Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: a literature review
Open accessAbstract
This report contains a review of the technical literature concerning the detection, location, and characterization of structural damage via techniques that examine changes in measured structural vibration response. The report first categorizes the methods according to required measured data and analysis technique. The analysis categories include changes in modal frequencies, changes in measured mode shapes (and their derivatives), and changes in measured flexibility coefficients. Methods that use property (stiffness, mass, damping) matrix updating, detection of nonlinear response, and damage detection via neural networks are also summarized. The applications of the various methods to different types of engineering problems are categorized by type of structure and are summarized. The types of structures include beams, trusses, plates, shells, bridges, offshore platforms, other large civil structures, aerospace structures, and composite structures. The report describes the development of the damage-identification methods and applications and summarizes the current state-of-the-art of the technology. The critical issues for future research in the area of damage identification are also discussed.
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The basic idea of vibration-based damage detection methods is that structural damage may induce changes in vibration characteristics, such as frequencies and mode shapes.
“The basic idea of vibration-based damage detection methods is that structural damage may induce changes in vibration characteristics, such as frequencies and mode shapes [2].”
From Review on the new development of vibration-based damage identification for civil engineering structures: 2010–2019 (2021) · cites this paper as [2]
Most current studies focus on the first three levels of damage identification.
“Most current studies focus on the first three levels [2].”
From Review on the new development of vibration-based damage identification for civil engineering structures: 2010–2019 (2021) · cites this paper as [2]
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“[1].”
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“Many nondestructive evaluation methods exist ranging from acoustics to optical, with most of them operating through measuring sound, light, intensity of electromagnetic field, temperature, or displacements.(9) Many researchers have conducted damage identification studies based on nondestructive evaluation methods: the…”
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“…unfortunate since while the broader area of SHM is now a viable commercial proposition with a number of industrial proponents, extensive research (Doebling et al., 1996), has shown that after initial promise several decades ago (Adams et al., 1978), VBDD effectiveness in automatically detecting…”
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“2 Mode‐Shapes Measuring mode shapes is more laborious than measuring frequencies, and also, a significant number of sensors is required to specify mode shape vectors accurately [101].”
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Damage detection by finite element model updating using modal flexibility residual
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Identification of damping in a bridge using a moving instrumented vehicle
González, A., OBrien, E. J., & McGetrick, P. J. (2012) · Journal of Sound and Vibration · doi:10.1016/j.jsv.2012.04.019 · Cited by 289 · see citing works
“maintenance has involved the direct instrumentation of bridge structures - commonly referred to as Structural Health Monitoring (SHM) [1-3] - including vibration based monitoring of modal parameters [4,5].”
BackgroundNatural computing for mechanical systems research: A tutorial overview
Keith Worden, B., Staszewski, W. J., & Hensman, J. J. (2010) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2010.07.013 · Cited by 290 · see citing works
Updating robust reliability using structural test data
Papadimitriou, C., Beck, J. L., & Katafygiotis, L. S. (2001) · Probabilistic Engineering Mechanics · doi:10.1016/s0266-8920(00)00012-6 · Cited by 287 · see citing works
A combined genetic and eigensensitivity algorithm for the location of damage in structures
Friswell, M. I., Penny, J. E. T., & Garvey, S. D. (1998) · Computers & Structures · doi:10.1016/s0045-7949(98)00125-4 · Cited by 276 · see citing works
A review on prognostics and health monitoring of proton exchange membrane fuel cell
Sutharssan, T., Montalvão, D., Chen, Y., Wang, W.-C., Pisac, C., & Elemara, H. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.11.009 · Cited by 272 · see citing works
A modular, wireless damage monitoring system for structures
Straser, E. G., Kiremidjian, A. S., & Meng, T. H. Y. (1998) · Cited by 266 · see citing works
Caicedo, J. M., Dyke, S. J., & Johnson, E. A. (2003) · Journal of Engineering Mechanics · doi:10.1061/(asce)0733-9399(2004)130:1(49 · Cited by 266 · see citing works
