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作 者:王志华 陆艳 高凯明 马笑峰 WANG Zhihua;LU Yan;GAO Kaiming;MA Xiaofeng(United Automotive Electronic Systems Co.Ltd.,Shanghai 201206,China)
出 处:《工业加热》2024年第12期17-20,共4页Industrial Heating
摘 要:通过AI热处理建模,建立热力学数据库和磁性能的计算模型,并通过构建多元多相瞬态预报模型,实现精准地找到热处理最佳工艺参数,高效地开发出最佳性能的软磁钢材料。探讨了AI热处理模型建立,开发软磁钢制备过程热力学计算模型,建立数据模型的软磁钢热处理生产全过程工艺参数及产品性能数据库,构建复杂性能同步输出条件下的算法及数学模型,能仿真模拟磁性材料的热处理关键工艺参数,精简热处理DOE试验,助力于软磁钢开发,高效地开发出最佳性能的软磁钢材料。同时探讨了熔炼成分,热轧关键参数,拉拔的减面率,热处理温度和时间等重要参数纳入AI建模中,开发软磁钢-加工变形-热处理全过程一体化的高通量实验方法,实现生产工艺参数高通量筛选,实现产品短周期、低成本研发和高质量制造软磁钢材料。Through AI heat treatment modeling,the thermodynamic database and the calculation model of magnetic performance are established,and through the construction of multiplex multiphase transient prediction model,the best process parameters of heat treatment can be accurately found,and the soft magnetic steel material with the best performance can be developed efficiently.Discuss the AI heat treatment model establishment,develop the preparation of soft magnetic steel thermodynamic calculation model,establish data model of soft magnetic steel heat processing process parameters and product performance database,build the complexity of synchronous output algorithm and mathematical model,can simulate magnetic material heat processing key process parameters,streamline heat treatment DOE test,in the power of the development of soft magnetic steel,efficiently develop the best performance of soft magnetic steel material are discussed.At the same time,the melting composition,hot rolling key parameters,drawing of surface reduction,heat treatment temperature and time and other important parameters into the AI modeling,the development of soft magnetic steel-processing deformation-heat processing process integration of high throughput experimental method,high throughput screening production process parameters,realize product short cycle,low cost research and development and high quality manufacturing of soft magnetic steel materials.
关 键 词:AI建模 热处理 高通量实验 智能制造 软磁材料 生产过程参数 数学模型 DOE
分 类 号:TG155.1[金属学及工艺—热处理]
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