Abstract
Structural health monitoring comprises several procedures such as data fusion, information condensation, feature extraction and probabilistic modelling for the detection, localisation, assessment of defects and prediction of remaining life time in civil, aeronautic and aerospace structures. The monitoring system should decide autonomously whether the host structure is damaged or not. On that account, this work proposes a novel approach based on time–frequency analysis, multiway hierarchical nonlinear principal component analysis, squared prediction error statistic (SPE) and self-organising maps (SOM) for the detection and classification of damage in pipework. The formalism is based on a distributed piezoelectric sensor network for the detection of structural dynamic responses where each sensor acts in turn as an actuator. In a first step, the discrete wavelet transform is used for feature selection and extraction from the structural dynamic responses at different frequency scales. Neural Networks are then used to build a probabilistic model from these features for each actuator with the data from the healthy structure by means of sensor data fusion. Next, the features extracted from the structural dynamic responses in different states (damaged or not) are projected into the probabilistic models by each actuator in order to obtain the non-linear principal components, and then the SPE metrics are calculated. Finally, these metrics together with the non-linear principal components are used as input feature vectors to a SOM. Results show that all the damages were detectable and classifiable, and the selected features proved capable of separating all damage conditions from the undamaged state.
Similar content being viewed by others
References
Van Velsor JK, Rose JL (2007) Guided-wave tomographic imaging of defects in pipe using a probabilistic reconstruction algorithm. Insight NonDestruct Test Cond Monit 49(9):532–537
Hua J, Rose JL (2010) Guided wave inspection penetration power in viscoelastic coated pipes. Insight NonDestruct Test Cond Monit 52(4):195–200
Buethe I, Torres Arredondo MA, Mujica LE, Rodellar J, Fritzen C-P (2012) Damage detection in piping systems using pattern recognition techniques. In: Proceedings of the 6th European workshop in structural health monitoring, EWSHM Dresden, Germany, 2012, pp. 624–631
Rizzo P, Bartoli I, Marzani A, di Scalea FL (2005) Defect classification in pipes by neural networks using multiple guided ultrasonic wave features extracted after wavelet processing. J Press Vessel Technol 127(3):294–303
Brunner AJ, Barbezat M (2006) Acoustic emission monitoring of leaks in pipes for transport of liquid and gaseous media: a model experiment. Adv Mater Res 13–14:351–356
Demma A, Cawley P, Lowe M, Roosenbrand AG, Pavlakovic B (2004) The reflection of guided waves from notches in pipes: a guide for interpreting corrosion measurements. NDT E Int 37(3):167–180
Lowe MJS, Alleyne DN, Cawley P (1998) The mode conversion of a guided wave by a part-circumferential notch in a pipe. J Appl Mech 65(3):649–656
Torres Arredondo MA, Jung H, Fritzen C-P (2012) Towards the development of predictive models for the system design and modal analysis of acoustic emission based technologies. Key Eng Mater 518:396–408
Torres Arredondo MA, Jung H, Fritzen C-P (2011) A study of attenuation and acoustic energy anisotropy of lamb waves in multilayered anisotropic media for NDT and SHM applications. In Proceedings of the 6th international workshop NDT in progress, Prague, Czech Republic: Brno University of Technology, 2011, pp. 313–325
Worden K, Staszewski WJ, Hensman JJ (2011) Natural computing for mechanical systems research: a tutorial overview. Mech Syst Signal Process 25(1):4–111
Pochhammer L (1876) Ueber die fortplanzungsgeschwindigkeiten schwingungen in einemunbegrentzten isotropen kreiscylinder. Journal fuer die reine angewandte Mathematik 81:324–336
Chree C (1889) The equations of an isotropic solid in polar and cylindrical coordinates, their solutions and applications. Trans Camb Philos Soc 14:250–369
Gazis DC (1959) Three-dimensional investigation of the propagation of waves in hollow circular cylinders. I. Analytical foundation. J Acoust Soc Am 31(5):568–573
