Regression models for structural health monitoring of welded bridge joints based on temperature, traffic and strain measurements
Abstract
A modelling platform based on regression analysis is developed as a novel approach to structural health monitoring of welded joints of orthotropic bridge steel decks. Monitoring outcomes from the Great Belt Bridge (Denmark) are used to develop regression models following a weighted least squares approach to characterize the normal correlation pattern between environmental conditions (daily-averaged pavement temperatures), operational loads (daily-aggregated heavy traffic counts) and a strain-based performance indicator. The developed models can be used within a structural health monitoring–based asset management framework for performance assessment (i.e. diagnosis of structural performance changes) and performance prediction (i.e. prognosis of structural performance leading to service life estimates). The main novelty of the work presented consists of the development of an algorithm based on statistical control charts related to the prediction bands of the regression models. The algorithm enables the interpretation of new monitoring data and the identification of potentially abnormal behaviours via outlier detection, as part of an envisaged ‘real-time’ performance assessment application. The proposed approach to outlier detection through structural health monitoring is finally illustrated considering actual monitoring outcomes from the bridge. This highlights the applicability of the developed modelling platform and contributes to bridging the gap between monitoring data and monitoring-based information that can lead to more effective asset management decisions.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Mass is recognized as the most significant consequence of crossing vehicles.
“Since mass is recognized as the most significant consequence of crossing vehicles, its effects on the bridge structure have been investigated by the SHM community in recent decades [198,199].”
From Effects of Environmental and Operational Conditions on Structural Health Monitoring and Non-Destructive Testing: A Systematic Review (2023) · cites this paper as [198]
Cites
Hahn, G. J., Draper, N. R., & Smith, H. C. (1982) · Technometrics · doi:10.2307/1267833 · Cited by 5,820 · see citing works
Applied Regression Analysis (2nd ed).
de Carvalho, J. F., Draper, N. R., & Smith, H. (1981) · Journal of the American Statistical Association · doi:10.2307/2287608 · Cited by 3,054 · see citing works
Vibration Based Condition Monitoring: A Review
Carden, E. P., & Fanning, P. (2004) · Structural Health Monitoring · doi:10.1177/1475921704047500 · Cited by 1,549 · see citing works
Technology developments in structural health monitoring of large-scale bridges
Ko, J. M., & Ni, Y. (2005) · Engineering Structures · doi:10.1016/j.engstruct.2005.02.021 · Cited by 1,014 · see citing works
Review Paper: Health Monitoring of Civil Infrastructure
Chang, P. C., Flatau, A. B., & Liu, S. C. (2003) · Structural Health Monitoring · doi:10.1177/1475921703036169 · Cited by 989 · see citing works
Effects of environmental and operational variability on structural health monitoring
Sohn, H. (2007) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2006.1935 · Cited by 883 · see citing works
The application of machine learning to structural health monitoring
Keith Worden, B., & Manson, G. (2006) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2006.1938 · Cited by 436 · see citing works
Structural Health Monitoring Using Statistical Process Control
Sohn, H., Czarnecki, J. J., & Farrar, C. R. (2000) · Journal of Structural Engineering · doi:10.1061/(asce)0733-9445(2000)126:11(1356 · Cited by 348 · see citing works
Ambient vibration re-testing and operational modal analysis of the Humber Bridge
Brownjohn, J., Magalhães, F., Caetano, E., & Cunha, Á. A. M. F. (2010) · Engineering Structures · doi:10.1016/j.engstruct.2010.02.034 · Cited by 320 · see citing works
Monitoring-Based Fatigue Reliability Assessment of Steel Bridges: Analytical Model and Application
Ni, Y. Q., Ye, X. W., & Ko, J. M. (2010) · Journal of Structural Engineering · doi:10.1061/(asce)st.1943-541x.0000250 · Cited by 225 · see citing works
Assessment of Bridge Expansion Joints Using Long-Term Displacement and Temperature Measurement
Ni, Y. Q., Hua, X., Wong, K. Y., & Ko, J. M. (2007) · Journal of Performance of Constructed Facilities · doi:10.1061/(asce)0887-3828(2007)21:2(143 · Cited by 159 · see citing works
Fatigue reliability assessment of retrofitted steel bridges integrating monitored data
