 15 publications

Research progress of cooling control systems after hot rolling

Research progress of cooling control systems after hot rolling

The current research status of heat transfer models for hot rolling strip

Multi-Objective Optimization of Low-Alloy Hot-Rolled Strip Cooling Process Based on Gray Correlation Analysis

Contact Info

Product

Resources

About