Aluminum alloys are widely spread in many industrial sectors due to their desirable characteristics as low density, good formability, high specific strength, and good resistance to corrosion. Autogenous laser welding is a technology that enables the use of these materials in the industrial process due to its high repeatability, reliability, and ease of automatization. In particular, in automotive applications, Al-alloys are welded in lap-joint configurations with more than 2 layers of material. The welding condition should be monitored in order to detect the complete penetration, hence guaranteeing the appropriate weld resistance. The use of non-invasive and coaxial monitoring solutions is highly desirable for the identification of weld defects during the process. This study investigates an autogenous laser welding process and monitoring in the double lap-joint configuration of sheets of AA 5754. First, the process parameters are investigated to identify the geometrical and mechanical characteristics of the resultant welding seams at different process conditions. The employed high-brilliance 3 kW fiber laser provided the possibility of reading the back-reflected light signal from an internal photodiode. The capability of this signal to be used as a non-invasive, coaxial, and remote monitoring system in order to predict the process outcome was tested. In the experiments the back-reflected light intensity could be correlated to the weld seam width at the second interface, as well as the strength of the joint to shear. Finally, the monitoring signal behavior was demonstrated under simulated weld defect conditions. The results show that weld anomalies such as lack of penetration, misalignment, and gap formation can be sensed through the monitoring approach.
CITATION STYLE
Garavaglia, M., Demir, A. G., Zarini, S., Victor, B. M., & Previtali, B. (2020). Fiber laser welding of AA 5754 in the double lap-joint configuration: process development, mechanical characterization, and monitoring. International Journal of Advanced Manufacturing Technology, 111(5–6), 1643–1657. https://doi.org/10.1007/s00170-020-06128-6
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