Abstract

Fatigue cracking in sheet metal structures is a common problem during practical applications. It can cause a disastrous failure in the running condition of the structure if it is not addressed in time. A crack can potentially produce acoustic emission (AE) signals during the crack growth event as well as during rubbing/clapping of faying surfaces. All kind of AE signals from the crack provide useful information regarding the condition of the cracked structure. AE signals due to crack faying surface rubbing/clapping need to be identified and separated from AE signals due to other sources. This paper discusses the study of the AE signals generated due to rubbing/clapping of crack faying surfaces. The initial fatigue crack was generated in a sheet metal sample through fatigue loading. The sample was then vibrated at various frequencies using a vibration exciter, and AE signals were generated by vibration induced rubbing/clapping of crack faying surfaces. AE signal signature due to vibration induced rubbing/clapping was identified and studied. AE signal due to rubbing/clapping of sheet metal sample while undergoing an axial static load is also discussed in this paper. The sheet metal sample with fatigue crack was axially loaded using a test cell manufactured in-house for loading sheet metal samples. The samples were vibrated to excite AE signals, and the influence of static load on crack rubbing/clapping AE signals were studied. The vibration-induced crack faying surface motion generated a large number of AE signals. A comparison among these AE signals was performed by using the Pearson correlation of the signals. The first novelty of this research is experimental design and fabrication of an experimental setup for detecting vibration induced rubbing and clapping in fatigue cracked metallic structures. The second novelty of this research is the development of a novel correlation coefficient based approach for comparing a large number of AE signals.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call