基于相关性分析和SSA-BP神经网络的铝合金电阻点焊质量预测
TG453.9; 基于电阻点焊过程中工艺信号特征,在不同间距、不同间隙和不同间距与间隙 3种条件下,引入相关性分析方法分析工艺信号与熔核直径之间的相关性,并建立基于麻雀搜索算法-BP神经网络(sparrow search algorithm-back propagation neural network,SSA-BP)的电阻点焊质量预测模型,将功率、焊接电流、焊接电压和动态电阻作为预测模型输入特征.结果表明,经麻雀搜索算法优化后的BP神经网络在测试集上的决定系数R2、均方误差(mean-square error,MSE)、均方根误差(root mean square error,RMSE)和平...
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| Vydané v: | 焊接学报 Ročník 45; číslo 2; s. 13 - 32 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | Chinese |
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天津大学,材料科学与工程学院,天津, 300350
01.02.2024
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| ISSN: | 0253-360X |
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| Abstract | TG453.9; 基于电阻点焊过程中工艺信号特征,在不同间距、不同间隙和不同间距与间隙 3种条件下,引入相关性分析方法分析工艺信号与熔核直径之间的相关性,并建立基于麻雀搜索算法-BP神经网络(sparrow search algorithm-back propagation neural network,SSA-BP)的电阻点焊质量预测模型,将功率、焊接电流、焊接电压和动态电阻作为预测模型输入特征.结果表明,经麻雀搜索算法优化后的BP神经网络在测试集上的决定系数R2、均方误差(mean-square error,MSE)、均方根误差(root mean square error,RMSE)和平均绝对误差(mean absolute error,MAE)分别为0.95,1.55,1.24和 0.90,均优于BP模型.获得了功率、焊接电流、焊接电压和动态电阻与熔核直径的映射关系,可为焊接的工艺参数设计提供依据. |
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| AbstractList | TG453.9; 基于电阻点焊过程中工艺信号特征,在不同间距、不同间隙和不同间距与间隙 3种条件下,引入相关性分析方法分析工艺信号与熔核直径之间的相关性,并建立基于麻雀搜索算法-BP神经网络(sparrow search algorithm-back propagation neural network,SSA-BP)的电阻点焊质量预测模型,将功率、焊接电流、焊接电压和动态电阻作为预测模型输入特征.结果表明,经麻雀搜索算法优化后的BP神经网络在测试集上的决定系数R2、均方误差(mean-square error,MSE)、均方根误差(root mean square error,RMSE)和平均绝对误差(mean absolute error,MAE)分别为0.95,1.55,1.24和 0.90,均优于BP模型.获得了功率、焊接电流、焊接电压和动态电阻与熔核直径的映射关系,可为焊接的工艺参数设计提供依据. |
| Abstract_FL | Based on the characteristics of the process signals in the resistance spot welding process,three working condi-tions of different spacing,different gaps and different spacing and gaps are analyzed,and correlation analysis is introduced to extract the correlation between the process signals and the dia-meter of nugget.A resistance spot welding quality prediction model based on Sparrow Search Algorithm-Back Propagation Neural Network(SSA-BP)was established,and power,weld-ing current,welding voltage and dynamic resistance are used as input features of the prediction model.The results show that the BP neural network optimized by the sparrow search al-gorithm outperforms the BP model on the test set with R2,MSE,RMSE and MAE of 0.95,1.55,1.24 and 0.90,respect-ively.It is also determined that there exists a mapping relation-ship between power,welding current,welding voltage and dy-namic resistance and the diameter of the nugget,which provides a basis for the design of process parameters for weld-ing. |
| Author | 罗震 董建伟 胡建明 |
| AuthorAffiliation | 天津大学,材料科学与工程学院,天津, 300350 |
| AuthorAffiliation_xml | – name: 天津大学,材料科学与工程学院,天津, 300350 |
| Author_FL | LUO Zhen DONG Jianwei HU Jianming |
| Author_FL_xml | – sequence: 1 fullname: DONG Jianwei – sequence: 2 fullname: HU Jianming – sequence: 3 fullname: LUO Zhen |
| Author_xml | – sequence: 1 fullname: 董建伟 – sequence: 2 fullname: 胡建明 – sequence: 3 fullname: 罗震 |
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| ClassificationCodes | TG453.9 |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DOI | 10.12073/j.hjxb.20230226001 |
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| DocumentTitle_FL | Quality prediction of aluminum alloy resistance spot weld-ing based on correlation analysis and SSA-BP neural net-work |
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| Keywords | resistance spot welding correlation analysis BP neural network 熔核直径 麻雀搜索算法 相关性分析 BP神经网络 nugget diameter sparrow search algorithm 电阻点焊 |
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| PublicationTitle | 焊接学报 |
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| Publisher | 天津大学,材料科学与工程学院,天津, 300350 |
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| Snippet | TG453.9; 基于电阻点焊过程中工艺信号特征,在不同间距、不同间隙和不同间距与间隙 3种条件下,引入相关性分析方法分析工艺信号与熔核直径之间的相关性,并建立基于麻雀搜索算... |
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| Title | 基于相关性分析和SSA-BP神经网络的铝合金电阻点焊质量预测 |
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