Structural Damage Detection Using a Minimum Rank Update Theory
Zimmerman, D. C., & Kaouk, M. (1994) · Journal of vibration and acoustics · doi:10.1115/1.2930416 · Cited by 265 · see citing works
Applications of wavelet transforms to damage detection in frame structures
Ovanesova, A. V., & Suárez, L. E. (2003) · Engineering Structures · doi:10.1016/j.engstruct.2003.08.009 · Cited by 264 · see citing works
Structural health monitoring algorithm comparisons using standard data sets
Figueiredo, E., Park, G., Figueiras, J. A., Farrar, C. R., & Keith Worden, B. (2009) · doi:10.2172/961604 · Cited by 262 · see citing works
Self-citationKeith Worden, B., Manson, G., & ALLMAN, D. (2002) · Journal of Sound and Vibration · doi:10.1006/jsvi.2002.5168 · Cited by 258 · see citing works
Zang, C., & Imregun, M. (2001) · Journal of Sound and Vibration · doi:10.1006/jsvi.2000.3390 · Cited by 254 · see citing works
Structural Health Monitoring in Composite Structures: A Comprehensive Review
Hassani, S., Mousavi, M., & Gandomi, A. H. (2021) · Sensors · doi:10.3390/s22010153 · Cited by 258 · see citing works
Damage detection by means of structural damping identification
Curadelli, O., Riera, J. D., Ambrosini, D., & Amani, M. G. (2008) · Engineering Structures · doi:10.1016/j.engstruct.2008.05.024 · Cited by 251 · see citing works
Zhou, G. Y., & Sim, L. M. (2002) · Smart Materials and Structures · doi:10.1088/0964-1726/11/6/314 · Cited by 247 · see citing works
Q-statistic and T2-statistic PCA-based measures for damage assessment in structures
Delgado, L. E. M., Rodellar, J., Fernández, A., & Güemes, A. (2010) · Structural Health Monitoring · doi:10.1177/1475921710388972 · Cited by 240 · see citing works
Structural health monitoring using smart sensors
Nagayama, T., Spencer, J. F., & Rice, J. (2008) · CRC Press eBooks · doi:10.1201/9781439828441.ch129 · Cited by 235 · see citing works
“As Doebling et al. (1996) describes, the objective function is numerically optimized to update the matrices under constraints such as matrix sparsity, connectivity, symmetry, and matrix positivity.”
BackgroundMethodInfluentialHurlebaus, S., & Gaul, L. (2005) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2005.08.025 · Cited by 234 · see citing works
Reagan, D., Sabato, A. F., & Niezrecki, C. (2017) · Structural Health Monitoring · doi:10.1177/1475921717735326 · Cited by 231 · see citing works
“The system employs an image-processing algorithm for crack detection, proving to be a viable method for SHM.”
BackgroundMoughty, J. J., & Casas, J. R. (2017) · Applied Sciences · doi:10.3390/app7050510 · Cited by 228 · see citing works
Khan, A., Ko, D.-K., Lim, S. C., & Kim, H. S. (2018) · Composites Part B Engineering · doi:10.1016/j.compositesb.2018.12.118 · Cited by 227 · see citing works
Time-series methods for fault detection and identification in vibrating structures
Fassois, S. D., & Sakellariou, J. S. (2006) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2006.1929 · Cited by 221 · see citing works
“In recent years, significant attention has been paid to fault detection via vibration-based methods (Doebling et al. 1996, 1998; Salawu 1997; Zou et al. 2000; Farrar et al. 2001).”
BackgroundInfluentialARMA modelled time-series classification for structural health monitoring of civil infrastructure
Carden, E. P., & Brownjohn, J. (2007) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2007.07.003 · Cited by 220 · see citing works
“Introduction The last two decades have seen a great deal of research and publication in the field of SHM and there has been a proliferation of SHM paradigms put forward [1-3], with longterm monitoring systems implemented on bridges in Europe, the United States and Asia [4-6].”
BackgroundEnvironmental seismology: What can we learn on earth surface processes with ambient noise?
Larose, É., Carrière, S., Voisin, C., Bottelin, P., Baillet, L., Guéguen, P., Walter, F., Jongmans, D., Guillier, B., Garambois, S., et al. (2015) · Journal of Applied Geophysics · doi:10.1016/j.jappgeo.2015.02.001 · Cited by 219 · see citing works
Damage assessment in reinforced concrete beams using eigenfrequencies and mode shape derivatives
Ndambi, J. M., Vantomme, J., & Harri, K. (2002) · Engineering Structures · doi:10.1016/s0141-0296(01)00117-1 · Cited by 219 · see citing works
Condition and Damage Assessment: Issues and Some Promising Indices
Çatbaş, F. N., & Aktan, A. E. (2002) · Journal of Structural Engineering · doi:10.1061/(asce)0733-9445(2002)128:8(1026 · Cited by 216 · see citing works
Structural health monitoring using extremely compressed data through deep learning
Azimi, M., & Pekcan, G. (2019) · Computer-Aided Civil and Infrastructure Engineering · doi:10.1111/mice.12517 · Cited by 216 · see citing works
“Comprehensive state-of-the-art reviews of various aspects of SHM are available in a number of publications (Carden & Fan-ning, 2004; Doebling, Farrar, Prime, & Shevitz, 1996; W. Fan & Qiao, 2011; Kong, Cai, & Hu, 2017; Sinou, 2009; Sohn et al., 2003).”
