Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-20T03:42:46.922Z Has data issue: false hasContentIssue false
  • English
  • Français

An integrated approach to local ultrasonic monitoring of fastener hole fatigue cracks

Published online by Cambridge University Press:  03 February 2016

A. C. Cobb ,
J. E. Michaels  and
T. E. Michaels
A. C. Cobb
Affiliation:
Southwest Research Institute, San Antonio, Texas, USA
J. E. Michaels
Affiliation:
jennifer.michaels@ece.gatech.edu, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
T. E. Michaels
Affiliation:
jennifer.michaels@ece.gatech.edu, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
Get access Rights & Permissions [Opens in a new window]

Abstract

Ultrasonic nondestructive evaluation methods are routinely used to detect and size fatigue cracks near fastener holes in aircraft structures as a part of scheduled maintenance. In contrast, statistical crack propagation models provide an estimate of the expected fatigue life assuming a known crack size and future fatigue loadings. Here an integrated approach for in situ diagnosis and prognosis of fastener hole fatigue cracks is proposed and implemented that incorporates both ultrasonic monitoring and crack growth laws. The sensing method is an ultrasonic angle beam technique, and cracks are automatically detected from the ultrasonic response. An extended Kalman filter is applied to combine ultrasonically estimated crack sizes with a crack growth law, effectively using the time history of the ultrasonic results rather than only the most recent measurement. A natural extension of this method is fatigue life prognosis. Results from fatigue tests on 7075-T651 aluminium coupons show improved crack size estimates as compared to those obtained from ultrasonic measurements alone, and also demonstrate the capability of predicting the remaining life. This approach for fatigue crack detection, sizing and prognosis is an example of a general strategy for in situ monitoring of structural damage whereby improved results are achieved from the integration of noisy measurements with imperfect crack growth models.

