基于BP神经网络的激光叠焊焊接接头熔深预测研究
程志义1周广浩1程炜晴2姜岩1姜娜1
Research on Laser Lap Weld Depth Prediction Based on BP Neural Network
CHENG ZhiyiZHOU GuanghaoCHENG WeiqingJIANG YanJIANG Na
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作者信息:1.中车长春轨道客车股份有限公司质量保证部,130062,长春；
2.电子科技大学格拉斯哥学院，611731，成都
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Affiliation:CRRC Changchun Railway Vehicles Co., Ltd., 130062, Changchun, China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.2020.02.035
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中图分类号/CLCN:F570.73
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栏目/Col:应用技术
摘要:
分析了激光功率、焊接速度和离焦量3个焊接参数的变化对激光叠焊焊接接头熔宽和熔深的影响，证明了熔宽和熔深的变化规律具有一致性。利用焊接参数和超声波检测信号建立了BP神经网络模型，模型验证结果表明，熔深预测的最大偏差不超过0.1 mm，最大相对误差为3%。所建立的BP神经网络预测模型满足实际应用中对激光叠焊焊接接头熔深测量要求。
Abstracts:
The influence of laser power, welding speed and defocusing distance on laser lap weld width and depth was analyzed. It is proved that the changing patterns of weld width and depth are consistent. A BP neural network prediction model for laser weld depth is established by the welding parameters and ultrasonic testing signals. The verification results of the model show that the maximum deviation of the weld depth prediction is less than 0.1 mm, and the maximum relative error is 3%, which meets the measuring requirements of laser weld depth in practical applications.
引文 / Ref:
程志义，周广浩，程炜晴，等.基于BP神经网络的激光叠焊焊接接头熔深预测研究[J].城市轨道交通研究，2020，23（2）：141.
CHENG Zhiyi，ZHOU Guanghao，CHENG Weiqing，et al.Research on Laser Lap Weld Depth Prediction Based on BP Neural Network[J].Urban mass transit，2020，23（2）：141.
CHENG Zhiyi，ZHOU Guanghao，CHENG Weiqing，et al.Research on Laser Lap Weld Depth Prediction Based on BP Neural Network[J].Urban mass transit，2020，23（2）：141.
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