Intelligent Fault Diagnosis for Bridge via Modal Analysis

Intelligent Fault Diagnosis for Bridge via Modal Analysis

Wenjun Zhuang
Copyright: © 2022 |Volume: 13 |Issue: 2 |Pages: 12
ISSN: 1947-8186|EISSN: 1947-8194|EISBN13: 9781683181705|DOI: 10.4018/IJISMD.313582
Cite Article Cite Article

MLA

Zhuang, Wenjun. "Intelligent Fault Diagnosis for Bridge via Modal Analysis." IJISMD vol.13, no.2 2022: pp.1-12. http://doi.org/10.4018/IJISMD.313582

APA

Zhuang, W. (2022). Intelligent Fault Diagnosis for Bridge via Modal Analysis. International Journal of Information System Modeling and Design (IJISMD), 13(2), 1-12. http://doi.org/10.4018/IJISMD.313582

Chicago

Zhuang, Wenjun. "Intelligent Fault Diagnosis for Bridge via Modal Analysis," International Journal of Information System Modeling and Design (IJISMD) 13, no.2: 1-12. http://doi.org/10.4018/IJISMD.313582

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Due to natural disasters and man-made reasons, bridges are prone to structural damage during long-term usage, which reduces the associated carrying capacity, increases natural aging, and reduces safety. It is urgent to monitor the health status of bridge structure via intelligent technology. This paper proposes a bridge fault recognition structure. First, the signals of bridge parameter are collected by using distributed sensors. Then, the collected signals are processed by signal processing to extract the features in time and frequency domain. Lastly, the extracted features are used to learn an intelligent classifier. The large margin distribution machine is adopted as a classification model. The experimental results have proven the feasibility of the proposed bridge fault recognition structure.