Gazis DC (1959) Three-dimensional investigation of the propagation of waves in hollow circular cylinders. II. Numerical results. J Acoust Soc Am 31(5):573–578
Rose JL (1999) Ultrasonic waves in solid media. Cambridge University Press, Cambridge
Silk MG, Baiton KF (1979) The propagation in metal tubing of ultrasonic wave modes equivalent to Lamb waves. Ultrasonics 17(1):11–19
Kundu T (2003) Ultrasonic nondestructive evaluation: engineering and biological material characterization, 1st edn. CRC Press, London
Torres Arredondo, MA, Ramirez Lozano MM, Fritzen C-P (2011) DispWare toolbox: a scientific computer program for the calculation of dispersion relations for modal-based acoustic emission and ultrasonic testing. MSc Thesis. Mechanical Engineering Department, University of Siegen
Alleyne DN, Lowe MJS, Cawley P (1998) The reflection of guided waves from circumferential notches in pipes. J Appl Mech 65(3):635–641
Torres Arredondo MA, Fritzen C-P (2012) Characterization and classification of modes in acoustic emission based on dispersion features and energy distribution analysis. J Shock Vib 19(1–9):825–833
Tibaduiza-Burgos DA, Mujica LE, Güemes A, Rodellar J (2010) Active Piezoelectric system using PCA. In: Proceedings of the fifth European workshop on structural health monitoring, Sorrento, Italy, 2010. DEStech Publications, Inc., Lancaster, pp. 164–169
Mallat SG (1989) A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal Mach Intell 11(7):674–693
Mallat S (1997) A wavelet tour of signal processing, 2nd edn. Academic Press, San Diego
Newland DE (1993) Random vibration, spectral and wavelet analysis. Longman, Harlow and Wiley, New York
Nomikos P, MacGregor JF (1994) Monitoring batch processes using multiway principal component analysis. AIChE J 40(8):1361–1375
Mujica LE, Rodellar J, Fernandez A, Guemes A (2010) Q-statistic and T2-statistic PCA-based measures for damage assessment in structures. Struct Health Monit 10(5):539–553
Joe Qin S (2003) Statistical process monitoring: basics and beyond. J Chemom 17(8–9):480–502
Scholz M (2006) Approaches to analyse and interpret biological profile data. PhD Thesis. Max Planck Institute of Molecular Plant Physiology, Potsdam University
Kramer MA (1991) Nonlinear principal component analysis using autoassociative neural networks. AIChE J 37(2):233–243
Kohonen T (2001) Self organizing maps. Springer, Berlin
Ultsch A (2003) U*-Matrix: a Tool to visualize Clusters in high dimensional Data. Computer Science Department, Philipps-University Marburg, Marburg
Merkl D, Rauber A (1997) Cluster connections: a visualization technique to reveal cluster boundaries in self-organizing maps. In: Proceedings of the 9th Italian Workshop on Neural Nets (WIRN97), 1997. Springer, Berlin
Kaski S, Nikklia J, Kohonen T (1998) Methods for interpreting a self-organized map in data analysis. In: Proceedings of the 6th European symposium of artificial neural networks (ESANN98), Brussels, Belgium, pp. 185–190
Vesanto J, Himberg J, Alhoniemi E, Parhankangas J (2000) SOM toolbox for matlab 5. Helsinki University of Technology, Helsinki
Bermes C, Kim JY, Qu J, Jacobs LJ (2007) Experimental characterization of material nonlinearity using Lamb waves. Appl Phys Lett 90(2):021901
Shadrivov IV, Kozyrev AB, Van der Weide DW, Kivshar YS (2008) Tunable transmission and harmonic generation in nonlinear metamaterials. Appl Phys Lett. 93:161903
Srivastava A, di Scalea FL (2009) On the existence of antisymmetric or symmetric Lamb waves at nonlinear higher harmonics. J Sound Vib 323(3–5):932–943
Acknowledgments
The authors would like to express their gratitude to the Research School on Multi Modal Sensor Systems for Environmental Exploration (MOSES) and the Centre for Sensor Systems (ZESS) for sponsoring the research presented herein. Furthermore, the authors thank Mr. Fahit Gharibnezhad from the Polytechnic University of Catalunya for his support during the experiments.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Torres-Arredondo, M.A., Buethe, I., Tibaduiza, D.A. et al. Damage detection and classification in pipework using acousto-ultrasonics and non-linear data-driven modelling. J Civil Struct Health Monit 3, 297–306 (2013). https://doi.org/10.1007/s13349-013-0060-5
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13349-013-0060-5