Non-contact Surface Wave Testing Inversion by Artificial Neural Networks
Conference: Publication Date: 26 March 2018Testing Method:
The advantage of non-contact, air-coupled sensing is that it provides an opportunity for a quick scanning and imaging of large civil engineering structures. The non-contact Spectral Analysis of Surface Waves SASW test is considered to be an extension of the traditional SASW test, where the ground-coupled sensors are replaced by non- contact sensors to collect the leaky surface waves, instead of ground vibration. The objective of the test is to determine the leaky Rayleigh wave dispersion curve, i.e. the velocity of leaky Rayleigh waves as a function of frequency, and then through a process of inversion to estimate the elastic modulus profile. Significant efforts have been devoted to develop a general automated inversion procedure. This paper presents the development and application of Artificial Neural Networks (ANNs) for an automated inversion of non-contact SASW test data. Numerical simulation of the air-coupled SASW test on several hundred pavement configurations using finite elements was made to develop an extensive database of surface wave dispersion curves. The database was used in the development of the ANN for an automated inversion. The developed automated system was validated through inversion of additional data not used in training of the ANN (i.e. synthetic dispersion curves), and it showed a good performance in prediction of pavement profiles.
- Castaings, M., and Hosten, B.,2001, "Lamb and SH waves generated and detected by air-coupled ultrasonic transducers in composite material plates". NDT & E International, 34(4), 249-258.
- Zhu, J., and Popovics, J. ,2002, "Non-contact detection of surface waves in concrete using an air-coupled sensor",In Quantitative Nondestructive Evaluation (Vol. 615, No. 1, pp. 1261-1268). AIP Publishing.
- Karim, H. H. and Al-dami, H. A. N.(2012) "Non-destructive testing of concrete structures using GPR technique with an intermediate antennas frequency", Eng. &Tech. Journal, UOT, Vol.30, No. 14, pp. 2678-2693, 2012.
- Gucunski, N. (1994). "Detection of multi-course surface pavement layers by the SASW method", Nondestructive Testing of Pavements and Backcalculation of Moduli: Second Volume. ASTM International.
- Kee, S. H., and Zhu, J., 2010, "Using air-coupled sensors to determine the depth of a surface-breaking crack in concrete", The Journal of the Acoustical Society of America, 127(3), 1279-1287.
- Ryden, N., Lowe, M. J. S., and Cawley, P., 2009, "Non-contact surface wave testing of pavements using a rolling microphone array", Proceedings of the NDTCE, Nantes, France, 30.
- Nazarian, S., Abdallah, I., and Yuan, D.,2004,"Neural networks for rapid reduction interpretation of spectral analysis of surface waves results",Transportation Research Record: Journal of the Transportation Research Board, (1868), 150-155.
- WANG, H., 2011,"Analysis of Tire-Pavement Interaction and Pavement Responses Using a Decoupled Modeling", Ph.D. Dissertation, University of Illinois, Urbana-Champaign.
- ABAQUS." Abaqus analysis user's manual". Version 6.14-6, 2016, Providence, RI, USA.
- Zerwer, A. C. (2002).,"Parameter estimation in finite elemnt simulation of Rayleigh wave", Journal of Geotechnical &Enviromental Engineering, ASCE, 128(3), 250-261.
- Nazarian, S., and Stokoe, K. H.,1986, "In situ determination of elastic moduli of pavement systems by spectral analysis of surface waves method" (theoretical aspects).
- Wu, J., Liang, J., and Adhikari, S., 2014," Dynamic response of concrete pavement structure with asphalt isolating layer under moving loads", Journal of Traffic and Transportation Engineering (English Edition), 1(6), 439-447.
- Lu, Y., Cao, Y., McDaniel, J. G., and Wang, M. L., 2015, " Fast Inversion of Air-Coupled Spectral Analysis of Surface Wave (SASW) Using in situ Particle Displacement", ISPRS International Journal of Geo- Information, 4(4), 2619-2637.
- Williams, T. P., and Gucunski, N., 1995,"Neural networks for backcalculation of moduli from SASW test", Journal of computing in civil engineering, 9(1), 1-8.
42 Page Views
0 PDF Downloads
0 Facebook Shares