Smart Structures and Systems

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Cable anomaly detection driven by spatiotemporal correlation dissimilarity measurements of bridge grouped cable forces

  • Dong-Hui, Yang (State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures, Shijiazhuang Tiedao University) ;
  • Hai-Lun, Gu (School of Civil Engineering, Dalian University of Technology) ;
  • Ting-Hua, Yi (School of Civil Engineering, Dalian University of Technology) ;
  • Zhan-Jun, Wu (State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology)
  • Received : 2022.06.01
  • Accepted : 2022.09.06
  • Published : 2022.12.25
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Abstract

Stayed cables are the key components for transmitting loads in cable-stayed bridges. Therefore, it is very important to evaluate the cable force condition to ensure bridge safety. An online condition assessment and anomaly localization method is proposed for cables based on the spatiotemporal correlation of grouped cable forces. First, an anomaly sensitive feature index is obtained based on the distribution characteristics of grouped cable forces. Second, an adaptive anomaly detection method based on the k-nearest neighbor rule is used to perform dissimilarity measurements on the extracted feature index, and such a method can effectively remove the interference of environment factors and vehicle loads on online condition assessment of the grouped cable forces. Furthermore, an online anomaly isolation and localization method for stay cables is established, and the complete decomposition contributions method is used to decompose the feature matrix of the grouped cable forces and build an anomaly isolation index. Finally, case studies were carried out to validate the proposed method using an in-service cable-stayed bridge equipped with a structural health monitoring system. The results show that the proposed approach is sensitive to the abnormal distribution of grouped cable forces and is robust to the influence of interference factors. In addition, the proposed approach can also localize the cables with abnormal cable forces online, which can be successfully applied to the field monitoring of cables for cable-stayed bridges.

Keywords

Acknowledgement

This research work was also jointly supported by the National Natural Science Foundation of China (Grants Nos. 52078102 and 52250011), the Fundamental Research Funds for the Central Universities (Grant No. DUT21JC38) and State Key Laboratory of Structural Analysis for Industrial Equipment (Grant No. GZ20105). The authors would like to thank the organizers of the 1st International Project Competition for SHM (IPC-SHM, 2020) for providing the invaluable data used in this paper.

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