With a perspective of democratizing hydrogen-powered vehicles, the automotive industry is working on the improvement of the manufacturing processes with the aim to launch mass production. In order to optimize costs and weight, some hydrogen fuel cell components have been significantly reduced in thickness. This is especially true for the bipolar plates of the proton exchange membrane fuel cells. They consist of two thin stainless steel laser welded plates. However, laser welding may lead to internal defects, which can cause internal or external leaks. Thus, the development of a nondestructive and reliable evaluation method to assess the structural integrity of very thin laser welds on bipolar plates of hydrogen fuel cells is essential. The method must be able to identify the failed joints and describe the characteristics of the failure. Laser weld inspection methods are many and varied. However, none have been evaluated to inspect internal defects in such small welds (about 200 μm wide). This thesis focuses on ultrasonic solutions that could address this issue. Ultrasonic testing has the advantage over other nondestructive testing techniques of being able to inspect the internal structure of welds by locating and characterizing defects.
Two ultrasonic inspection methods were investigated in this thesis: ultrasonic guided waves and acoustic microscopy. The methods were first evaluated using finite element simulation of the emission and propagation of the ultrasonic waves through the various transverse media. These simulations demonstrated the feasibility and limitations of the methods. The analysis of defects that may be found in the welds was thus carried out. Subsequently, experiments were carried out on several samples with various geometries and defects. Based on the results obtained, a conclusion on the feasibility of ultrasonic inspection of fine laser welds on bipolar plates and possible improvements for future work were formulated.
| Date | 23 Jul 2019 |
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| Original language | American English |
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| Awarding Institution | - École de technologie supérieure
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| Supervisor | Pierre Bélanger (Supervisor) |
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Veit, G. (Author),
Bélanger (Supervisor),
23 Jul 2019Student thesis: Master's thesis › Master in Engineering: Automated Manufacturing Engineering