摘要
DP590是冷轧高强钢代表性产品之一,对其生产工艺要求极为严格。生产中由于存在带钢边部温降,其边部、中部力学性能波动较大,然而沿带钢宽向的全域力学性能评价是生产工艺参数调整的重要参考。目前采用的抽样、有损检测方法不能满足性能沿带钢宽向整体、全域的评价要求。微磁检测是一种无损、高效的性能评价方法,基于微磁原理,采集得到的多种磁特征与相应位置的力学性能相关。选用首钢顺义冷轧公司生产的DP590高强钢为研究对象,分析了多种微磁特征与其屈服强度、抗拉强度及断后伸长率(A80)之间的相关性,利用神经网络方法建立了相应的定量预测模型,模型预测精度在93%以上,可用于实际生产。
DP590 is one of the representative products of cold rolled high strength steel,and its production process requirements are extremely strict.Due to the temperature drop at the edge of the strip in production,the mechanical properties of the edge and middle of the strip fluctuate greatly,but the evaluation of the mechanical properties of the whole area along the width of the strip is an important reference for the adjustment of production process parameters.At present,the sampling and destructive testing methods used cannot meet the evaluation requirements of the whole and the whole area of the properties along the width of the strip.Micromagnetic detection is a non-destructive and efficient property evaluation method,based on the principle of micromagnetism,and a variety of magnetic features collected are related to the mechanical properties of the corresponding position.DP590 high strength steel produced by Shougang Shunyi Cold Rolling Company was selected as the research object,and the correlation between various micromagnetic characteristics and their yield strength,tensile strength and elongation after break(A80)were analyzed,and the corresponding quantitative prediction model was established by neural network method,and the prediction accuracy of the model was more than 93%,which can be used for actual production.
作者
张阳阳
王林
张栋
李明远
于洋
王贤贤
ZHANG Yangyang;WANG Lin;ZHANG Dong;LI Mingyuan;YU Yang;WANG Xianxian(Research Technology Institute of Shougang Group Co.,Ltd.,Beijing 100043,China;Beijing University of Technology,Beijing 100000,China;Beijing Key Laboratory of Green Recyclable Process for Iron and Steel Production Technology,Beijing 100043,China)
出处
《轧钢》
北大核心
2024年第2期97-102,共6页
Steel Rolling
关键词
冷轧高强钢
力学性能
微磁无损检测
定量预测
神经网络
cold rolled high strength steel
mechanical properties
micromagneticnon-destructive detection
quantitative forecasting
neural networks