PSI - Issue 18

Danilo D’ Angela et al. / Procedia Structural Integrity 18 (2019) 570–576 Danilo D’Angela et al. / Structural Integrity Procedia 00 (2019) 000–000

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Fig. 5. Logarithmic cumulative Shannon Entropy (log Σ H S ) over time-discontinuous data detection related to the A 2 case: five sets of 500 random process curves varying the number of detection windows ( N DW ) and global Entropy curve. 4. Conclusions The results of AE testing of fatigue fracture in metal plates were presented in the paper. The information Entropy of the AE data (AE Entropy) was experimentally investigated as a fracture-sensitive feature for real-time monitoring of metal plates under fatigue fracture. Both Shannon and Kullback-Leibler (i.e., relative Entropy) formulations were considered for the computation of the AE Entropy. Crack initiation and fracture propagation were found to be clearly correlated to the evolution of both Shannon and relative cumulative Entropy. The analysis of the AE Entropy allowed the prediction of the fracture failure. The reliability of the AE Entropy was also checked considering time discontinuous data detection, which is typical of realistic monitoring of structures. Both time-discontinuous detection and reduced total monitored time did not affect the trend of the Entropy evolution. The findings strengthened the robustness of the presented approach. Even if the evaluation of the AE Entropy resulted promising for the application to real monitoring of structures, further studies are necessary to strengthen the experimental damage criteria as well as to define innovative monitoring protocols. Acknowledgements The project was supported by REF funding (2016/2017 and 2017/2018) awarded by Dr Marianna Ercolino. References Aggelis, D.G., Kordatos, E.Z., Matikas, T.E., 2011. Acoustic emission for fatigue damage characterization in metal plates. Mechanics Research Communications 38, 106–110. https://doi.org/10.1016/j.mechrescom.2011.01.011 Al-jumaili, S.K.J., 2016. Damage Assessment In Complex Structures Using Acoustic Emission. Amiri, M., Khonsari, M.M., 2011. On the Role of Entropy Generation in Processes Involving Fatigue. Entropy 14, 24–31. https://doi.org/10.3390/e14010024 Carpinteri, A., Lacidogna, G., Puzzi, S., 2009. From criticality to final collapse: Evolution of the “b-value” from 1.5 to 1.0. Chaos, Solitons & Fractals 41, 843–853. https://doi.org/10.1016/j.chaos.2008.04.010 Chai, M., Zhang, Z., Duan, Q., 2018. A new qualitative acoustic emission parameter based on Shannon’s entropy for damage monitoring. Mechanical Systems and Signal Processing 100, 617–629. https://doi.org/10.1016/j.ymssp.2017.08.007 Chen, Z., Zhou, X., Wang, X., Dong, L., Qian, Y., 2017. Deployment of a Smart Structural Health Monitoring System for Long-Span Arch Bridges: A Review and a Case Study. Sensors 17, 2151. https://doi.org/10.3390/s17092151 D’Angela, D., Ercolino, M., 2018. Finite Element Analysis of Fatigue Response of Nickel Steel Compact Tension Samples using ABAQUS. Procedia Structural Integrity 13, 939–946. https://doi.org/10.1016/j.prostr.2018.12.176 Ercolino, M., Farhidzadeh, A., Salamone, S., Magliulo, G., 2015. Detection of initiation of failure in prestressed strands by cluster analysis of acoustic emissions. Structural Monitoring and Maintenance 2, 339–355. https://doi.org/10.12989/smm.2015.2.4.339 European Committee for Standardization, 2000. EN 2002-16. Aerospace series - Metallic materials; test methods - Part 16: Non-destructive testing, penetrant testing.