Active strategies for structural health monitoring using ultrasonic guided waves mainly deal with excitation signals that are band limited in order to minimize the effect of dispersion. The underlying idea is to activate only the fundamental wave modes so that the signal complexity decreases and individual wave packets in the sensor signals can be identified separately. However, it would be advantageous to increase the temporal resolution of the signal in order to enhance the performance of the post-processing algorithms, for example, travel-time-based damage localization algorithms that need precise arrival time estimations or imaging approaches processing the deconvolved signals directly. This article suggests a new technique to deconvolve narrowband and nonstationary ultrasonic signals by means of a time-varying inverse filter. This filter is realized through the application of the matching pursuit decomposition algorithm. The properties of this methodology are quantitatively compared with several onset-time estimation approaches and evaluated with experimental pitch-catch and differential signals between the pristine and the damaged structure.
Su Z., Ye L. and Lu Y.Guided Lamb waves for identification of damage in composite structures: a review. J Sound Vib2006; 295(3-5): 753-780.
2.
Raghavan A. and Cesnik CES.Review of guided-wave structural health monitoring. Shock Vibr Dig2007; 11(7): 91-114.
3.
Moll J. and Fritzen C-P.Advanced aspects of mode-selective excitation of ultrasonic guided waves. In: 24th Conference on Noise and Vibration Engineering , Leuven, Belgium, 2010 .
4.
Qing XP, Beard SJ, Kumar A., Ooi TK and Chang F.-K. Built-in sensor network for structural health monitoring of composite structure . J Intell Mater Syst Struct2007 ; 18: 39-49.
5.
Croxford AJ , Wilcox PD, Konstantinidis G. and Drinkwater BWStrategies for guided-wave structural health monitoring. Proc Math Phys Eng Sci2007; 463: 2961-2981.
6.
Croxford AJ , Moll J., Wilcox PD and Michaels JEEfficient temperature compensation strategies for guided wave structural health monitoring. Ultrasonics2010; 50(4-5): 517-528.
7.
Lu Y. and Michaels JEA methodology for structural health monitoring with diffuse ultrasonic waves in the presence of temperature variations. Ultrasonics2005; 43(9): 717-731.
8.
Qing XP, Beard SJ, Kumar A., et al. The performance of a piezoelectric-sensor-based SHM system under a combined cryogenic temperature and vibration environment. Smart Mater Struct2008; 17: 1-11.
9.
Zagrai AN and Giurgiutiu V.Electro-mechanical impedance method for crack detection in thin plates . J Intell Mater Syst Struct2001; 12: 709-718.
10.
Moll J., Schulte RT, Hartmann B., C-P. Fritzen and Nelles O.Multi-site damage localization in anisotropic plate-like structures using an active guided wave structural health monitoring system. Smart Mater Struct2010; 19(4): 045022.
11.
Grennberg A. and Sandell M.Estimation of subsample time delay differences in narrowband ultrasonic echoes using the Hilbert transform correlation . IEEE Trans Ultrason Ferroelectr Freq Control1994; 41(5): 588-595.
12.
Seydel R. and Chang F-K.Impact identification of stiffened composite panels: I. system development . Smart Mater Struct2001; 10(2): 354-369.
13.
Grosse CU and Reinhardt H-W.Schallemissionsquellen automatisch lokalisieren - Entwicklung eines Algorithmus . Materialprüfung1999; 41(9): 342-347.
14.
Lu Y., Ye L. and Su Z.Crack identification in aluminium plates using Lamb wave signals of a PZT sensor network. Smart Mater Struct2006 ; 15(3): 839-849.
15.
Raghavan A. and Cesnik CES.Guided-wave signal processing using chirplet matching pursuits and mode correlation for structural health monitoring. Smart Mater Struct2007; 16: 355-366.
16.
Michaels JE and Michaels TEDetection of structural damage from the local temporal coherence of diffuse ultrasonic signals. IEEE Trans Ultrason Ferroelectr Freq Control2005; 52(10): 1769-1782.
