织构对无取向硅钢磁性能影响的主成分回归分析

• 作 者: 陈凌峰 赵志毅 王宝明 赵东红 黄赛
• 机 构: 北京科技大学材料科学与工程学院,首钢迁安钢铁有限责任公司冷轧部,北京科技大学数理学院,
• 出 处: 热加工工艺
• 发表日期: 2015年16期
• 关键词: 主成分回归分析 无取向硅钢 组分含量 铁损 线性关系 影响因素 定量研究 主成分分析 纵截面 电子背散射衍射

采用电子背散射衍射技术测定50SW1300冷轧无取向硅钢中不同织构组分的含量,利用主成分回归分析法,综合研究{100}面织构、{110}<001>Goss织构、{111}<110>织构、{111}<112>织构组分含量对无取向硅钢磁性能的影响。结果表明:利用主成分回归分析法能够从多个影响因素中获取主要的信息来定量研究多变量问题,揭示不同织构组分含量对无取向硅钢磁性能的影响规律。结果表明,不同织构组分含量与铁损之间并无线性关系;轧面、纵截面上{100}面织构、{110}<001>Goss织构组分含量的增加均能改善无取向硅钢的磁感,而{111}<110>织构、{111}<112>织构组分的增加会劣化磁感,且在优化磁感时,增加{100}面织构、{110}<001>Goss织构组分含量比降低{111}<110>织构、{111}<112>织构组分含量效果要好。

Electronic backscatter diffraction was used to determine the content of different textured components in 50SW1300 cold-rolled non-oriented silicon steel. Principal component regression analysis was used to study the {100} plane texture, {110} <001> Goss texture, {111 } <110> textures and {111} <112> texture components on the magnetic properties of non-oriented silicon steel. The results show that using principal component regression analysis can obtain the main information from multiple influencing factors to quantitatively study the multivariable problem and reveal the influence of different textured components on the magnetic properties of non-oriented silicon steel. The results show that there is no linear relationship between the content of the different textured components and the iron loss, and the increase of {100} plane texture and {110} <001> Goss texture components on the rolling surface and the longitudinal section can all be improved The orientation of {111} <110> texture and the increase of {111} <112> texture components will degrade the magnetic induction. When the magnetic induction is optimized, the {100} } <001> Goss texture component content is lower than {111} <110> texture, {111} <112> texture component content effect is better.