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高强低伸型涤纶工业丝总拉伸倍率与强度损失率关系分析数据

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浙江省数据知识产权登记平台2023-10-25 更新2024-05-08 收录
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资源简介:
在涤纶工业丝生产过程中,总拉伸倍率会对涤纶工业丝产品的150℃下一个 月的强度损失率产生重大影响,通过采取不同的总拉伸倍率对产品150℃下一个月的强度损失率指标进行测试,经计算建立总拉伸倍率与150℃下一个月的强度损失率的对应关系,进而可以研究各级总拉伸倍率对150℃下一个月的强度损失率的影响规律。根据日常实际试验积累,获得不同总拉伸倍率工艺下的150℃下一个月的强度损失率数据;二、数据分析:总拉伸倍率作为因变量(X),150℃下一个月的强度损失率为自变量(Y), 通过fit()函数对X、Y的值进行模型训练,最后拟合形成总拉伸倍率与150℃下一个月的强度损失率关系的多项式方程模型:Y=b1X +b2X2 +b3X3+b4X4 +e。三、数据应用:利用上述规律,可以通过代入不同总拉伸倍率数值(X)计算得到Y值,即150℃下一个月的强度损失率,进而提升工艺开发效率,指导纺丝工艺调整

During the production of polyester industrial yarns, the total draw ratio exerts a significant impact on the strength loss rate of the products after storage at 150℃ for one month. By testing the strength loss rate index of the products under this condition using different total draw ratios, the corresponding relationship between total draw ratio and the strength loss rate was established via calculation, and the influence law of total draw ratios at various levels on the strength loss rate after 150℃ storage for one month was further explored. Data on the strength loss rate after 150℃ storage for one month under different total draw ratio processes were obtained from accumulated daily practical experiments. 2. Data Analysis: The total draw ratio is taken as the dependent variable (X), while the strength loss rate after 150℃ storage for one month is taken as the independent variable (Y). Model training was performed on the values of X and Y using the fit() function, and finally a polynomial equation model describing the relationship between total draw ratio and the aforementioned strength loss rate was fitted: Y = b₁X + b₂X² + b₃X³ + b₄X⁴ + e. 3. Data Application: Leveraging the obtained rule, the Y value (i.e., the strength loss rate after 150℃ storage for one month) can be calculated by substituting different total draw ratio values (X). This approach can improve the efficiency of process development and guide the adjustment of spinning processes.
提供机构:
浙江古纤道绿色纤维有限公司
创建时间:
2023-09-25
搜集汇总
数据集介绍
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特点
该数据集包含高强低伸型涤纶工业丝的总拉伸倍率与150℃下一个月强度损失率的对应关系数据,共22条记录,旨在通过建立数学模型优化生产工艺。
以上内容由遇见数据集搜集并总结生成
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