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作 者:王少华 宋红兵[1,2] 张万鹏 周超[1,2] 谢航 肖群星[1,2] 邢煜林 王效岗 WANG Shao-hua;SONG Hong-bing;ZHANG Wan-peng;ZHOU Chao;XIE Hang;XIAO Qun-xing;XING Yu-lin;WANG Xiao-gang(Chinese National Engineering Research Center for Petroleum and Natural Gas Tubular Goods Co.,Ltd.,Xi′an 710018,China;CNPC Baoji Petroleum Steel Pipe Co.,Ltd.,Baoji 721008,China;High-end Heavy Machinery Equipment Research Institute,Taiyuan University of Science and Technology,Taiyuan 030024,China)
机构地区:[1]中油国家石油天然气管材工程技术研究中心有限公司,陕西西安710018 [2]中国石油宝鸡石油钢管有限责任公司,陕西宝鸡721008 [3]太原科技大学高端重型机械装备研究院,山西太原030024
出 处:《塑性工程学报》2025年第3期71-77,共7页Journal of Plasticity Engineering
基 金:中国石油天然气集团有限公司前瞻性基础性技术攻关项目(2022DJ1409)。
摘 要:采用实验以及建立BP神经网络的方式,对拉拔理论公式进行验证,研究拉拔成形工艺的制定以及拉拔后焊缝对管材质量的影响。实验结果表明,对于304不锈钢焊管来说,单道次最大减径率为30.4%,伸长率最大为40%;拉拔力与减径率、工作带长度等影响因素成正相关,拉拔速度对拉拔力的影响不大;通过拉拔成形工艺能有效改善焊缝处的晶粒取向,使得管材沿拉拔方向有较好的成形性;建立BP神经网络训练模型,得到回归值R,表明该模型有较好的预测性,从而验证了模型的可行性。The drawing theoretical formula was verified by experiments and the establishment of BP neural networks,the development of the drawing process and the effect of the weld on the quality of the tube after drawing were studied.The experiment results show that for 304 stainless steel welded tube,the maximum diameter reduction rate in a single pass is 30.4%,and the maximum elongation is 40%;the drawing force is positively correlated with influencing factors such as the diameter reduction rate and the length of the working belt,and the drawing speed has little effect on the drawing force.The grain orientation at the weld can be effectively improved through the drawing process,so that the tubes have better formability along the drawing direction.BP neural network training model was established to obtain the regression value R,which shows that the model has good predictability,thus verifying the feasibility of the model.
分 类 号:TG356.53[金属学及工艺—金属压力加工]
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