The probability of acoustic emission (AE) detection associated with the fatigue crack extension in steel bridge component
seems to be an intractable problem because of the complexity of the AE sources. It is an ongoing challenge because the
AE sensors are not only sensitive to the AE signals but also the mechanical noises; and is very difficult to interpret the real
signals related to microcrack extension. Probability of detection may also be influenced by the medium of wave propagation,
threshold setting, sensitivity and frequency range of the sensors and the source–to–sensor distance. This paper presents the
probability of AE detection associated with fatigue crack extension in steel bridge element as a function of stress intensity
range. The real AE events associated with the fatigue crack extension are screened by using different filtering techniques.
For simplicity, the Poisson distribution is employed to calculate the probability of AE detection associated with fatigue crack
extension at different level of fatigue crack which may later facilitate to determine the priorities of instrumentation to the real
in-service bridges for structural health monitoring and hence reduces the cost of monitoring.
1. AAR, Procedure for acoustic emission evaluation of tank cars and IM-101 tanks, Issue 8. 1999, Operation and
Maintenance Department, Association of American Railroads.
2. Folch, L.C.A., et al., “Application of the Local Damage Mechanics Approach to Transition Temperature Behaviour in
Steels,” UMIST, 1997.
3. Folch, L.C.A. and F.M. Burdekin, “Application of coupled brittle–ductile model to study correlation between Charpy
energy and fracture toughness values,” Engineering Fracture Mechanics, 63(1): p. 57-80.
4. Hamstad, M.A. and J.D. McColskey, “Detectability of Slow Crack Growth in Bridge Steels by Acoustic Emission,”
Materials Evaluation, Vol. 57, No. 11, pp.1165-1174, 1999.
5. Hossain, M., P. Ziehl, J. Yu, J. Caicedo and F. Matta, “Source Mechanisms of Acoustic Emission during Fatigue Crack
Growth in Steel Bridge Material,” Proc. 5th European Conference on Structural Control (EACS 2012), June 18-20,
2012, Genoa, Italy, paper#158, 7 p.
6. Hossain, M., J. Yu, P. Ziehl, J. Caicedo, F. Matta, S. Guo and M.A. Sutton, “Acoustic Emission Source Mechanisms
for Steel Bridge Material in Review of Progress in QNDE,” 32B, AIP Conference Proceedings, Vol. 1511, American
Institute of Physics, Melville, NY (2013), pp. 1378-1385, 2012.
7. MATLAB v., The MathWorks Inc. Natick, MA (USA), 2010.
8. Nondestructive Testing Handbook, third edition: Volume 6, Acoustic Emission Testing, ASNT, Columbus, OH, 2005.
9. Scruby, C.B., “An introduction to acoustic emission,” J. Phys. E: Sci. Instru., (20) 946, 1987.
10. Pollock, A.A., “A POD model for Acoustic Emission-Discussion and Status,” AIP Conf. Proc. 1211, pp. 1927-1933,
2009.
11. Weibull, W., “A statistical distribution function of wide applicability,” Journal of Applied Mechanics, 1951. 18:
p. 293-297.
12. Yu, J., P. Ziehl, B. Zarate and J. Caicedo, “Prediction of Fatigue Crack Growth in Steel Bridge Components Using
Acoustic Emission,” Journal of Constructional Steel Research, Vol. 67, No. 11, pp. 1254-1260, 2011.