Abstract
Since the monitoring of cable tension are rather susceptible to environmental influence and external loads, the condition assessment of stay cables is vitally difficult because of these uncertainties. In this paper, regarding the health condition of stay cables, a multilevel assessment framework is presented, which can synthetically combined the evaluation results from numerical simulation, field monitoring and visual inspection. Based on these methods, three qualitative and three quantitative indices are selected as the evaluation indices. To reduce the uncertainties during the assessment procedure, an intelligent methodology based on cloud model and Dempster-Shafer (D-S) evidence theory is proposed. With the combination of forward cloud generator and backward cloud generator, the cloud parameters of in-situ data is transmitted to the cloud model of grade criteria, then the cloud evidence with relative weights are fused by Dempster combination, the condition grade of the cable is finally obtained. The Junshan Yangtze River Bridge is adopted to verify the effectiveness of the proposed methodology. The results show that the uncertainty degree can be obviously reduced from 55.7% to 6.7%, so that a scientific evaluation of cable conditions can be obtained. The multilevel assessment framework proposed in this study can serve as an effective basis for cable replacement and maintenance.
Similar content being viewed by others
References
Certa A, Hopps F, Inghilleri R, La Fata CM (2017) A dempster-shafer theory-based approach to the failure mode, effects and criticality analysis (FMECA) under epistemic uncertainty: Application to the propulsion system of a fishing vessel. Reliability Engineering & System Safety 159:69–79, DOI: https://doi.org/10.1016/j.ress.2016.10.018
Cross EJ, Koo KY, Brownjohn JMW, Worden K (2013) Long-term monitoring and data analysis of the Tamar Bridge. Mechanical Systems and Signal Processing 35(1–2):16–34, DOI: https://doi.org/10.1016/j.ymssp.2012.08.026
Degrauwe D, De Roeck G, Lombaert G (2009) Uncertainty quantification in the damage assessment of a cable-stayed bridge by means of fuzzy numbers. Computers & Structures 87(17–18):1077–1084, DOI: https://doi.org/10.1016/j.compstruc.2009.03.004
Gao HB, Xie GT, Liu HZ, Zhang XY, Li DY (2017) Lateral control of autonomous vehicles based on learning driver behavior via cloud model. The Journal of China Universities of Posts and Telecommunications 24(2):10–17, DOI: https://doi.org/10.1016/S1005-8885(17)60194-8
Han SH (2011) A study on safety assessment of cable-stayed bridges based on stochastic finite element analysis and reliability analysis. KSCE Journal of Civil Engineering 15(2):305–315, DOI: https://doi.org/10.1007/s12205-011-0823-7
Hassan MM (2013) Optimization of stay cables in cable-stayed bridges using finite element, genetic algorithm, and B-spline combined technique. Engineering Structures 49:643–654, DOI: https://doi.org/10.1016/j.engstruct.2012.11.036
JTG D60-2015 (2015) General specifications for design of highway bridge and culverts. JTG D60-2015, Ministry of Transport of the People’s Republic of China, Beijing, China
JTG/T D65-01-2007 (2007) Guidelines for design of highway cable-stayed bridge. JTG/T D65-01-2007, Ministry of Transport of the People’s Republic of China, Beijing, China
JTG/T H21-2011 (2011) Standards for technical condition evaluation of highway bridges. JTG/T H21-2011, Ministry of Transport of the People’s Republic of China, Beijing, China
JT/T 775-2010 (2010) Stay cable of parallel steel wires for large-span cable- stayed bridge. JT/T 775-2010, Ministry of Transport of the People’s Republic of China, Beijing, China
Kim S (2001) Bridge management system development for a cable-stayed bridge. KSCE Journal of Civil Engineering 5(3):43–49, DOI: https://doi.org/10.1007/BF02830725
Li D (1995) Membership clouds and membership cloud generators. Computer Research and Development 32(6):15–20
Li X, Gao C, Guo Y, He F, Shao Y (2019) Cable surface damage detection in cable-stayed bridges using optical techniques and image mosaicking. Optics & Laser Technology 110:36–43, DOI: https://doi.org/10.1016/j.optlastec.2018.07.012
Li D, Liu C, Gan W (2009) A new cognitive model: Cloud model. International Journal of Intelligent Systems 24(3):357–375, DOI: https://doi.org/10.1002/int.20340
Li H, Ou J (2016) The state of the art in structural health monitoring of cable-stayed bridges. Journal of Civil Structural Health Monitoring 6(1):43–67, DOI: https://doi.org/10.1007/s13349-015-0115-x
Li S, Wei S, Bao Y, Li H (2018) Condition assessment of cables by pattern recognition of vehicle-induced cable tension ratio. Engineering Structures 155:1–15, DOI: https://doi.org/10.1016/j.engstruct.2017.09.063
Li H, Zhang F, Jin Y (2014) Real-time identification of time-varying tension in stay cables by monitoring cable transversal acceleration. Structural Control and Health Monitoring 21(7):1100–1117, DOI: https://doi.org/10.1002/stc.1634
