Non-destructive Real Time Monitoring of the Laser Welding Process

2012 ◽  
Vol 21 (5) ◽  
pp. 764-769 ◽  
Author(s):  
Hana Sebestova ◽  
Hana Chmelickova ◽  
Libor Nozka ◽  
Jiri Moudry
2001 ◽  
Vol 40 (33) ◽  
pp. 6019 ◽  
Author(s):  
Antonio Ancona ◽  
Vincenzo Spagnolo ◽  
Pietro Mario Lugarà ◽  
Michele Ferrara

Author(s):  
Wei Huang ◽  
Shanglu Yang ◽  
Dechao Lin ◽  
Radovan Kovacevic

Nowadays high-strength steels have great applications in different industries due to their good combination of formability, weldability, and high strength-to-weight ratio. To guarantee a high quality without the presence of defects such as partial penetration (PP) in the laser welding of high-strength steels, it is very important to on-line monitor the whole welding process. While optical sensors are widely applied to monitor the laser welding process, we are proposing to use a microphone to acquire the airborne acoustic signals produced during laser welding of high-strength steel DP980. In order to extract valuable information from a very noisy signal acquired in a harsh environment such as industrial welding, spectral subtraction (SS), a noise reduction method is used to process the acquired airborne sound signals. Furthermore, by applying the power spectrum density (PSD) estimation method, the frequency characteristics of the acoustic signals are analyzed as well. The results indicate that the welds in full penetration (FP) and PP produce different signatures of acoustic signals that are characterized with different sound pressure levels and frequency distributions ranging from 500 Hz to 1500 Hz. Based on these differences, two algorithms are developed to distinguish the FP from PP during the laser welding process. A real-time monitoring system is implemented by a LabVIEW-based graphic program developed in this research. A feedback control system that could guarantee the FP will be developed in the near future.


2012 ◽  
Vol 201-202 ◽  
pp. 91-94
Author(s):  
Yan Xi Zhang ◽  
Xiang Dong Gao

Configuration of a molten pool is related to the laser welding quality. Analyzing the configuration of a molten pool is important to monitor the laser welding process. This paper proposes a method of segmentation of a molten pool and its shadow during high power disk laser welding, consequently provides the groundwork for reconstruction of the molten pool and analysis of welding quality. Subsection linear stretching histogram equalization was applied to enhance the contrast of the original images firstly, and then edge detection was used to highlight the edges. After that we used the morphology filtering method to produce the segmentation mask, and then combined the mask with the original images to get the final segmentation results. Also, the proposed method was compared with other traditional methods. The experimental results showed that our method not only could give better segmentation results and process large quantities images automatically, but also overcame the less-segmentation problems of traditional methods.


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