Type
Research Article
Information
The Aeronautical Journal , Volume 113 , Issue 1150: Flight structures fundamental research in the United States of America: A Special Issue – PART II , December 2009 , pp. 775 - 788
Copyright
Copyright © Royal Aeronautical Society 2009 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Thompson, R.B. and Thompson, D.O., Ultrasonics in nondestructive evaluation, 1985, Proceedings of the IEEE, 73, (12), pp 1716–1755.Google Scholar
2. Grooteman, F., A stochastic approach to determine lifetimes and inspection schemes for aircraft components, Int J of Fatigue, 2008, 30, pp 138–149.Google Scholar
3. Rose, J.L. and Schlemm, H., Equivalent flaw size measurements and characterization analysis, Materials Evaluation, 1976, 34, pp 1–8.Google Scholar
4. Silk, M.G., The transfer of ultrasonic energy in the diffraction technique for crack sizing, NDT Int, 1976, 9, pp 290–297.Google Scholar
5. Ravenscroft, F.A., Newton, K. and Scruby, C.B., Diffraction of ultrasound by cracks: comparison of experiment with theory, Ultrasonics, 1991, 29, pp 29–37.Google Scholar
6. Silk, M.G., The determination of crack penetration using ultrasonic surface waves, Ultrasonics, 1979, 17, pp 113–120.Google Scholar
7. Cook, D.A. and Berthelot, Y.H., Detection of small surface breaking fatigue cracks in steel using scattering of Rayleigh waves, NDT&E Int, 2001, 34, pp 483–492.Google Scholar
8. Keller, E. and Ray, A., Real-time health monitoring of mechanical structures, Structural Health Monitoring, 2003, 2, (3), pp 191–203.Google Scholar
9. Mi, B., Michaels, J.E. and Michaels, T.E., An ultrasonic method for dynamic monitoring of fatigue crack initiation and growth, J Acoustical Soc of America, 2006, 119, (1), pp 74–85.Google Scholar
10. Kim, J.-Y., Yakovlev, V.A. and Rokhlin, S.I., Surface acoustic wave modulation on a partially closed fatigue crack, J Acoustical Soc of America, 2004, 115, (5), pp 1961–1972.Google Scholar
11. Harri, K., Guillaume, P. and Vanlanduit, S., On-line monitoring of cracks using ultrasonic ‘multisine’ surface waves, 2006, Proceedings of the 9th European Conference on Non-Destructive Testing, pp Th.1.5.3:1–7.Google Scholar
12. Chang, Z. and Mal, A., Scattering of Lamb waves from a rivet hole with edge cracks, Mechanics of Materials, 1999, 31, (3), pp 197–204.Google Scholar
13. Fromme, P. and Sayir, M., Detection of cracks at rivet holes using guided waves, Ultrasonics, 2002, 40, (2), pp 199–203.Google Scholar
14. Jarmer, G.J.S. and Todd, M.D., Crack detection diagnostics using ultrasonic insonification and pattern recognition, Kundu, T. (Ed), Proceedings of SPIE, Health Monitoring and Smart Nondestructive Evaluation of Structural and Biological Systems III, 2009, 7295, SPIE, Bellingham, Washington, pp 72950T:1–8.Google Scholar
15. Staszewski, W.J., Lee, B.C. and Traynor, R., Fatigue crack detection in metallic structures with Lamb waves and 3D laser vibrometry, Measurement Science and Technology, 2007, 18, 187, pp 727–739.Google Scholar
16. Lu, Y., Ye, L., Su, Z. and Huang, N., Quantitative evaluation of crack orientation in aluminum plates based on Lamb waves, Smart Materials and Structures, 2007, 16, pp 1907–1914.Google Scholar
17. Michaels, J.E., Michaels, T.E. and Martin, R.S., Analysis of global ultrasonic sensor data from a full scale wing panel test, Thompson, D. O. and Chimenti, D.E. (Eds), Review of Progress in Quantitative Nondestructive Evaluation, 2009, 28A, American Institute of Physics, New York, pp 950–957.Google Scholar
18. Cobb, A.C., Michaels, J.E. and Michaels, T.E., An automated time frequency approach for ultrasonic monitoring of fastener hole cracks, NDT&E International, 2007, 40, pp 525–536.Google Scholar
19. Gupta, S., Ray, A. and Keller, E., Symbolic time series analysis of ultrasonic data for early detection of fatigue damage, Mechanical Systems and Signal Processing, 2007, 21, pp 866–884.Google Scholar
20. Gupta, S., Ray, A. and Keller, E., Online fatigue damage monitoring by ultrasonic measurements: A symbolic dynamics approach, Int J of Fatigue, 2007, 29, pp 1100–1114.Google Scholar
21. Ray, A. and Tangirala, S., Stochastic modeling of fatigue crack dynamics for on-line failure prognosis, IEEE Transactions on Control Systems Technology, 1996, 4, (4), pp 443–451.Google Scholar
