点焊过程信号采集及焊接质量预测研究  

Research on Signal Acquisition and Welding Quality Prediction in Spot Welding Process

作　　者：高子博 郭海欣 李天雷 张莉 周冲 张晨曦 Gao Zibo;Guo Haixin;Li Tianlei;Zhang Li;Zhou Chong;Zhang Chenxi

机构地区：[1]吉利汽车研究院(宁波)有限公司,浙江省宁波市315300

出　　处：《时代汽车》2023年第8期144-146,共3页Auto Time

摘　　要：电阻点焊技术因其低价高效性在汽车行业广泛应用于车身各部件的连接上,点焊的质量直接影响到整个汽车的品质。本文设计了一个点焊质量评分预测模型,通过传感器采集焊接过程中的动态电流、电压等信号,在与焊接质量评分进行相关性分析后选取可以表征焊接质量的特征量,基于机器学习算法建立点焊焊接质量预测模型并进行误差分析。最后选用随机森林算法模型,得到焊接评分预测值,结果表明预测值与真实值的误差可以控制在2%以内,预测较为准确。Resistance spot welding technology is widely used in the automotive industry for the connection of various parts of the car body because of its low cost and high effi ciency,and the quality of spot welding directly aff ects the quality of the entire car.In this paper,a spot-welding quality score prediction model is designed,which collects dynamic current,voltage and other signals in the welding process through sensors,selects the characteristic quantities that can characterize the welding quality after correlation analysis with the welding quality score,and establishes the spot-welding quality prediction model based on the machine learning algorithm and analyzes the error.Finally,the random forest algorithm model is selected to obtain the predicted value of the welding score,and the results show that the error between the predicted value and the real value can be controlled within 2%,and the prediction is more accurate.

关 键 词：电阻点焊 数据采集 机器学习 质量预测 

分 类 号：U46[机械工程—车辆工程]