Wavelet-Based Analysis for Detection of Isolation Bearing Malfunction in a Continuous Multi-Span Girder Bridge

ABSTRACT

This paper describes techniques for detecting bearing malfunction directly from the seismic response of the bridge using wavelet transform time-varying identification. Instantaneous frequency of continuous wavelet and detail components of discrete wavelet transform are utilized as structural features, and they characterize isolation bearing condition via statistical clustering technique. Accuracy and efficacy of the techniques were verified in numerical simulations using analytical and finite element models. The techniques were implemented on seismic records from long-term monitoring of multi-span continuous-girder isolated bridge. Results demonstrate that wavelet-based features can effectively characterize the condition of the isolation bearing directly from seismic responses of girder and piers.

KEYWORDS:

• Wavelet analysis
• seismically isolated bridge
• structural assessment
• bearing malfunction
• seismic monitoring

Acknowledgement

This study is supported by the JSPS Grant-in-Aid Kakenhi C No. 18K04320 and partially by Taisei Foundation for the first author. These supports are gratefully acknowledged. We also gratefully acknowledge the supports from the Central Nippon Expressway Co. Ltd. (NEXCO) throughout the bridge instrumentation process. Opinions and findings in this paper are of the authors and not of the institutions named above.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This study is supported by the JSPS Grant-in-Aid Kakenhi C No. 18K04320 and partially by Taisei Foundation Fellowship to the first author.