Application of Model-Based Estimation to Time-Delay Estimation of Ultrasonic Testing Signals


1 K.N. Toosi university of Tech.

2 K.N.Toosi University of Tech.


Time-Delay-Estimation (TDE) has been a topic of interest in many applications in the past few decades. The emphasis of this work is on the application of model-based estimation (MBE) for TDE of ultrasonic signals used in ultrasonic thickness gaging. Ultrasonic thickness gaging is based on precise measurement of the time difference between successive echoes which reflect back from the back wall of the test piece. The received echoes are modelled by Gaussian pulses and the desired system response is estimated using Gauss-Newton and Space Alternating Generalized Expectation Maximization (SAGE) algorithms. In addition to the model-based estimation approach, five other TDE techniques including peak-to-peak measurement, cross-correlation, cross-correlation with interpolation, phase-slope, and cross-correlation with Wiener filtering are also considered and compared with the SAGE. The main advantage of the SAGE algorithm, in addition to its higher accuracy, is its ability to deconvolve the overlapping echoes.


Main Subjects

1 . Demirli, R. and J. Saniie, Model-based estimation of ultrasonic echoes. Part I: Analysis and algorithms. Ultrasonic, Ferroelectrics and Frequency Control, IEEE Transactions on 48(3) (2001)787-802.

2 .Demirli, R. and J. Saniie, Model-based estimation of ultrasonic echoes. Part II: Nondestructive evaluation applications. Ultrasonics, Ferroelectrics, and Frequency Control, IEEE Transactions on 48(3) (2001)803-811.

3 .Feder, M. and E. Weinstein), Parameter estimation of superimposed signals using the EM algorithm. Acoustics, Speech and Signal Processing, IEEE Transactions on 36(4) (1988) 477-489.

4 .Jacovitti, G. and G. Scarano,  Discrete time techniques for time delay estimation. Signal Processing, IEEE Transactions on 41(2) (1993) 525-533.

5 .Matz, V,  R. Smid, S,  Starman and M. Kreidl , Signal-to-noise ratio enhancement based on wavelet filtering in ultrasonic testing. Ultrasonics 49(8) (2009) 752-759.

6 .Sandell, M. and A. Grennberg , Estimation of the spatial impulse response of an ultrasonic transducer using a tomographic approach. The Journal of the Acoustical Society of America 98(4) (1995) 2094-2103.

7 .Shull, P. J,  Nondestructive evaluation: theory, techniques, and applications, CRC press, (2002).

8 .Zhou, J., X. Zhang, G. Zhang and D. Chen ,  Optimization and Parameters Estimation in Ultrasonic Echo Problems Using Modified Artificial Bee Colony Algorithm.  Journal of Bionic Engineering 12(1) (2015)160-169.

9 .F. Honarvar, F. Salehi, V. Safavi, A. Mokhtari, and A. N. Sinclair, Ultrasonic monitoring of erosion/corrosion thinning rates in industrial piping systems, Ultrasonics, vol. 53(2013)1251-1258.

10 .F. Honarvar, M. Iran-Nejad, A. Gholami, and A. Sinclair, Estimation of Uncertainty in Ultrasonic Thickness Gauging and Improvement of Measurements by Signal Processing, in Annual Conference, ed. Toronto, Canada: Canadian Institute of Nondestructive Evaluation (CINDE), 2014.

11 .M. Hajian and F. Honarvar, Reflectivity Estimation using an Expectation Maximization Algorithm for Ultrasonic Testing of Adhesive Bonds, Materials Evaluation, 2011.

12 .A. Gholami, F. Honarvar, and H. A. Moghaddam, Optimal parameter estimation of ultrasonic signals by using a combination of particle swarm optimization and gauss-newton algorithms, Modares Mechanical Engineering, vol. 15, 2015.