17.
Cicero T., Cawley P., Simonetti F. and Rokhlin SIPotential and limitations of a deconvolution approach for guided wave structural health monitoring. Struct Health Monitor2009 ; 7(51): 1-16.
18.
Michailovich O. and Tannenbaum A.Blind deconvolution of medical ultrasound images: a parametric inverse filtering approach. IEEE Trans Image Process2007; 16(12): 3005-3019.
19.
Sin S-K. and Chen C-H.A comparison of deconvolution techniques for the ultrasonic nondestructive evaluation of materials. IEEE Trans Image Process1992; 1(1): 3-10.
20.
Kniecke U. and Eger R.Messtechnik - Systemtheorie für Elektrotechniker. Berlin: Springer, 2008.
21.
Mallat SG and Zhang Z.Matching pursuits with time-frequency dictionaries. IEEE Trans Signal Process1993; 41(12): 3397-3415.
22.
Lu Y. and Michaels JENumerical implementation of matching pursuit for the analysis of complex ultrasonic signals. IEEE Trans Ultrason Ferroelectr Freq Control2008; 55(1): 173-182.
23.
Zhou W., Chakraborty D., Kovvali N., Papandreou-Suppappola A, Cochran D, and Chattopadhyay A. Damage classification for structural health monitoring using time-frequency feature extraction and continuous hidden Markov models. In: IEEE Asilomar Conference on Signals, Systems and Computers, Monterey , USA, 2007, pp. 848-852.
24.
Li F., Su Z., Ye L. and Meng G.A correlation filtering-based matching pursuit (CF-MP) for damage identification using Lamb waves. Smart Mater Struct2006; 15(6): 1585-1594.
25.
Liu L. and Yuan FGActive damage localization for plate-like structures using wireless sensors and a distributed algorithm. Smart Mater Struct2008; 17: 1-12.
26.
Zhang X., Qian T., Mei G., et al. Active health monitoring of an aircraft wing with an embedded piezoelectric sensor/actuator network: II. wireless approaches. Smart Mater Struct2007; 16: 1218-1225.
27.
Kienke U., Schwarz M. and Weickert T.Signalverarbeitung: Zeit-Frequenz-Analyse und Schtäzverfahren . Munich, Germany: Oldenbourg Wissenschaftsverlag GmbH , 2008.
28.
Staszewski WJ and Robertson ANTime-frequency and time-scale analyses for structural health monitoring. Philos Trans R Soc A2006; 365(1851): 449-477.
29.
Stolze F., Staszewski WJ, Manson G., and Worden K.An investigation into the instantaneous phase of guided ultrasonic waves in a multi-riveted strap joint aluminium panel. In: 7th International Workshop on Structural Health Monitoring, Stanford, USA, 2009, pp. 2290-2298.
30.
Van der Baan M.Time-varying wavelet estimation and deconvolution . In: CSPG CSEG CWLS Convention, Calgary, AB, Canada, 2009.
31.
Giurgiutiu V.Tuned Lamb wave excitation and detection with piezoelectric wafer active sensors for structural health monitoring. J Intell Mater Syst Struct2005; 16(4): 291-305.
32.
Schulte RT and Fritzen C-P.Spectral element modelling of wave propagation in stringer stiffened structures . In: 4th European Workshop on Structural Health Monitoring, Krakow, Poland, 2008 , pp. 512-519.
33.
Liu L. and Yuan FGA linear mapping technique for dispersion removal of Lamb waves. Struct Health Monitor2010; 9(1): 75-86.
34.
Wilcox PDA rapid signal processing technique to remove the effect of dispersion from guided wave signals. IEEE Trans Ultrason Ferroelectr Freq Control2003; 50(4): 419-427.
35.
Moll J. and Fritzen C-P.Time-varying inverse filtering for high resolution imaging with ultrasonic guided waves. In: 10th European Conference on Non-Destructive Testing, Moscow, Russia, 2010 (on CD-ROM).
