title: Unsupervised performance evaluation strategy for bridge superstructure based on fuzzy clustering and field data.
abstract: Performance evaluation of a bridge is critical for determining the optimal maintenance strategy. An unsupervised bridge superstructure state assessment method is proposed in this paper based on fuzzy clustering and bridge field measured data. Firstly, the evaluation index system of bridge is constructed. Secondly, a certain number of bridge health monitoring data are selected as clustering samples to obtain the fuzzy similarity matrix and fuzzy equivalent matrix. Finally, different thresholds are selected to form dynamic clustering maps and determine the best classification based on statistic analysis. The clustering result is regarded as a sample base, and the bridge state can be evaluated by calculating the fuzzy nearness between the unknown bridge state data and the sample base. Nanping Bridge in Jilin Province is selected as the engineering project to verify the effectiveness of the proposed method.
authors.affiliation: College of Transportation, Jilin University, Changchun 130025, China.
authors.forename: Yubo
authors.initials: Y
authors.lastname: Jiao
authors.forename: Hanbing
authors.initials: H
authors.lastname: Liu
authors.forename: Peng
authors.initials: P
authors.lastname: Zhang
authors.forename: Xianqiang
authors.initials: X
authors.lastname: Wang
authors.forename: Haibin
authors.initials: H
authors.lastname: Wei
mesh_terms: D016000:Cluster Analysis; D017143:Fuzzy Logic; D055883:Structure Collapse