BackgroundVibration‐based structural condition assessment using convolution neural networks
Khodabandehlou, H., Pekcan, G., & Fadali, M. S. (2018) · Structural Control and Health Monitoring · doi:10.1002/stc.2308 · Cited by 211 · see citing works
“Doebling et al.(1) presented an extensive review of vibration‐based damage detection methods up to 1996, and subsequently Sohn et al.”
Automated output-only dynamic identification of civil engineering structures
Rainieri, C., & Fabbrocino, G. (2009) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2009.10.003 · Cited by 210 · see citing works
Health monitoring of structural composites with embedded carbon nanotube coated glass fiber sensors
Sebastian, J. R., Schehl, N. D., Bouchard, M., Boehle, M., Li, L., Lagounov, A., & Lafdi, K. (2013) · Carbon · doi:10.1016/j.carbon.2013.08.058 · Cited by 206 · see citing works
Damage Identification Using Modal Data: Experiences on a Prestressed Concrete Bridge
Huth, O., Feltrin, G., Maeck, J., Kilic, N., & Motavalli, M. (2005) · Journal of Structural Engineering · doi:10.1061/(asce)0733-9445(2005)131:12(1898 · Cited by 199 · see citing works
A 2-D continuous wavelet transform of mode shape data for damage detection of plate structures
Fan, W., & Qiao, P. (2009) · International Journal of Solids and Structures · doi:10.1016/j.ijsolstr.2009.08.022 · Cited by 199 · see citing works
Damage localization using transmissibility functions: A critical review
Chesné, S., & Deraemaeker, A. (2013) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2013.01.020 · Cited by 196 · see citing works
Wind energy research: State-of-the-art and future research directions
Willis, D. J., Niezrecki, C., Kuchma, D. A., Hines, E. M., Arwade, S. R., Barthelmie, R. J., DiPaola, M. F., Drane, P. J., Hansen, C. J., İnalpolat, M., et al. (2018) · Renewable Energy · doi:10.1016/j.renene.2018.02.049 · Cited by 195 · see citing works
Vibration of Delaminated Composite Laminates: A Review
Della, C. N., & Shu, D. (2007) · Applied Mechanics Reviews · doi:10.1115/1.2375141 · Cited by 194 · see citing works
Multi-classifier information fusion in risk analysis
Pan, Y., Zhang, L., Wu, X., & Skibniewski, M. J. (2020) · Information Fusion · doi:10.1016/j.inffus.2020.02.003 · Cited by 191 · see citing works
Vibration-based structural damage identification using wavelet transform
Bayissa, W. L., Haritos, N., & Thelandersson, S. (2007) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2007.11.001 · Cited by 188 · see citing works
A review of nonlinear dynamics applications to structural health monitoring
Worden, K., Farrar, C. R., Haywood, J., & Todd, M. (2008) · Structural Control and Health Monitoring · doi:10.1002/stc.215 · Cited by 212 · see citing works
“Identifying features that can accurately distinguish a damaged structure from an undamaged one is the focus of most SHM technical literature [2,3].”
BackgroundMethodInfluentialSelf-citationStructural damage identification using damping: a compendium of uses and features
Cao, M. S., Sha, G. G., Gao, Y. F., & Ostachowicz, W. (2017) · Smart Materials and Structures · doi:10.1088/1361-665x/aa550a · Cited by 196 · see citing works
“two decades can be categorized into two groups: local inspection methods [10] and global detection methods [8, 9].”
