Mechanical properties prediction of tire cord steel via multi-stage neural network with time-series data

IF 1.7 3区 材料科学 Q2 METALLURGY & METALLURGICAL ENGINEERING Ironmaking & Steelmaking Pub Date : 2022-12-25 DOI:10.1080/03019233.2022.2152597
Long Chen, Fei He
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Abstract

ABSTRACT Cord steel is a kind of high-quality wire, whose mechanical properties will affect the safety and service life of tire. Therefore, the prediction model of mechanical properties during production process is very important to ensure the quality stability. In the paper, the Multi-Stage Neural Network with Time-Series data (MSNNTS) is proposed to mine the rich information of high-resolution time-series data and represent multistage process to achieve accurate mechanical properties prediction. According to the results, the best mean relative error, for tensile strength prediction, is about 1.25% and the hit rate with 3% error limit is about 98% on the testing set. It also obtains good results in predicting reduction of area. The results show that the method is of great significance to improve the quality stability and uniformity of cord steel.
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基于时序数据的多级神经网络预测轮胎帘子线钢力学性能
帘线钢是一种高质量的钢丝,其力学性能将影响轮胎的安全性和使用寿命。因此,建立生产过程中力学性能的预测模型对保证质量稳定具有重要意义。本文提出了具有时间序列数据的多阶段神经网络(MSNNTS),以挖掘高分辨率时间序列数据中丰富的信息,并表示多阶段过程,从而实现准确的力学性能预测。结果表明,在试验台上,抗拉强度预测的最佳平均相对误差约为1.25%,误差极限为3%的命中率约为98%。在预测面积减少方面也取得了良好的效果。结果表明,该方法对提高帘线钢的质量稳定性和均匀性具有重要意义。
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来源期刊
Ironmaking & Steelmaking
Ironmaking & Steelmaking 工程技术-冶金工程
CiteScore
3.70
自引率
9.50%
发文量
125
审稿时长
2.9 months
期刊介绍: Ironmaking & Steelmaking: Processes, Products and Applications monitors international technological advances in the industry with a strong element of engineering and product related material. First class refereed papers from the international iron and steel community cover all stages of the process, from ironmaking and its attendant technologies, through casting and steelmaking, to rolling, forming and delivery of the product, including monitoring, quality assurance and environmental issues. The journal also carries research profiles, features on technological and industry developments and expert reviews on major conferences.
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