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Structure and Infrastructure Engineering
Maintenance, Management, Life-Cycle Design and Performance
Volume 15, 2019 - Issue 4
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Original Articles

Condition evaluation of suspension bridges for maintenance, repair and rehabilitation: a comprehensive framework

ORCID Icon, ORCID Icon, , , &
Pages 555-567 | Received 20 Jun 2018, Accepted 26 Sep 2018, Published online: 16 Feb 2019
 

Abstract

To indicate health status of bridges and help stakeholders make decision on maintenance, a comprehensive framework has been proposed to evaluate structural efficiency of suspension bridges using analytic hierarchy process. First, the analytical hierarchy model (i.e. hierarchical network together with data aggregation algorithms) has been constructed using multi-source data, including visual inspection, non-destructive testing and structural health monitoring information. Age-dependent variable weight theory is developed to account for the service history of elements ensuring the alignment of variation trend of index weights with the objective law in bridge maintenance and management activities. To overcome the limitations of factor-based variable weight model for weight adjustment, the factor- and age-based variable weight model has been adopted for data aggregation. Finally, four cases are used to test the effectiveness of the three models (i.e. constant weight model, factor-based variable weight model and factor- and age-based variable weight model). By comparing the performance of the three models, the recommended maintenance strategy derived from factor- and age-based variable weight model aligns more with the actual strategy than the other two. The factor- and age-based variable weight model outperforms both the factor-based variable weight model and constant weight model in helping bridge owners make maintenance decisions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The research reported in this paper was supported in part by the National Natural Science Foundation of China under grant no. 51208096, the Key Science and Technology Project of Jiangsu Transport Department, China under grant no. 2014Y02 and China Scholarship Council and the Scientific Research Foundation of Graduate School of Southeast University under grant no. YBJJ1845.

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