22. Orchard, M.E. and Vachtsevanos, G.J., A particle filtering approach for on-line prognosis in a planetary gear plate, Int J of Fuzzy Logic and Intelligent Systems, 2007, 7, (4), pp 22–227.Google Scholar
23. Kulkarni, S.S., Sun, L., Moran, B., Krishnaswamy, S. and Achenbach, J.D., A probabilistic method to predict fatigue crack initiation, Int J of Fracture, 2006, 137, pp 9–17.Google Scholar
24. Kulkarni, S.S. and Achenbach, J.D., Strutural health monitoring and damage prognosis in fatigue, Structural Health Monitoring, 2008, 7, (1), pp 37–49.Google Scholar
25. Michaels, J.E., Michaels, T.E. and Mi, B., An ultrasonic angle beam method for in situ sizing of fastener hole cracks, J Nondestructive Evaluation, 2006, 25, (1), pp 3–16.Google Scholar
26. Michaels, J.E., Michaels, T.E., Cobb, A.C. and Kacprzynski, G.J., Ultrasonic sensing and life prediction for the DARPA structural integrity prognosis system, in: Thompson, D.O. and Chimenti, D.E. (Eds), Review of Prog in Quantitative Nondestructive Evaluation, 2006, 26B, American Institute of Physics, New York, pp 1453–1460.Google Scholar
27. Papazian, J., Silberstein, R., Welsh, G., Grundy, D., Craven, C., Evans, L., Goldfine, N., Michaels, J., Michaels, T., Li, Y. and Laird, C., Sensors for monitoring early stage fatigue cracking, Int J Fatigue, 2007, 29, pp 1668–1680.Google Scholar
28. Michaels, T.E., Michaels, J.E. and Cobb, A.C., Simultaneous ultrasonic monitoring of crack growth and dynamic loads during a full scale fatigue test of an aircraft wing, Thompson, D.O. and Chimenti, D.E. (Eds), Review of Prog in Quantitative Nondestructive Evaluation, 2009, 28B, American Institute of Physics, New York, pp 1458–1465.Google Scholar
29. Moon, T.K. and Stirling, W.C., Mathematical Methods and Algorithms for Signal Processing, 2000, 1st Edition, Pearson Education.Google Scholar
30. Hayes, M., Statistical Digital Signal Processing and Modeling, 7th Edition, 1996, John Wiley and Sons.Google Scholar
31. MIL-HDBK-1823, Nondestructive evaluation system reliability assessment, 1999, Department of Defense.Google Scholar
32. Paris, P. and Erdogan, F., A critical analysis of crack propagation laws, J Basic Eng, 1963, 85, pp 528–534.Google Scholar
33. Dowling, N.E., Mechanical Behavior of Materials, 10th Edition, 1993, Prentice-Hall, New Jersey.Google Scholar
34. Shah, R.C., Stress intensity factors for through and part-through cracks originating at fastener holes, Mech Crack Growth, 1976, ASTM STP 590, ASTM, Philadelphia, pp 429–459.Google Scholar
35. Murakami, Y. (Ed). Stress Intensity Factors Handbook, 1987, Pergamon Press, Oxford, UK.Google Scholar
36. Lucáš, P., Stress intensity factor for small notch-emanated cracks, Eng Fracture Mech, 1987, 26, (3), pp 471–473.Google Scholar
37. Newman, J.C. Jr. Fatigue-life prediction methodology using a crack-closure methodology, J Eng Materials and Tech, 1995, 117, pp 433–439.Google Scholar
38. Skorupa, M., Machniewicz, T., Schijve, J. and Skorupa, A., Application of the strip-yield model from the NASGRO software to predict fatigue crack growth in aluminium alloys under constant and variable amplitude loading, Engineering Fracture Mech, 2007, 74, pp 291–313.Google Scholar
39. Mohanty, S., Das, S., Chattopadhyay, A. and Peralta, P., Gaussian process time series model for life prognosis of metallic structures, Int J Intelligent Material Systems and Structures, 2009, 20, pp 887–896.Google Scholar
40. Haroon, M. and Adams, D.E., Development of component-level damage evolution models for mechanical prognosis, J Applied Mech, 2008, 75, pp 021017:1–15.Google Scholar
41. Ray, A. and Patankar, R., A stochastic model of fatigue crack propagation under variable-amplitude loading, Eng Fracture Mech, 1999, 62, pp 477–493.Google Scholar
42. Hilands, T.W. and Thomopoulos, S.C.A., Nonlinear filtering methods for harmonic retrieval and model order selection in Gaussian and non-Gaussian noise, IEEE Transactions on Signal Processing, 1997, 45, (1), pp 982–995.Google Scholar
43. Jetto, L., Longhi, S. and Venturini, G., Development and experimental validation of an adaptive extended Kalman filter for the localization of mobile robots, IEEE Transactions on Robotics and Automation, 1997, 15, (2), pp 219–229.Google Scholar
44. Hoffman, P. and Hurtado, J., Airframe integrity based on Bayesian approach, 2006, Proceedings of the Annual Reliability and Maintainability Symposium, pp 630–635, IEEE, Piscataway, New Jersey.Google Scholar