Browse > Article
http://dx.doi.org/10.12989/sss.2016.18.3.501

Piezoelectric impedance based damage detection in truss bridges based on time frequency ARMA model  

Fan, Xingyu (Centre for Infrastructural Monitoring and Protection, School of Civil and Mechanical Engineering, Curtin University)
Li, Jun (Centre for Infrastructural Monitoring and Protection, School of Civil and Mechanical Engineering, Curtin University)
Hao, Hong (Centre for Infrastructural Monitoring and Protection, School of Civil and Mechanical Engineering, Curtin University)
Publication Information
Smart Structures and Systems / v.18, no.3, 2016 , pp. 501-523 More about this Journal
Abstract
Electromechanical impedance (EMI) based structural health monitoring is performed by measuring the variation in the impedance due to the structural local damage. The impedance signals are acquired from the piezoelectric patches that are bonded on the structural surface. The impedance variation, which is directly related to the mechanical properties of the structure, indicates the presence of local structural damage. Two traditional EMI-based damage detection methods are based on calculating the difference between the measured impedance signals in the frequency domain from the baseline and the current structures. In this paper, a new structural damage detection approach by analyzing the time domain impedance responses is proposed. The measured time domain responses from the piezoelectric transducers will be used for analysis. With the use of the Time Frequency Autoregressive Moving Average (TFARMA) model, a damage index based on Singular Value Decomposition (SVD) is defined to identify the existence of the structural local damage. Experimental studies on a space steel truss bridge model in the laboratory are conducted to verify the proposed approach. Four piezoelectric transducers are attached at different locations and excited by a sweep-frequency signal. The impedance responses at different locations are analyzed with TFARMA model to investigate the effectiveness and performance of the proposed approach. The results demonstrate that the proposed approach is very sensitive and robust in detecting the bolt damage in the gusset plates of steel truss bridges.
Keywords
structural damage detection; piezoelectric impedance; time-frequency ARMA; steel bridge; gusset; joint condition;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 Pavelko, I., Pavelko, V., Kuznetsov, S. and Ozolinsh, I. (2014), "Bolt-joint structural health monitoring by the method of electromechanical impedance", Aircraft Eng. Aerospace Technol., 86(3), 207-214.   DOI
2 Raju, V., Park, G. and Cudney, H. (1998), "Impedance-based health monitoring technique of composite reinforced structures", Proceedings of the 9th International Conference on Adaptive Structures and Technologies.
3 Rucka, M. and Wilde, K. (2006), "Application of continuous wavelet transform in vibration based damage detection method for beams and plates", J. Sound Vib., 297(3-5), 536-550.   DOI
4 Sohn, H., Allen, D.W., Worden, K. and Farrar, C.R. (2003), "Statistical damage classification using sequential probability ratio tests," Struct. Health Monit., 2(1), 57-74.   DOI
5 Song, H., Lim, H.J. and Sohn, H. (2013), "Electromechanical impedance measurement from large structures using a dual piezoelectric transducer", J. Sound Vib., 332(25), 6580-6595.   DOI