Liu, M., Frangopol, D. M., & Kwon, K. (2009) · Structural Safety · doi:10.1016/j.strusafe.2009.08.003 · Cited by 114 · see citing works
Renovation techniques for fatigue cracked orthotropic steel bridge decks
de Jong, F. B. P. (2007) · Research Repository (Delft University of Technology) · Cited by 107 · see citing works
Influence of ambient temperature on the fatigue damage of welded bridge decks
GUO, T., LI, A., & Wang, H. (2007) · International Journal of Fatigue · doi:10.1016/j.ijfatigue.2007.08.004 · Cited by 75 · see citing works
Tong, G., Li, A., & Li, J. (2008) · Structural Health Monitoring · doi:10.1177/1475921708090556 · Cited by 69 · see citing works
Guo, T., & Chen, Y.-W. (2011) · Engineering Failure Analysis · doi:10.1016/j.engfailanal.2010.09.014 · Cited by 58 · see citing works
On model- and data-based approaches to structural health monitoring
Barthorpe, R. J. (2010) · White Rose eTheses Online (University of Leeds, The University of Sheffield, University of York) · Cited by 57 · see citing works
Ding, Y., & Li, A. (2011) · Frontiers of Architecture and Civil Engineering in China · doi:10.1007/s11709-011-0122-x · Cited by 50 · see citing works
Design principles of surfacings on orthotropic steel bridge decks
Medani, T. O. (2006) · Research Repository (Delft University of Technology) · Cited by 43 · see citing works
Wang, Y., Li, Z. X., & Li, A. Q. (2010) · Theoretical and Applied Fracture Mechanics · doi:10.1016/j.tafmec.2010.10.008 · Cited by 36 · see citing works
Dynamic Characteristics of an Overpass Bridge in a Full-Scale Destructive Test
Siringoringo, D. M., Fujino, Y., & Nagayama, T. (2011) · Journal of Engineering Mechanics · doi:10.1061/(asce)em.1943-7889.0000280 · Cited by 32 · see citing works
Song, Y., & Ding, Y. (2013) · Science China Technological Sciences · doi:10.1007/s11431-013-5235-0 · Cited by 30 · see citing works
Vibration monitoring of a footbridge with a wireless sensor network
Feltrin, G., Jalsan, K. E., & Flouri, K. (2013) · Journal of Vibration and Control · doi:10.1177/1077546313501929 · Cited by 22 · see citing works
Statistical approach to a SHM benchmark problem
Casciati, S. (2010) · Smart Structures and Systems · doi:10.12989/sss.2010.6.1.017 · Cited by 19 · see citing works
Iwasaki, A., TODOROKI, A., Sugiya, T., et al. (2005) · Smart Materials and Structures · doi:10.1088/0964-1726/14/3/018 · Cited by 12 · see citing works
Data-Based Models for Assessment and Life Prediction of Monitored Civil Infrastructure Assets.
Alcover, I. F. (2014) · Surrey Research Insight Open Access (The University of Surrey) · Cited by 9 · see citing works
Alcover, I. F., Andersen, J. E., & Chryssanthopoulos, M. K. (2013) · Structural Engineering International · doi:10.2749/101686613x13627351081470 · Cited by 7 · see citing works
Self-citationFasl, J. D., Helwig, T. A., Wood, S., et al. (2010) · Bridge maintenance, safety and management · doi:10.1201/b10430-55 · Cited by 6 · see citing works
Control of traffic loads on Great Belt Bridge
Laigaard, J., Bitsch, N., Gjelstrup, H., et al. (2012) · Bridge maintenance, safety and management · doi:10.1201/b12352-505 · Cited by 4 · see citing works
Suhardjo (2001) · doi:10.1002/1096-9845(200102)30:2
Flagged first, then by citations
Cited by
Sorted by citations
Keshmiry, A., Hassani, S., Mousavi, M., & Dackermann, U. (2023) · Buildings · doi:10.3390/buildings13040918 · Cited by 96 · see citing works
He, X., Tan, G., Chu, W., Zhang, S., & Wei, X. (2022) · Sustainability · doi:10.3390/su14159600 · Cited by 16 · see citing works
- Authors
- Farreras-Alcover, I., Chryssanthopoulos, M. K., & Andersen, J. E.
- Affiliations
- COWI A/S, Kongens Lyngby, Denmark
- University of Surrey (GB)
- Cowi (Denmark) (DK)
- Venue
- Structural Health Monitoring
- Publisher
- SAGE Publications
- Published
- 2015-10-16
- Volume
- 14
- Issue
- 6
- Pages
- 648-662
- ISSN
- 1475-9217 (ISSN-L)
- 1741-3168
- OpenAlex
- W2418057341
- Cited by
- 58
- References
- 30
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 5 · 2023: 12 · 2022: 7 · 2021: 8 · 2020: 1 · 2019: 1 · 2018: 7 · 2017: 5 · 2016: 2 · 2013: 1
- FWCI
- 7.72
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Structural Health Monitoring (publishedVersion)
- Surrey Research Insight Open Access (The University of Surrey) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Engineering and Materials Analysis
- Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Maintenance and Monitoring
- Keywords
- orthotropic steel deck, regression models, weighted least squares, pavement temperature, asset management, service life prediction, control charts, outlier detection, Great Belt Bridge
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
