Penetration fluctuation monitoring of aluminum-copper laser lap welding based on optical coherence tomography and spectral signals
Abstrak
Laser lap welding of dissimilar Al–Cu metals is increasingly applied in electrical interconnections and power battery manufacturing for new energy vehicles due to the high conductivity of copper and the lightweight, high-strength properties of aluminum. However, their distinct physical characteristics, including melting point, thermal conductivity, and laser absorptivity, induce severe penetration depth fluctuations during welding, which deteriorate joint performance. To address this challenge, a multi-signal fusion approach is proposed for predicting penetration fluctuations. Real-time keyhole depth signals are captured via optical coherence tomography (OCT), while electron temperature is derived from plasma plume spectra, forming multi-source descriptors of molten pool dynamics. After feature extraction, a backpropagation neural network (BPNN) is developed. Experimental validation shows that the model achieves an average prediction error of 0.0448 mm. The proposed method provides a reliable tool for quality control and defect prevention in Al–Cu dissimilar metal laser welding.
Penulis (4)
Shixuan Li
Leshi Shu
Ping Jiang
Chu Han
Akses Cepat
PDF tidak tersedia langsung
Cek di sumber asli →- Tahun Terbit
- 2025
- Bahasa
- en
- Sumber Database
- Semantic Scholar
- DOI
- 10.1109/MAEIE68099.2025.11405916
- Akses
- Open Access ✓