BackgroundEmbedding damage detection algorithms in a wireless sensing unit for operational power efficiency
Lynch, J. P., Sundararajan, A., Law, K. H., Kiremidjian, A. S., & Carryer, E. (2004) · Smart Materials and Structures · doi:10.1088/0964-1726/13/4/018 · Cited by 182 · see citing works
Sadhu, A., Narasimhan, S., & Antoni, J. (2017) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2017.03.001 · Cited by 179 · see citing works
Experimental and Analytical Modal Analysis of Steel Arch Bridge
Ren, W., Zhao, T., & Harik, I. E. (2004) · Journal of Structural Engineering · doi:10.1061/(asce)0733-9445(2004)130:7(1022 · Cited by 176 · see citing works
Condition based maintenance of machine tools—A review
Goyal, D., & Pabla, B. S. (2015) · CIRP Journal of Manufacturing Science and Technology · doi:10.1016/j.cirpj.2015.05.004 · Cited by 175 · see citing works
Structural Identification for Condition Assessment: Experimental Arts
Aktan, A. E., Farhey, D. N., Helmicki, A. J., Brown, D. L., Hunt, V. J., Lee, K.-L., & Levi, A. (1997) · Journal of Structural Engineering · doi:10.1061/(asce)0733-9445(1997)123:12(1674 · Cited by 174 · see citing works
Xu, Y., & Liu, G. R. (2002) · Journal of Intelligent Material Systems and Structures · doi:10.1177/104538902761696733 · Cited by 173 · see citing works
“It is worth mentioning that, compared with the other detection methods such as ultrasonic waves methods (Lange and Moskovenko, 1978), mechanical impedance methods (Cawley, 1984), modal analysis methods (Doebling et al., 1996), etc, the presently proposed”
MethodResultApplication of Wavelet Approach for ASCE Structural Health Monitoring Benchmark Studies
Hera, A., & Hou, Z. (2003) · Journal of Engineering Mechanics · doi:10.1061/(asce)0733-9399(2004)130:1(96 · Cited by 172 · see citing works
Long‐Term Monitoring and Identification of Bridge Structural Parameters
Soyöz, S., & Feng, M. Q. (2008) · Computer-Aided Civil and Infrastructure Engineering · doi:10.1111/j.1467-8667.2008.00572.x · Cited by 171 · see citing works
Vagnoli, M., Remenyte‐Prescott, R., & Andrews, J. (2017) · Structural Health Monitoring · doi:10.1177/1475921717721137 · Cited by 171 · see citing works
“However, instead of following one of the schemes proposed by [Doebling et al., 1996], the review is carried out by classifying the methods following their mathematical nature: i) model-based methods based on the FE updating strategy; ii) non-model-based methods, such as ANN methods, which are one…”
BackgroundMethodInfluentialReview on Vibration-Based Structural Health Monitoring Techniques and Technical Codes
Yang, Y., Zhang, Y., & Tan, X. (2021) · Symmetry · doi:10.3390/sym13111998 · Cited by 170 · see citing works
Operational Modal Parameter Identification from Power Spectrum Density Transmissibility
Yan, W., & Ren, W. (2011) · Computer-Aided Civil and Infrastructure Engineering · doi:10.1111/j.1467-8667.2011.00735.x · Cited by 169 · see citing works
“The surveys by Doebling et al. (1996) and Sohn et al. (2002) have shown that the structural damage identification through changes in dynamic characteristics such as natural frequencies, mode shapes and their extensions (mode shape curvature, modal flexibility, modal strain energy, etc.) was a…”
BackgroundModal identification of bridges under varying environmental conditions: Temperature and wind effects
Li, H., Li, S., Ou, J., & Li, H. (2009) · Structural Control and Health Monitoring · doi:10.1002/stc.319 · Cited by 168 · see citing works
- Authors
- Los Alamos National Lab., N. (. S., Doebling, S., USDOE, W., Farrar, C., Prime, M., & Shevitz, D.
- ORCID
- Doebling, S
- Published
- 1996-05-01
- OpenAlex
- W2100722180
- Cited by
- 2,899
- References
- 51
- Citations by year
- 2026: 39 · 2025: 99 · 2024: 64 · 2023: 98 · 2022: 103 · 2021: 107 · 2020: 105 · 2019: 112 · 2018: 128 · 2017: 109 · 2016: 135 · 2015: 154 · 2014: 158 · 2013: 172 · 2012: 124
- Type
- report
- Language
- en
- Open access
- green
- www.osti.gov
- Locations
- University of North Texas Digital Library (University of North Texas) (submittedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- Funders
- USDOE, Washington, DC (United States)
- DOE (W-7405-ENG-36)
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
- Physical Sciences › Engineering › Civil and Structural Engineering › Bladed Disk Vibration Dynamics
- Physical Sciences › Engineering › Mechanics of Materials › Ultrasonics and Acoustic Wave Propagation
- Keywords
- structural damage detection, structural health monitoring, vibration-based damage detection, flexibility coefficient, stiffness matrix updating, nonlinear structural response, beams, trusses, plates, shells, bridges, offshore platforms, aerospace structures, composite structures
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