基于XGBoost算法的铜杆性能检测研究
Research on Performance Testing of Copper Rod Based on XGBoost Algorithm
张萱 1高义 1王松兴 1朱明彪 1桂志平 1杨卫良1
作者信息
- 1. 江西康成特导新材股份有限公司,江西 鹰潭 335000
- 折叠
摘要
为了对工业生产的铜杆的制备性能进行优化,研究设计了一种基于XGBoost算法的铜杆性能检测模型.以某铜厂2023年上半年的铜杆生产数据为基础,数据经过处理后提取与铜杆生产工艺相关的特征,结合XGBoost算法构建出铜杆性能检测模型.结果显示,铜杆拉伸强度真实值和检测值的最大误差约为1.1 MPa,铜杆延展性能的真实值和检测值最大误差约为0.5％,说明该模型具有极高的检测精度.利用该模型优化铜杆性能的实验中发现,向原料铜中添加w(La)为0.000 18％～0.000 22％时,可将铜杆的拉伸强度和延展性能分别维持在375～380 MPa和3.0％～3.2％.由此可见,构建的铜杆性能检测模型可以精确检测铜杆性能并优化生产工艺参数,同时为同类型的产品检测和优化提供技术支持.
Abstract
In order to optimize the preparation performance of copper rods in industrial production,a copper rod performance detection model based on XGBoost algorithm was studied and designed.Based on the copper rod production data of a certain copper factory in the first half of 2023,the data is processed to extract features related to the copper rod production process,and combined with the XGBoost algorithm to construct a copper rod performance detection model.The results showed that the maximum error between the true value and the detection value of the tensile strength of the copper rod was about 1.1 MPa,and the maximum error between the true value and the detection value of the tensile performance of the copper rod was about 0.5％,indicating that the model has extremely high detection accuracy.In the experiment of optimizing the performance of copper rods using this model,it was found that adding w(La)to the raw copper at a range of 0.000 18％to 0.000 22％can maintain the tensile strength and ductility of copper rods at 375～380 MPa and 3.0％to 3.2％,respectively.From this,it can be seen that the constructed copper rod performance testing model can accurately detect the performance of copper rods and optimize production process parameters,while providing technical support for the testing and optimization of similar products.
关键词
铜杆/检测模型/拉伸强度/延展性能/工艺参数Key words
copper rod/detection model/tensile strength/extension performance/process parameters引用本文复制引用
出版年
2024
NETL
NSTL
万方数据