Liang L, Sun S, Li M, Li X (2019) Data fusion technique for bridge safety assessment. Journal of Testing and Evaluation 47(3), DOI: https://doi.org/10.1520/JTE20170760
Lilien JL, Pinto da Costa A (1994) Vibration amplitudes caused by parametric excitation of cable stayed structures. Journal of Sound and Vibration 174(1):69–90, DOI: https://doi.org/10.1006/jsvi.1994.1261
Liu XL, Huang Q, Ren Y, Wang B, Xu X (2017) Comprehensive evaluation method of cable-stayed bridges with multi-index evidence fusion. Journal of Harbin Institute of Technology 49(3):74–79, DOI: https://doi.org/10.11918/j.issn.0367-6234.2017.03.012
Lu Y (2003) A golden section approach to optimization of automotive friction materials. Journal of Materials Science 38(5):1081–1085, DOI: https://doi.org/10.1023/A:1022362217043
Lu H, Ren L, Chen Y, Tian P, Liu J (2017) A cloud model based multiattribute decision making approach for selection and evaluation of groundwater management schemes. Journal of Hydrology 555:881–893, DOI: https://doi.org/10.1016/j.jhydrol.2017.10.009
Montassar S, Mekki OB, Vairo G (2015) On the effects of uniform temperature variations on stay cables. Journal of Civil Structural Health Monitoring 5(5):735–742, DOI: https://doi.org/10.1007/s13349-015-0140-9
Pan NF (2008) Fuzzy AHP approach for selecting the suitable bridge construction method. Automation in Construction 17(8):958–965, DOI: https://doi.org/10.1016/j.autcon.2008.03.005
Ren Y, Xu X, Huang Q, Zhao DY, Yang J (2019) Long-term condition evaluation for stay cable systems using dead load — induced cable forces. Advances in Structural Engineering 22(7):1644–1656, DOI: https://doi.org/10.1177/1369433218824486
Shieh JI, Wu HH (2017) A framework of applying ordering coefficient based on the information energy to identify the causal relationships among critical factors from raw data. Journal of Testing and Evaluation 46(2):704–713, DOI: https://doi.org/10.1520/JTE20150328
Sun S, Liang L, Li M, Li X (2019) Bridge performance evaluation via dynamic fingerprints and data fusion. Journal of Performance of Constructed Facilities 33(2):04019004, DOI: https://doi.org/10.1061/(ASCE)CF.1943-5509.0001256
Suzumura K, Nakamura SI (2004) Environmental factors affecting corrosion of galvanized steel wires. Journal of Materials in Civil Engineering 16(1):1–7, DOI: https://doi.org/10.1061/(ASCE)0899-1561(2004)16:1(1)
Talebinejad I, Fischer C, Ansari F (2011) Numerical evaluation of vibration-based methods for damage assessment of cable-stayed bridges. Computer-Aided Civil and Infrastructure Engineering 26(3): 239–251
Verbert K, Babuška R, De Schutter B (2017) Bayesian and dempster — shafer reasoning for knowledge-based fault diagnosis — A comparative study. Engineering Applications of Artificial Intelligence 60:136–150, DOI: https://doi.org/10.1016/j.engappai.2017.01.011
Wang H (2002) Minimum entropy control of non-Gaussian dynamic stochastic systems. IEEE Transactions on Automatic Control 47(2): 398–403, DOI: https://doi.org/10.1109/9.983388
Wang D, Zeng D, Singh VP, Xu P, Liu D, Wang Y, Wang L (2016) A multidimension cloud model-based approach for water quality assessment. Environmental Research 149:113–121, DOI: https://doi.org/10.1016/j.envres.2016.05.012
Xiong W, Xiao R, Deng L, Cai CS (2010) Methodology of long-term real-time condition assessment for existing cable-stayed bridges. Advances in Structural Engineering 13(1):111–125, DOI: https://doi.org/10.1260/1369-4332.13.1.111
Xu X, Huang Q, Ren Y, Sun HB (2018) Condition assessment of suspension bridges using local variable weight and normal cloud model. KSCE Journal of Civil Engineering 22(8):4064–4072, DOI: https://doi.org/10.1007/s12205-018-1819-3
Xu F, Wang X, Wang L (2011) Cable inspection robot for cable-stayed bridges: Design, analysis, and application. Journal of Field Robotics 28(3):441–459, DOI: https://doi.org/10.1002/rob.20390
Zarbaf SEHAM, Norouzi M, Allemang R, Hunt V, Helmicki A, Venkatesh C (2018) Vibration-based cable condition assessment: A novel application of neural networks. Engineering Structures 177: 291–305, DOI: https://doi.org/10.1016/j.engstruct.2018.09.060
Zhang S, Shen R, Wang T, De Roeck G, Lombaert G (2018) A two-step FEM-SEM approach for wave propagation analysis in cable structures. Journal of Soundand Vibration 415:41–58, DOI: https://doi.org/10.1016/j.jsv.2017.11.002
Zhang L, Wu X, Chen Q, Skibniewski MJ, Zhong J (2015) Developing a cloud model based risk assessment methodology for tunnel-induced damage to existing pipelines. Stochastic Environmental Research and Risk Assessment 29(2):513–526, DOI: https://doi.org/10.1007/s00477-014-0878-3
Acknowledgments
The authors acknowledge the financial support from the National Natural Science Foundation of China (No. 51474048) and the Fundamental Research Funds for the Central Universities (Grant No. N170104024).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Sun, S., Liang, L. & Li, M. Condition Assessment of Stay Cables via Cloud Evidence Fusion. KSCE J Civ Eng 25, 866–878 (2021). https://doi.org/10.1007/s12205-021-0139-1
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12205-021-0139-1