PIDAS热处理产品与工艺辅助设计技术研究

Research on PIDAS heat treatment products and process aided design technology

基于厚板部的热处理工艺后钢板性能的预测需求,进行PIDAS热处理产品与工艺辅助设计技术研究。模块设计思路为:通过相关性分析、变量选择等方法进行数据处理,运用机器学习方法进行回归分析并运用分类模型进行修正;通过区间估计的方法得到预测区间,建立反向调整的逻辑,根据性能要求推荐重要工艺参数。研究表明,PIDAS热处理产品与工艺辅助设计对钢板力学性能有很好的控制效果,有工业应用价值。

Based on the predicted demand for the performance of the steel plate after the heat treatment process of the heavy plate department,carry out the research on the PIDAS heat treatment product and process aided design technology.After data processing and feature engineering,machine learning is used for regression analysis and the classification model is used for correction.The prediction interval is obtained through the method of interval estimation,and the logic of reverse adjustment is established at the same time,and important process parameters are recommended according to the mechanical performance requirements.Research has shown that it has a good predictive effect on mechanical properties,and has industrial application value.