焊管2026，Vol.49Issue(1)：28-35,8.DOI:10.19291/j.cnki.1001-3938.2026.01.003
基于机器学习的X80管线钢环焊缝热影响区硬度预测模型
Machine Learning based Hardness Prediction Model for Girth Weld Heat Affected Zone of X80 Pipeline Steel
摘要
Abstract
To investigate the characteristics of the heat-affected zone(HAZ)in X80 pipeline steel girth weld joints,and obtain the nonlinear relationship between thermal cycle data and HAZ hardness,precise predictions of HAZ hardness were conducted.Using X80 pipeline steel as the research subject,thermal simulation tests were performed.Microhardness tests were conducted on the thermal simulation specimens to determine the hardness values and the hardness distribution of the HAZ in full scale girth weld joints.Based on the hardness database of thermal simulation specimens,a multi-index comprehensive evaluation was carried out to optimize the support vector regression algorithm using particle swarm optimization,thereby constructing a hardness prediction model.Furthermore,characteristic data of the thermal cycle were acquired through finite element modeling of the girth weld.Input the hardness prediction model to predict the actual hardness distribution in the heat-affected zone.Results showed that the relative errors in the predicted mean hardness for fully automatic welding and combined automatic welding were 4.70%and 6.01%,respectively.The model demonstrated high accuracy and could provide guidance for optimizing welding processes,ensuring the inherent safety of high-grade pipelines.关键词
X80管线钢/环焊缝热影响区/热模拟试验/硬度预测/机器学习Key words
X80 pipeline steel/girth weld heat-affected zone/thermal simulation experiment/hardness prediction/machine learning分类
矿业与冶金引用本文复制引用
蒋庆梅,邓丽阳,张小强,贡誉,张东,甄莹,刘啸奔..基于机器学习的X80管线钢环焊缝热影响区硬度预测模型[J].焊管,2026,49(1):28-35,8.基金项目
国家重点研发计划"中俄管道重大风险防控与安全保障关键技术"(项目编号2022YFC3070100) （项目编号2022YFC3070100）
应急管理部重点科技计划"油气管网系统环境安全重大风险防控关键技术研究"(项目编号2024EMST090903) （项目编号2024EMST090903）
北京市科协"青年人才托举工程"项目"高钢级管道环焊缝可靠性评价方法研究"(项目编号BYESS2023261). （项目编号BYESS2023261）