6 Stoica, P. and Moses, R. (1997), Introduction to Spectral Analysis, Prentice-Hall, 1st Edition.
7 Sun, R., Sevillano, E. and Perera, R. (2015), "Debonding detection of FRP strengthened concrete beams by using impedance measurements and an ensemble PSO adaptive spectral model", Compos. Struct., 125, 374-387.   DOI
8 Tseng, K.K.H. and Naidu, A.S.K. (2002), "Non-parametric damage detection and characterization using smart piezoceramic material", Smart Mater. Struct., 11(3), 317-329.   DOI
9 Wang, D., Song, H. and Zhu, H. (2014), "Embedded 3-D electromechanical impedance model for strength monitoring of concrete using PZT transducer", Smart Mater. Struct., 23(11), 115019.   DOI
10 Wang, D., Zhu, H., Chen, C. and Xia, Y. (2007), "An impedance analysis for crack detection in the Timoshenko beam based on the anti-resonance technique", Acta Mech. Solida Sinica, 20(3), 228-235.   DOI
11 Wax, M. and Kailath, T. (1983), "Efficient inversion of Toeplitz-block Toeplitz matrix", IEEE T. Acoust., Speech Signal Pr., 31(5), 1218-1221.   DOI
12 Yang, J.N., Lei, Y., Lin, S. and Huang, N. (2004), "Hilbert-Huang based approach for structural damage detection", J. Eng. Mech. - ASCE, 130(1), 85-95.   DOI
13 Yang, J.N., Lei, Y., Pan, S. and Huang, N. (2003), "System identification of linear structures based on Hilbert-Huang spectral analysis Part 1: Normal modes", Earthq. Eng. Struct. D., 32(9), 1443-1467.   DOI
14 Yang, Y.W., Xu, J.F. and Soh, C.K. (2005), "Generic impedance-based model for structure-piezoceramic interacting system", J. Aerospace Eng. - ASCE, 18(2), 93-101.   DOI
15 Yi, T.H., Li, H.N. and Gu, M. (2013a), "Wavelet based multi-step filtering method for bridge health monitoring using GPS and accelerometer", Smart Struct. Syst., 11(4), 331-348.   DOI
16 Yi, T.H., Li, H.N. and Sun, H.M. (2013b), "Multi-stage structural damage diagnosis method based on "energy-damage" theory", Smart Struct. Syst., 12(3), 345-361.   DOI
17 Jachan, M., Matz, G. and Hlawatsch, F. (2007), "Time-frequency ARMA models and parameter estimators for underspread nonstationary random processes", IEEE T. Signal Pr., 55(9), 4366-4381.   DOI
18 Baptista, F.G. and Filho, J.V. (2009), "A new impedance measurement system for PZT-based structural health monitoring", IEEE T. Instrument. Measurement, 58(10), 3602-3608.   DOI
19 Feng, Z., Liang, M. and Chu, F. (2013), "Recent advances in time-frequency analysis methods for machinery fault diagnosis: a review with application examples", Mech. Syst. Signal Pr., 38(5), 165-205.   DOI
20 Jachan, M., Hlawatsch, F. and Matz, G. (2005), "Linear methods for TFARMA parameter estimation and system approximation", IEEE Signal Processing Workshop on Statistical Signal Array Processing, 2; 844-852.
21 Liang, C., Sun, F.P. and Rogers, C.A. (1994), "Coupled electro-mechanical analysis of adaptive material systems - determination of the actuator power consumption and system energy transfer", J. Intel. Mat. Syst. Str., 5(1), 12-20.   DOI
22 Li, J. and Hao, H. (2014), "Substructure damage identification based on wavelet domain response reconstruction", Struct. Health Monit., 13(4), 389-405.   DOI
23 Li, J. and Hao, H. (2015), "Damage detection of shear connectors under moving loads with relative displacement measurements", Mech. Syst. Signal Pr., 60-61, 124-150.   DOI
24 Li, J., Hao, H. and Zhu, H.P. (2014), "Dynamic assessment of shear connectors in composite bridges with ambient vibration measurements", Adv. Struct. Eng., 17(5), 617-638.   DOI
25 Naidu, A.S.K. (2004), Structural damage identification with admittance signatures of smart PZT transducers, PhD Thesis, Nanyang Technological University, Singapore.
26 National Transportation Safety Board (2008), "Collapse of I-35W Highway Bridge Minneapolis," Minnesota, Highway Accident Report.
27 Park, G., Cudney, H. and Inman, D.J. (2000), "Impedance-based health monitoring of civil structural components", J. Infrastruct. Syst. - ASCE, 6(4), 153-160.   DOI
28 Park, S., Lee, J.T., Yun, C.B. and Inman, D.J. (2008), "Electro-mechanical impedance-based wireless structural health monitoring using PCA-data compression and k-means clustering algorithms", J. Intel. Mat. Syst. Str., 19(4), 509-520   DOI
29 Park, S., Yun, C.B., Roh, Y. and Lee, J.J. (2005), "Health monitoring of steel structures using impedance of thickness modes at PZT patches", Smart Struct. Syst., 1(4), 339-353.   DOI