Article Article
Fatigue crack measurement based on information entropy of acoustic emission signals

Fatigue crack detection and measurement play an essential role in the remaining useful life (RUL) estimation of sensitive structures. The current use of non-destructive testing (NDT) methods is usually limited to the out-of-service inspections and measurements. The ability to detect structural changes resulting from redistribution of the stress within components while in-service, makes acoustic emission (AE) a desirable NDT method for structural health monitoring (SHM). However, current approaches in AE signal analysis are usually based on some threshold-dependent features such as count and energy of the signals, which limit their utility. This research examines the potential of using a threshold-independent measure of AE signals based on the information content of the signals. The histogram of AE signals is studied to measure the Shannon information entropy. Cumulative information entropy of signals from two independent sensors placed in close vicinity of a crack is compared to two conventional threshold-dependent AE features. It is found that compared to cumulative energy and cumulative count, cumulative AE information entropy is less spatially dependent. The cumulative information entropy is shown to correlate well with crack length. This method provides a novel approach to measure the crack length in general, as shown specifically for aluminum alloy 7075-T6 material, using AE as a well-known NDT technique.

References

[1]S. A. Barter, L. Molent, and R. J. H. Wanhill, “Typical fatigue-initiating discontinuities in metallic aircraftstructures,” International Journal of Fatigue, vol. 41, pp. 11–22, Aug. 2012, doi:10.1016/j.ijfatigue.2011.10.017.

[2]E. Salvati, S. O’Connor, T. Sui, D. Nowell, and A. M. Korsunsky, “A study of overload effect on fatigue crackpropagation using EBSD, FIB–DIC and FEM methods,” Engineering Fracture Mechanics, vol. 167, pp. 210–223, Nov. 2016, doi: 10.1016/j.engfracmech.2016.04.034.

[3]J. C. Newman, E. L. Anagnostou, and D. Rusk, “Fatigue and crack-growth analyses on 7075-T651 aluminumalloy coupons under constant- and variable-amplitude loading,” International Journal of Fatigue, vol. 62, pp.133–143, May 2014, doi: 10.1016/j.ijfatigue.2013.04.020.

[4]E. U. Lee, G. Glinka, A. K. Vasudevan, N. Iyyer, and N. D. Phan, “Fatigue of 7075-T651 aluminum alloyunder constant and variable amplitude loadings,” International Journal of Fatigue, vol. 31, no. 11–12, pp.1858–1864, Nov. 2009, doi: 10.1016/j.ijfatigue.2008.11.013.

[5]N. Iyyer, S. Sarkar, R. Merrill, and N. Phan, “Aircraft life management using crack initiation and crack growthmodels – P-3C Aircraft experience,” International Journal of Fatigue, vol. 29, no. 9–11, pp. 1584–1607, Sep.2007, doi: 10.1016/j.ijfatigue.2007.03.017.

[6]L. Molent and B. Dixon, “Airframe metal fatigue revisited,” International Journal of Fatigue, vol. 131, p.105323, Feb. 2020, doi: 10.1016/j.ijfatigue.2019.105323.

[7]A. P. Mouritz, Introduction to Aerospace Materials. Reston, VA: Woodhead Publishing, 2012.

[8]T. M. Morton, R. M. Harrington, and J. G. Bjeletich, “Acoustic emissions of fatigue crack growth,”Engineering Fracture Mechanics, vol. 5, no. 3, pp. 691–697, Sep. 1973, doi: 10.1016/0013-7944(73)90047-7.

[9]M. Rabiei and M. Modarres, “Quantitative methods for structural health management using in situ acousticemission monitoring,” International Journal of Fatigue, vol. 49, pp. 81–89, Apr. 2013, doi:10.1016/j.ijfatigue.2012.12.001.

[10]M. Rabiei and M. Modarres, “A recursive Bayesian framework for structural health management using onlinemonitoring and periodic inspections,” Reliability Engineering & System Safety, vol. 112, pp. 154–164, Apr.2013, doi: 10.1016/j.ress.2012.11.020.

[11]A. Keshtgar, C. Sauerbrunn, and M. Modarres, “Structural Reliability Prediction Using Acoustic Emission-Based Modeling of Fatigue Crack Growth,” Applied Sciences, vol. 8, no. 8, p. 1225, Jul. 2018, doi:10.3390/app8081225.

[12]C. Sauerbrunn, A. Kahirdeh, H. Yun, and M. Modarres, “Damage Assessment Using Information Entropy ofIndividual Acoustic Emission Waveforms during Cyclic Fatigue Loading,” Applied Sciences, vol. 7, no. 6, p.562, May 2017, doi: 10.3390/app7060562.

[13]M. Chai, Z. Zhang, Q. Duan, and Y. Song, “Assessment of fatigue crack growth in 316LN stainless steel basedon acoustic emission entropy,” International Journal of Fatigue, vol. 109, pp. 145–156, Apr. 2018, doi:10.1016/j.ijfatigue.2017.12.017.

[14]K. Ono, “Structural Health Monitoring of Large Structures Using Acoustic Emission–Case Histories,” AppliedSciences, vol. 9, no. 21, p. 4602, Oct. 2019, doi: 10.3390/app9214602.

[15]S. F. Karimian, M. Modarres, and H. A. Bruck, “A new method for detecting fatigue crack initiation inaluminum alloy using acoustic emission waveform information entropy,” Engineering Fracture Mechanics,vol. 223, p. 106771, Jan. 2020, doi: 10.1016/j.engfracmech.2019.106771.

10

[16]Shannon, Claude Elwood., “A Mathematical Theory of Communication,” Bell system technical journal, vol. 27,no. 3, pp. 379–423, 1948.

[17]J. A. Bannantine, J. J. Comer, and J. L. Handrock, Fundamentals of metal fatigue analysis. Englewood Cliffs,NJ: Prentice hall, 1990.

[18]A. Steuwer, M. Rahman, A. Shterenlikht, M. E. Fitzpatrick, L. Edwards, and P. J. Withers, “The evolution ofcrack-tip stresses during a fatigue overload event,” Acta Materialia, vol. 58, no. 11, pp. 4039–4052, Jun. 2010,doi: 10.1016/j.actamat.2010.03.013.

[19]L. P. Borrego, J. M. Ferreira, J. M. Pinho da Cruz, and J. M. Costa, “Evaluation of overload effects on fatiguecrack growth and closure,” Engineering Fracture Mechanics, vol. 70, no. 11, pp. 1379–1397, Jul. 2003, doi:10.1016/S0013-7944(02)00119-4.

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